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ALTERNATIVES FOR POWER GENERATION IN THE GREATER MEKONG SUB-REGION
Volume 3:
Power Sector Vision for the Lao People’s Democratic Republic
Final
20 March 2016
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Intelligent Energy Systems IESREF: 5973 ii
Disclaimer
This report has been prepared by Intelligent Energy Systems Pty Ltd (IES) and Mekong
Economics (MKE) in relation to provision of services to World Wide Fund for Nature (WWF).
This report is supplied in good faith and reflects the knowledge, expertise and experience of
IES and MKE. In conducting the research and analysis for this report IES and MKE have
endeavoured to use what it considers is the best information available at the date of
publication. IES and MKE make no representations or warranties as to the accuracy of the
assumptions or estimates on which the forecasts and calculations are based.
IES and MKE make no representation or warranty that any calculation, projection,
assumption or estimate contained in this report should or will be achieved. The reliance that
the Recipient places upon the calculations and projections in this report is a matter for the
Recipient’s own commercial judgement and IES accepts no responsibility whatsoever for any
loss occasioned by any person acting or refraining from action as a result of reliance on this
report.
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Acronyms
AD Anaerobic Digestion
ADB Asian Development Bank
ASEAN Association of Southeast Asian Nations
ASES Advanced Sustainable Energy Sector
BAU Business As Usual
BNEF Bloomberg New Energy Finance
BTU / Btu British Thermal Unit
CAGR Compound Annual Growth Rate
CAPEX Capital Expenditure
CCGT Combined Cycle Gas Turbine
CCS Carbon Capture and Storage
COD Commercial Operations Date
CSP Concentrated Solar Power
DNI Direct Normal Irradiation
DTU Technical University of Denmark
EDL Electricité du Laos
EE Energy Efficiency
EGAT Electricity Generation Authority of Thailand
EIA Energy Information Administration
EVN Electricity of Vietnam
FAO Food and Agriculture Organisation of the United Nations
FOB Free on Board
FOM Fixed Operating and Maintenance
GDP Gross Domestic Product
GHI Global Horizontal Irradiance
GMS Greater Mekong Subregion
GT Gas Turbine
HV High Voltage
ICT Information and Communication Technology
IEA International Energy Agency
IES Intelligent Energy Systems Pty Ltd
IPP Independent Power Producer
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IRENA International Renewable Energy Agency
LCOE Overall Levelised Cost of Electricity
LNG Liquefied Natural Gas
MEM Ministry of Energy and Mines
MERRA Modern Era-Retrospective Analysis
MKE Mekong Economics
MOU Memorandum of Understanding
MV Medium Voltage
NASA National Aeronautics and Space Administration (the United States)
NPV Net Present Value
NREL National Renewable Energy Laboratory (the United States)
OECD Organisation for Economic Co-operation and Development
OPEC Organisation of the Petroleum Exporting Countries
OPEX Operational Expenditure
PDR People’s Democratic Republic (of Laos)
PRC People’s Republic of China
PV Photovoltaic
RE Renewable Energy
ROR Run of River
SCADA/EMS Supervisory Control and Data Acquisition/Energy Management System
SES Sustainable Energy Sector
SWERA Solar and Wind Energy Resource Assessment
SWH Solar Water Heating
UN United Nations
USD United States Dollar
VOM Variable Operating and Maintenance
WEO World Energy Outlook
WWF World Wide Fund for Nature
WWF-GMPO WWF – Greater Mekong Programme Office
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Table of Contents
1 Introduction 7
1.1 Report Structure 7 2 Background: Lao PDR Electricity Sector 9
2.1 Industry Structure 9 2.2 Power System 10 2.3 Installed Capacity 12 2.4 Electricity Demand 13 2.5 Generation Supply 15 2.6 Exports and Imports 16
3 Development Options for Lao PDR Electricity Sector 20
3.1 Natural Gas Resources 20 3.2 Coal Resources 20 3.3 Hydro Power 21 3.4 Wind Power 22 3.5 Solar Power 25 3.6 Geothermal Energy 29 3.7 Biomass and Biogas 29 3.8 Renewable Energy Potential and Diversity 31
4 Lao PDR Development Scenarios 33
4.1 Scenarios 33 4.2 Technology Cost Assumptions 36 4.3 Fuel Pricing Outlook 38 4.4 Lao PDR Real GDP Growth Outlook 39 4.5 Population Growth 41 4.6 Committed Generation Projects in BAU, SES and ASES Scenarios 41 4.7 Regional Transmission System Integration 42 4.8 Imports and Exports 43 4.9 Technical Economic Power System Modelling 43
5 Business as Usual Scenario 46
5.1 Business as Usual Scenario 46 5.2 Demand Growth 46 5.3 Installed Capacity Development 48 5.4 Projected Generation Mix 51 5.5 Grid to Grid Power Flows 54 5.6 Generation Fleet Structure 54 5.7 Reserve Margin and Generation Trends 56 5.8 Electrification and Off Grid 58
6 Sustainable Energy Sector Scenario 59
6.1 Sustainable Energy Sector Scenario 59 6.2 Demand Growth 59 6.3 Installed Capacity Development 61 6.4 Projected Generation Mix 64 6.5 Grid to Grid Power Flows 67 6.6 Generation Fleet Structure 67 6.7 Reserve Margin and Generation Trends 69 6.8 Electrification and Off-Grid 71
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7 Advanced Sustainable Energy Sector Scenario 72
7.1 Advanced Sustainable Energy Sector Scenario 72 7.2 Demand Growth 72 7.3 Installed Capacity Development 74 7.4 Projected Generation Mix 77 7.5 Grid to Grid Power Flows 80 7.6 Generation Fleet Structure 80 7.7 Reserve Margin and Generation Trends 82 7.8 Electrification and Off-Grid 84
8 Analysis of Scenarios 85
8.1 Energy and Peak Demand 85 8.2 Energy intensity 87 8.3 Generation Mix Comparison 88 8.4 Carbon Emissions 90 8.5 Hydro Power Developments 91 8.6 Analysis of Bioenergy 91 8.7 Security of Supply Indicators 93 8.8 Interregional Power Flows 95
9 Economic Implications 97
9.1 Overall Levelised Cost of Electricity (LCOE) 97 9.2 LCOE Composition 98 9.3 Cumulative Capital Investment 100 9.4 Operating, Amortised Capital and Energy Efficiency Costs 105 9.5 Fuel Price Sensitivity 110 9.6 Impact of a Carbon Price 110 9.7 Renewable Technology Cost Sensitivity 111 9.8 Jobs Creation 112
10 Conclusions 115
10.1 Comparison of Scenarios 115 10.2 Economic Implications 116 10.3 Identified Barriers for the SES and ASES 117 10.4 Recommendations 118
Appendix A Technology Costs 120
Appendix B Fuel Prices 124
Appendix C Methodology for Jobs Creation 125
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1 Introduction
Intelligent Energy Systems Pty Ltd (“IES”) and Mekong Economics (“MKE”) have been
retained by WWF – Greater Mekong Programme Office (“WWF-GMPO”) to undertake a
project called “Produce a comprehensive report outlining alternatives for power generation
in the Greater Mekong Sub-region”. This is to develop scenarios for the countries of the
Greater Mekong Sub-region (GMS) that are as consistent as possible with the World Wildlife
Fund’s Global Energy Vision to the Power Sectors of all Greater Mekong Subregion countries.
The objectives of WWF’s vision are: (i) contribute to reduction of global greenhouse
emissions (cut by >80% of 1990 levels by 2050); (ii) reduce dependency on unsustainable
hydro and nuclear; (iii) enhance energy access; (iv) take advantage of new technologies and
solutions; (v) enhance power sector planning frameworks for the region: multi-stakeholder
participatory process; and (vi) develop enhancements for energy policy frameworks.
The purpose of this report is to provide detailed country-level descriptions of three scenarios
for the power sector of Lao People’s Democratic Republic (Lao PDR):
Business as Usual (BAU) power generation development path which is based on current
power planning practices, current policy objectives;
Sustainable Energy Sector (SES) scenario, where measures are taken to maximally
deploy renewable energy1 and energy efficiency measures to achieve a near-100%
renewable energy power sector; and
Advanced Sustainable Energy Sector (ASES) scenario, which assumes a more rapid
advancement and deployment of new and renewable technologies as compared to the
SES.
The scenarios were based on public data, independent assessments of resource potentials,
information obtained from published reports and power system modelling of the GMS region
for the period 2015 to 2050. All projections presented in this report commence in the year
2015.
1.1 Report Structure
This report has been organised in the following way:
Section 2 sets out recent outcomes for Lao PDR’s electricity industry;
Section 3 summarises the main development options covering both renewable energy
and fossil fuels;
Section 4 provides a brief summary of the scenarios that were modelled and a summary
of the assumptions in common;
Section 5 sets out the key results for the business as usual scenario;
1 Proposed but not committed fossil fuel based projects are not developed. Committed and existing fossil fuel based projects are retired at the end of their lifetime and not replaced with other fossil fuel projects. A least cost combination of renewable energy generation is developed to meet demand.
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Section 6 sets out the key results for the sustainable energy sector scenario;
Section 7 sets out the key results for an advanced sustainable energy sector scenario;
Section 8 provides comparative analysis of the three scenarios based on the
computation of a number of simple metrics that facilitate comparison;
Section 9 provides analysis of the economic implications of the scenarios; and
Section 10 provides the main conclusions from the modelling.
The following appendices provide some additional information for the scenarios:
Appendix A contains the technology cost assumptions that were used;
Appendix B provides the fuel price projections that were used; and
Appendix C sets out information used to estimate jobs creation potential for each
scenario.
Note that unless otherwise noted, all currency in the report is Real 2014 United States Dollars
(USD).
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2 Background: Lao PDR Electricity Sector
2.1 Industry Structure
The governance structure of Lao PDR’s electricity industry is illustrated in Figure 1.
Figure 1 Lao PDR Electricity Industry Governance Structure2
Source: Power to the People: Twenty Years of National Electrification, World Bank, 2012
The Ministry of Energy and Mines (MEM) under the Prime Ministry’s Office is the central
agency in charge of the energy sector and of renewable energy, and has the leading role in
preparing the country's renewable energy strategy. The MEM manages the electricity sector
through the Department of Electricity. A more specific statement of the policy objectives is:
Expand and improve the main grid supplies;
Expand and improve rural electrification;
Increase energy self-sufficiency and security;
Implement power projects that maximise long-term sustainability;
Develop power trade with GMS countries;
Develop IPP project selection and implementation procedures;
2 The Department of Energy Business, not shown in the chart, sits under the MEM and was established to share information on the Lao Government’s hydro power development plan and took over the role of Department of Energy promotional development since 2006. The Institute of Renewable Energy Promotion under MEM oversees the implementation of renewable energy, energy efficiency and rural electrification programs in Lao PDR.
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Maximise the benefits to Lao PDR from IPP developments; and
Develop transmission infrastructure for regional power trade.
Electricité du Laos (EDL) is wholly-owned by the government and owns and operates
vertically integrated generation, transmission and distribution assets in Lao PDR. EDL is
responsible for developing generation, transmission and distribution projects to meet policy
directives. As such they also perform system planning and manage electricity imports to and
electricity exports from the Lao PDR grid.
2.2 Power System
A representation of Lao PDR’s generation and transmission systems is shown in Figure 2. The
diagram highlights the present statehood of the country's national system in terms of the
main hydropower generation resources and 115 kV transmission lines that are used in the
power system and their locations within the country. We have also indicated the installed
capacity of each generator and highlighted whether the electricity is delivered for meeting
domestic demand or for exporting.
EDL operates the transmission and distribution network in the three regions of central,
northern and southern Lao PDR covering the 17 provinces. The Central 1 and Central 2
regions were integrated into a single region in 2011, however the three regions (115 kV
systems) remain isolated from each other. In addition to the main grid operated by EDL,
provincial authorities operate some 85 mini grids that are supplied by diesel generators or
small-scale hydro power stations in remote areas. These facilities primarily serve remote
areas that are not yet part of the national grid.
There is a significant amount of power exchange between Lao PDR and neighbouring
countries. Power is imported at a number of border points to meet local demand and
exported from dedicated hydro plants at other points. The largest exporter to Lao PDR is
neighbouring Thailand; however, some provinces receive power from Vietnam. On the other
hand, there are generation plans that largely export their electricity to Thailand, Viet Nam,
People’s Republic of China (PRC) and Cambodia. EDL effectively acts as a single buyer and
negotiates the terms and conditions for power imports and exports. To provide an indication
of the location of current installed capacity of hydro plants and whether the hydros are
geared towards serving Lao PDR’s national electricity system or for export, Figure 3 shows
installed capacity statistics by region and by type (whether export-oriented hydro or not).
Pertinent features of the Lao PDR power system as at 2013 are summarised below:
State-owned generation and network managed by a central electricity authority (EDL);
Generation capacity mostly owned by independent power producers (IPPs);
Total energy final demand of 3,381 GWh;
Low per capita consumption of 500 kWh per year;
High transmission and distribution losses;
Network connections with Thailand, China and Vietnam;
Imports of around one-third of its total electricity requirements and exported 690
GWh; and
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Household electrification ratio was 87%.
Figure 2 Map of Lao PDR Generators Map (2014)
Source: EDL
Nam Nhon
Nam Dong
Nam Ngay
Nam Ngum 5
Nam Long
Nam Ko
Nam Tha 3
Tad Salen
Nam Lik Nam Ngum 2
Nam Phao
Selabam
Nam Ngum 1
Theun HinbounNam Mang 3
Nam Theun 2
Nam Song
Xe Kaman 3Xe Set 1
Xe Set 2
Houay Ho
Nam Leuk
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Figure 3 Installed Hydro Capacity by Region and Type
2.3 Installed Capacity
All of the generation projects in Lao PDR were traditionally based on hydro power although
this has recently changed with the commissioning of the first 626 MW unit of the Hong Sa
Lignite Power Project in Xayaboury province early 2015.
As of 2014, 3,058 MW has been developed with most of this exported into Thailand and to a
smaller extent Vietnam. The levels of export into Thailand and Vietnam is set to increase with
the Government of Lao PDR signing MOUs that commit to the export of up to 7,000 MW to
Thailand and 5,000 MW to Vietnam by 20203. By March 2016 the coal-fired Hong Sa Lignite
Power Project will have a total of capacity of 1,878 MW, with some 1,473 MW having already
been sold to the Electricity Generation Authority of Thailand (EGAT). At present, there are
more than 50 hydropower sites planned to achieve the 2020 export target. The Lao PDR
Government and foreign investors jointly develop most of these exporting projects.
The current generation fleet in Lao PDR is shown in Table 1 and comprises of 610 MW owned
by EDL and 3,211 MW owned by independent power producers.
3 Lao PDR Country Report, Department of Energy Policy and Planning Ministry of Energy and Mines, 2013
13
228
- 8 -
870
1,588
523
-
200
400
600
800
1,000
1,200
1,400
1,600
Northern Central 1 Central 2 Souith
MW
Lao Hydro Export Hydro
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Table 1 Existing Large-scale Generators in Lao PDR
Generator Type Owner Capacity (MW)
Nam Ngum Hydro EDL 155
Nam Dong Hydro EDL 1
Xelabam Hydro EDL 5
Xeset 1 Hydro EDL 45
Nam Leuk Hydro EDL 60
Nam Ngay Hydro EDL 1.2
Nam Mang 3 Hydro EDL 35
Nam Ko Hydro EDL 1.5
Xeset2 Hydro EDL 76
Nam 1-2 Hydro EDL 100
Nam Ngum 5 Hydro EDL 120
Nam Nhone Hydro EDL 3
Tatsalen Hydro EDL 3
Nam Long Hydro EDL 5
Houay Ho Hydro IPP 150
Theun Hinboun Hydro IPP 490
Nam Theun 2 Hydro IPP 1,080
Nam Ngum 2 Hydro IPP 615
Xekaman 3 Hydro IPP 250
Hong Sa Lignite #1 Lignite IPP 626
Source: Various – as Compiled by Consultant
2.4 Electricity Demand
Figure 4 shows Lao PDR’s total final electricity consumption and the annual growth rates from
1996 to 2013. It indicates domestic demand has been growing rapidly; in particular, annual
electricity consumption increased at an average rate of 14.5% per annum over 10 years from
903 GWh in 2004 to 3,381 GWh in 2013. Electricity consumption has been traditionally
dominated by residential consumption, which made up 42% in 2010 dropping to 38% in 2013
(Figure 5). Industry consumption as at 2013 accounted for 33% of total electricity
consumption. This trend is expected to continue with additional industrial load to come
online over the next few years as part of the Government’s industrial development plans.
By 2013, the power system had a peak demand of 649 MW, which has been growing 12.5%
per annum over a 10 year period, and nearly doubled since 2008. Figure 6 indicates the
locations of main load centres, which include Vientiane capital city, Vientiane province,
Savannakhet, Khammouane and Champasak provinces.
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Figure 4 Electricity Demand Growth (1996-2013)
Source: Electricity Statistics 2013, Electricite Du Laos, 2014
Figure 5 Electricity Demand Shares by Category (2013)
0%
5%
10%
15%
20%
25%
-
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
An
nu
al A
vera
ge G
row
th (
%)
Dem
and
(G
Wh
)
Total Electricity Consumption Annual Average Growth Rate
Residential37.8%
Commercial21.7%
Entertainment0.3%
Gov. office5.6%
Irrigation1.0%
Int. Orgs0.3% Industry
33.1%
Edu. & Sport0.2%
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Figure 6 Main Load Centres (2013)
2.5 Generation Supply
Figure 7 shows annual statistics generation, import and export of electricity from 1991 to
2012. It indicates that while it had significantly increased its own generation supply (which
was entirely from hydropower), Lao PDR also had to import more electricity to meet the
domestic demand.
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Figure 7 Generation, Imports and Exports (1991-2012)
2.6 Exports and Imports
With many hydropower projects having been proposed, Lao PDR is expected to increase
electricity exports to neighbouring Thailand, and Vietnam to a lesser extent. The export of
energy via wider electricity trading arrangements in the surrounding regions is viewed by the
government as an opportunity to improve EDL’s financial position, foster economic growth
and over the longer-term reduce poverty.
The Lao PDR has various cross-border connections with other GMS neighbouring countries.
The numbers of agreed MOU interconnections and capacities between Lao PDR and each
country as at 2014 are4:
Thailand: 23 interconnections, 10,000 MW;
Vietnam: 7 interconnections, 5,000 MW; and
Lao PDR: 2 interconnections, 2,000 MW.
Dedicated transmission lines link each of the export IPP power plants into the respective off-
take countries. Links as at 2014 are:
Theun Hinboun to Sakhonnakhon (Electricity Generating Authority of Thailand - EGAT)
230 kV, 176 km, 440 MW (includes power station expansion);
Houay Ho to Ubon 2 (EGAT) 230 kV, 230 km, 150 MW;
4 IFC Workshop on Sustainable Hydropower & Regional Cooperation, Viravong, 2015
-
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
2,200
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
GW
h
Generation Imports Exports
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Nam Theun 2 to Roi Et (EGAT) 500 kV, 300 km, 1,000 MW;
Na Bong to Udon 3 (EGAT), 500 kV, 100 km, 615 MW; and
Xekaman 3 to Thanh My (Electricity of Vietnam - EVN) 230 kV, 150 km, 250 MW.
Lao PDR exports a large amount of hydropower to Thailand, but in exchange imports
electricity to supply provinces that are not connected to the national power grid. These
demand points include copper and gold mining operations, which consume significant
amounts of power.
Lao PDR also has 4 interconnections with China, with capacity of 2,000 MW to ensure
adequate power supplies in Luang Prabang and the Northern provinces. The interconnection
allows for power imports from China due to lower river levels up north and would indirectly
relieve pressure on the central Lao PDR hydro plants.5
The shares of neighbouring countries in Lao PDR exports and imports of electricity for 2013
are presented in Figure 8 and Figure 9. The approximate geographical representation of
power exchanges is shown in Figure 10.
Figure 8 Export and Import Shares by Country (2013)
Figure 9 Historical Annual Exports (2010-13)
5 http://www.vientianetimes.org.la/FreeContent/FreeConten_Laos%20imports.htm, accessed 20 May 2015
Exports to Thailand
71%
Exports to Cambodia
29%
Thailand (EGAT)
73%
Thailand (PEA)
7%
Vietnam2%
China18%
-
200
400
600
800
2010 2011 2012 2013
GW
h
Exports to Thailand Exports to Cambodia
Imports Exports
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Figure 10 Illustrative Flows of Cross Border Exports (2013)
Source: EDL
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Figure 11 Illustrative Flows of Cross Border Imports (2013)
Source: EDL
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3 Development Options for Lao PDR Electricity Sector
3.1 Natural Gas Resources
Lao PDR has no confirmed reserves of oil or gas, however, the Government has issued two
exploration concessions in central and southern Lao (Salamander Energy Group and Petro
Vietnam respectively)6. Significant work remains to be done to determine the results.
Based on this the likelihood of indigenous oil or gas reserves making an impact to the
electricity sector development in the next 10-20 years is low.
Consequently, Lao PDR imports petroleum products from other countries, with these
products being used approximately as follows:
88% used in transport sector;
11% used in the commercial sector; and
The remainder for residential, industry and agriculture.
3.2 Coal Resources
Lao PDR has coal reserves estimated at approximately 900 million tons7, comprising mostly
of lignite, and anthracite to a much smaller extent at various sites. Figure 12 shows the
location of coal deposits and occurrences in Lao PDR. Main lignite basins lie in Hong Sa,
Viengphoukha and Khangphaniang. Located in the northwestern region, Hong Sa is the
largest known reserve of lignite, with 400-700 million tons being reserved for power
generation. The country’s first coal-fired power plant - 1,878 MW Hong Sa Lignite Power
Project - would be completed by 2016 with 1,473 MW already sold to EGAT.
Anthracite (and bituminous) can be found at various sites, including Saravan and PHong
Saly provinces, with the total proven resource at approximately 100 million tons. Currently
130,000 tons of production is used for local factories and export purposes and the
government has a plan to support a 500 MW coal unit depending on further exploration
success.
6 Energy Sector Development in Lao PDR, Vongsay, 2013
7 Energy Sector Development in Lao PDR, Vongsay, 2013
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Figure 12 Location of Coal Deposits and Occurrences
3.3 Hydro Power
Hydropower is the most abundant energy resource in Lao PDR. There is an estimated
potential of 23,000 MW along the Mekong River and its sub-basins. By 2014, around 3,200
MW has been developed and is supplying domestic demand and neighbouring countries.
Table 2 below shows the hydro expansion plan to 2020. There is currently 6,000 MW of
committed projects in the pipeline with 75% of it planned for export. For implementation of
this plan, the Lao Government has opened up development opportunities to the
neighbouring governments (Thailand, Lao PDR, and Vietnam) and foreign companies.
The country’s small hydropower potential is also substantial, estimated to be around 2,000
MW. The development of small hydropower (capacity up to 15 MW) could also play an
important role in meeting the country’s objectives of increasing rural electrification coverage
from the current level of 70% to 90% in 20208. There are 75 smaller hydro projects as at the
8 Note that we refer to rural coverage in these statistics, the earlier stated “87%” relates to rural and urban.
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end of 2013 at various stages. There are also approximately 60,000 micro units installed in
Lao PDR servicing 90,000 households.
Figure 13 summarises the information about capacity of the existing, committed and
considered projects in Lao PDR.
Table 2 Hydroelectric Power Development Plan (2016-20)
Region No. Projects Capacity (MW) Production (GWh/yr)
Northern 31 1,623 7,783
Central 19 323 1,524
Southern 27 905 4,729
Total 77 2,851 14,036
Source: Electricite du Lao, 2011
Figure 13 Lao PDR Hydro Projects: Existing, Committed and Considered (2014)
Source: Compiled by Consultant
3.4 Wind Power
Lao PDR has a wind potential estimated at approximately 26,000 square kilometres with
wind speeds between 7-9 m/s. Table 3 shows the wind resource available in Lao PDR and
some of the other GMS countries. The resource mapping shows approximately 2,800 MW
2,426
1,635
3,632
1,288
2611.8
611
2,335
250
- 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000
Other Considered (Potential Thailand Export)
Other Considered (Potential Vietnam Export)
Considered on Mekong (Potential Thailand Export)
Considered on Mekong (Potential Vietnam Export)
Committed (2020)
Existing (Lao PDR)
Existing (Export - Thailand)
Existing (Export - Vietnam)
MW
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at ‘very good’ and ‘excellent’ wind speeds and 24,280 MW at locations with ‘good’ wind
speeds.
Table 3 Wind Resource Potential in Lao PDR9
Poor Fair Good Very Good Excellent
Parameter Unit < 6 m/s [6, 7) m/s [7, 8) m/s [8, 9) m/s >= 9 m/s
Land Area km^2 184,511 38,787 6,070 671 35
% total % 80.2% 16.9% 2.6% 0.3% 0.0%
Potential MW na 155,148 24,280 2,684 140
Source: Wind Energy Resource Atlas of Southeast Asia, TrueWind Solutions, 2001
Lao PDR wind power potential has also been estimated in a recent ADB study entitled
“Renewable Energy Developments and Potential in the Greater Mekong Subregion” (2015).
According to this study, Lao PDR has a theoretical wind energy potential of 455 GW and a
potential production capacity of about 1,112 TWh/yr. To obtain these estimates, the land
area suitable for wind power result was multiplied by the average amount of wind power
capacity that can be installed in a given area (assumed to be 10 MW/km2). However, the
technical wind energy potential would be much less due to the limitations of the overall
power generation and transmission grid systems.
An illustration of the dispersion of wind potential is charted in Figure 14. This shows 3TIER’s
Global Wind Dataset10 , which provides average annual wind speed at 80 meters above
ground level. This illustrates regions of high potential along the border with Vietnam and in
the south of the country, as well as pockets of 6 to 7 m/s potential in the north. Figure 15
shows the DTU Global Wind Atlas11 onshore and 30 km offshore wind climate dataset which
accounts for high resolution terrain effects for 100 m above ground level. According to the
IRENA global atlas description: “this was produced using microscale modelling in the Wind
Atlas Analysis and Application Program and capture small scale spatial variability of winds
speeds due to high resolution orography (terrain elevation), surface roughness and surface
roughness change effects. The layers shared through the IRENA Global Atlas are served at
1km spatial resolution.”
The Government is planning to develop 50 MW of wind power by 2025 to promote the
development of wind energy in the country.
9 For large wind turbines only. Potential MW assumes an average wind turbine density of 4 MW per square kilometre and no exclusions for parks, urban, or inaccessible areas. Wind speeds are for 65 m height in the predominant land cover with no obstructions.
10 Source: 3TIER data set was accessed via the IRENA Global Atlas Server: http://irena.masdar.ac.ae/.
11 See: http://globalwindatlas.com/.
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Figure 14 3TIER’s Global Wind Dataset 5km onshore wind speed at 80m height12
Source: 3TIER’s Global Wind Dataset (accessed via IRENA Global Atlas)
12 Average for period from 1980 to 2011.
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Figure 15 Average Wind Speed 1km at 100 m AGL DTU (2015)
Source: IRENA Global Atlas and Global Wind Atlas (2015)
3.5 Solar Power
Solar energy is an abundant energy resource in Lao PDR. The southern part of the country
experiences slightly higher irradiation levels and would be suitable for the deployment of
solar technologies (see Figure 16).
Lao PDR solar power potential has also been estimated in a recent ADB study entitled
“Renewable Energy Developments and Potential in the Greater Mekong Subregion” (2015).
According to this study, Lao PDR has a potential of 8,812 MW of combined peak solar
capacity, which far exceeds the earlier estimates 13 . The details of estimates of solar
potential are in Table 4. Lao PDR has GHI levels ranging between 1,200 and 1,800 kWh/m2
13 Based on analysis of high resolution measurements and comparisons of Lao PDR solar maps to other countries, IES views solar potential in Lao PDR to be at least 11,000 MW.
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pa and average DNI levels around 1,350 kWh/m2 per annum14, however, the hotter regions
in Lao PDR have DNI levels between 1,600 to 1,800 kWh/m2 pa which can accommodate
CSP technology.
Figure 16 Lao PDR DNI Solar Resource Map (kWh/m^2 per day)
Source: Solar and Wind Energy Resource Assessment, accessed 15 April 2015
14 Source: ADB, “Renewable Energy Developments and Potential in the Greater Mekong Subregion”, 2015.
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Table 4 Lao PDR Solar Power Technical Potential
Solar Irradiation
Level, kWh/m2
Suitable Land Areas,
thousand km2
Technical Capacity
Potential, MW
Technical Production
Potential, MWh/yr
Less than 1,200 - - -
1,200–1,300 0.09 5 5,613
1,300–1,400 1.88 113 125,148
1,400–1,500 12.84 770 918,500
1,500–1,600 41.02 2,461 3,137,931
1,600–1,700 69.14 4,149 5,630,307
1,700–1,800 21.89 1,313 1,890,265
Over 1,800 - - -
Total 146.9 8,812 11,707,764
Source: Renewable Energy Developments and Potential in the Greater Mekong Subregion, ADB, 2015
Figure 17 plots the monthly average irradiation levels for a number of selected sights with
the highest annual average irradiation levels based on SWERA data. This shows the monthly
variation throughout the year for solar irradiation and hence generation. This highlights
November through to March exhibit excellent solar conditions. The map shading the
locations of solar for Lao PDR is provided in Figure 18. This also highlights that the greatest
potential for solar lies in the central region of the country, covering the main load centre of
Vientiane.
Figure 17 Monthly DNI Levels for Selected Locations in Lao PDR
Source: NASA Atmosphere Science Data Centre, obtained via the SWERA Geospatial Toolkit
0
1
2
3
4
5
6
7
8
9
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Ave
rage
-kW
h/d
ay
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Figure 18 Main Locations with DNI Solar Power Potential in Lao PDR
Source: Developed by Consultant based on Information from EDL and SWERA
Figure 19 plots measurements of Global Horizontal Irradiance (GHI) based on the 3TIER high
resolution dataset accessed via the IRENA Global Atlas. This map shows that the GHI
potential is significant throughout the entire country.
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Figure 19 3TIER’s Global Solar Dataset (3km in W/m^2) for GHI
Source: 3TIER’s Global Solar Dataset (accessed via IRENA Global Atlas)
3.6 Geothermal Energy
According to a recent study15, 11 geothermal resources have been identified in a study in the
country’s northern mountainous areas. These sources are believed to be of the low
temperature type and unlikely to support power projects on a large scale. The Asian
Development Bank (ADB) has however reported that some 59 MW of geothermal generation
capacity could be developed in Lao PDR.
3.7 Biomass and Biogas
Lao PDR has vast forest coverage around 100,000 square kilometres or about 45% of its
land. In addition, a large amount of agricultural residues representing significant energy
potential can be harvested. The total electricity potential from biomass is estimated at 938
MW16. Table 5 shows the biomass source and energy potential. IES projected estimates
15 Nguyen Tien Hung et al, “Overview of geothermal resources in North Part of Laos”, Proceedings World Geothermal Congress 2015, Melbourne, Australia
16 Renewable Energy Development Strategy in Lao PDR, 2011
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based on the ADB study “Renewable Energy Developments and Potential in the Greater
Mekong Subregion” suggest an energy potential of around 17,000 GWh/yr or up to 2,300
MW.
Table 5 Energy Potential from Agriculture and Forestry Residues
Biomass sources Type of fuel Equivalent energy (GWh/yr)
Rice husk Combustive 2,108
Rice straw Biogas 1,030
Husbandry Biogas 3,269
Forest residues Combustive 12,500
Total Various 18,907
Source: Rural Electrification in Lao PDR and Lao PDR, Innovation Energie Developpement, 2007
Biogas energy technical potential from livestock manure has been estimated at around
8,540 MWh per day according to ADB 2015 study. Details are in Table 6 below.
Table 6 Lao PDR Biogas Technical Potential
Livestock Net Dry Matter
Available
(kg/day)
Mean Biogas Yield Factor
(m3/kg)
Daily Biogas
Production
(m3/day)
Energy Content
per Day
(kWh/day)
Buffalo 1,094.337 0.25 273,584 1,641,505
Cows 1,359,147 0.25 339.787 2,038,721
Pigs 192.835 4.20 809,908 4,859,448
Total 2,646,319 1,423,279 8,539,674
Source: Renewable Energy Developments and Potential in the Greater Mekong Subregion, ADB, 2015
Figure 20 shows the existing biomass capacity installed and 2025 targets. There are
currently two large-scale biomass projects operating in the central and south region. The
Hoang Anh Sugar Mill has a capacity of 30 MW in the Attapeau province and the Mit Lao
Sugar Mill is located in the Savannakhet province with a capacity of 9.7 MW.
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Figure 20 Current Biomass and Biogas Developments and Targets (MW)
Source: Country Presentation on Status of Bioenergy Development in Lao PDR, IEA, IRENA, FAO, 2014
3.8 Renewable Energy Potential and Seasonal Diversification
In summary, the renewable energy potential for Lao PDR is provided in Table 7. The
numbers presented here have been drawn from multiple sources and informed by analysis
of the IRENA Global Atlas data. Figure 21 plots the monthly capacity factors for solar, wind
and hydro against the normalised average monthly demand. The chart shows that there is
some natural seasonal / monthly diversification between resources: demand in Lao PDR is
highest peaking between March to May which coincides with reduction in wind speeds in
Lao PDR. There is a clear diversification benefit as the solar intensity drops towards the
middle of the year and wind speeds and hydro inflows start to increase.
It should be noted that the key issue in the charts is correlation but not amplitude, and
furthermore, that the hydro inflows fall into reservoirs, some with significant amount of
storage, which enables smoothing out generation throughout the year (within the limits of
the storage capacity of the reservoirs), thus there is some scope for the role / operation of
hydro power stations to change in Lao PDR to accommodate high levels of renewable energy.
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Table 7 Summary of Estimated Renewable Energy Potential (Compiled from
Various Sources and Analysis)
Resource Potential (MW)
Source and comments
Hydro (Large) 23,000 Lao hydropower potential and policy in the GMS context (EDL)
Hydro (Small) 2,000 Sites smaller than 15 MW. The Need for Sustainable Renewable Energy in Lao PDR (Vongchanh)
Pump Storage - Given the abundance of conventional hydro potential there has been little focus in Lao PDR to assess the potential of this technology.
Solar At least 11,000
IES assessment based on various sources set out in 3.5.
Wind Onshore 27,104 Resource above 7m/s. Wind Energy Resource Atlas of Southeast Asia (TrueWind Solutions, 2001)
Wind Offshore 0 Not applicable
Biomass 1,271 IES projections based on data from Renewable Energy Developments and Potential in the Greater Mekong Subregion (ADB, 2015)
Biogas 1,146 IES projections based on data from Renewable Energy Developments and Potential in the Greater Mekong Subregion (ADB, 2015)
Geothermal 59 Lao PDR Energy Sector Assessment, Strategy, and Road Map (ADB, 2013)
Ocean - Not applicable
Figure 21 Seasonality in Renewable Resource Profiles and National Demand
Source: Consultant analysis
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Hydro Wind Solar Demand
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4 Lao PDR Development Scenarios
In this section, we define the three scenarios for Lao PDR’s electricity sector that we have
modelled: the Business as Usual (BAU), Sustainable Energy Sector (SES), and Advanced SES
(ASES) scenarios. We also set out the assumptions made for technology costs (section 4.2)
and fuel prices (section 4.3) before providing the details for a number of Lao PDR specific
assumptions – in particular: our assumed economic outlook for Lao PDR, a list of generation
projects that we consider committed 17 and comments on the status of power import
projects. Further assumptions for each scenario are provided in Section 5, Section 6 and
Section 7.
4.1 Scenarios
The three development scenarios (BAU, SES and ASES) for Lao PDR are conceptually
illustrated in Figure 22.
Figure 22 GMS Power Sector Scenarios
The BAU scenario is characterised by electricity industry developments consistent with the
current state of planning within the GMS countries and reflective of growth rates in electricity
demand consistent with an IES view of base development, existing renewable energy targets,
where relevant, aspirational targets for electrification rates, and energy efficiency gains that
are largely consistent with the policies seen in the region.
17 That is, construction is already in progress, the project is near to commissioning or it is in an irreversible / advanced state of the planning process.
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In contrast, the SES seeks to transition electricity demand towards the best practice
benchmarks of other developed countries in terms of energy efficiency, maximise the
renewable energy development, cease the development of fossil fuel resources, and make
sustainable and prudent use of undeveloped conventional hydro resources. Where relevant,
it leverages advances in off-grid technologies to provide access to electricity to remote
communities. The SES takes advantage of existing, technically proven and commercially
viable renewable energy technologies.
Finally the ASES assumes that the power sector is able to more rapidly transition towards a
100% renewable energy technology mix under an assumption that renewable energy is
deployed more than in the SES scenario with renewable energy technology costs declining
more rapidly compared to BAU and SES scenarios. A summary of the main features of the
three scenarios are summarised in Table 818.
Table 8 Key Features of BAU, SES and ASES
Scenario Demand Supply
BAU Demand was forecast to grow in line
with historical electricity consumption
trends and projected GDP growth rates
using techniques that are largely the
same as what is typically done in
government plans. Electric vehicle
uptake was assumed to reach 10%
across all cars and motorcycles by 2050.
Generator new entry follows that of power
development plans for the country
including limited levels of renewable
energy but not a maximal deployment of
renewable entry.
SES Assumed a transition towards
energy efficiency benchmark for the
industrial sector of Hong Kong19 and
of Singapore for the commercial
sector by year 2050.
For the residential sector, it was
assumed that urban residential
demand per electrified capita grows
to 800 kWh pa by 2050, 40% less
than in the BAU.
Demand-response measures were
assumed to be phased in from 2021
with some 15% of demand being
flexible20 by 2050.
Assumed no further coal and gas new
entry beyond what is already
understood to be committed.
A modest amount of large scale hydro
(between 4,000 to 5,000 MW) was
deployed in Lao PDR and Myanmar
above and beyond what is understood
to be committed hydro developments
in these countries21.
Supply was developed based on a least
cost combination of renewable
generation sources limited by
estimates of potential rates of
deployment and judgments in on
18 Note that we summarise the key drivers here. For further details, please refer to the separate IES assumptions document.
19 Based on our analysis of comparators in Asia, Hong Kong had the lowest energy to GDP intensity for industrial sector while Singapore had the lowest for the commercial sector.
20 Flexible demand is demand that can be rescheduled at short notice and would be implemented by a varie ty of smart grid and demand response technologies.
21 This is important to all countries because the GMS is modelled as an interconnected region.
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Slower electrification rates for the
national grids in Cambodia and
Myanmar compared to the BAU, but
deployment of off-grid solutions
that achieve similar levels of
electricity access.
Mini-grids (off-grid networks) were
assumed to connect to the national
system in the longer-term for
reliability / mutual support reasons.
Electric vehicle uptake was as per
the BAU.
when technologies would be feasible
for implementation to deliver a power
system with the same level of
reliability as the BAU.
Technologies used include: solar
photovoltaics, biomass, biogas and
municipal waste plants, CSP with
storage, onshore and offshore wind,
utility scale batteries, geothermal and
ocean energy.
Transmission limits between regions
were upgraded as required to support
power sector development in the GMS
as an integrated whole, and the
transmission plan allowed to be
different compared to the
transmission plan of the BAU.
ASES The ASES demand assumptions were
essentially done as a sensitivity to the
SES:
An additional 10% energy efficiency
was applied to the SES demands
(excluding transport).
Flexible demand was assumed to
reach 25% by 2050.
Uptake of electric vehicles doubled by
2050.
ASES supply assumptions were also
implemented as a sensitivity to the SES,
with the following the main differences:
Allow rates of renewable energy
deployment to be more rapid compared
to the BAU and SES.
Technology cost reductions were
accelerated for renewable energy
technologies.
Implement a more rapid programme of
retirements for fossil fuel based power
stations.
Energy policy targets of 70% renewable
generation by 2030, 90% by 2040 and
100% by 2050 across the region are in
place.
Assume that technical / operational
issues with power system operation and
control for a very high level of
renewable energy are addressed22.
22 In particular: (1) sufficient real-time monitoring for both supply and demand side of the industry, (2) appropriate forecasting for solar and wind and centralised real-time control systems in place to manage a more distributed supply side, storages and flexible demand resources, and (3) power systems designed to be able to manage voltage, frequency and stability issues that may arise from having a power system that is dominated by asynchronous technologies.
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4.2 Technology Cost Assumptions
Technology capital cost estimates from a variety of sources were collected and normalised
to be on a consistent and uniform basis23. Mid-points were taken for each technology that is
relevant to the GMS region. The data points collated reflect overnight, turnkey engineering
procurement construction capital costs and are exclusive of fixed operating and maintenance
costs, variable operating and maintenance costs and fuel costs. The capital costs by
technology assumed in the study are presented in Figure 23 for the BAU and SES scenarios.
For the ASES scenario, we assumed that the technology costs of renewable technologies
decline more rapidly. These technology cost assumptions are listed in Figure 24. Note that
the technology capital costs have not included land costs, transmission equipment costs, nor
decommissioning costs and are quoted on a Real USD 2014 basis.
Comments on the various technologies are discussed below in relation to the BAU and SES
technology costs:
Conventional thermal technology costs are assumed to decrease at a rate of 0.05% pa
citing maturation of the technologies with no significant scope for cost improvement.
Onshore wind costs were based on the current installed prices seen in China and India
with future costs decreasing at a rate of 0.6% pa. Future offshore wind costs were
developed by applying the current percentage difference between current onshore and
offshore capital costs for all future years.
Large and small-scale hydro costs are assumed to increase over time reflecting easy
and more cost-efficient hydro opportunities being developed in the first instance.
IRENA reported no cost improvements for hydro over the period from 2010 to 2014.
Adjustments are made in the case of Lao PDR and Myanmar where significant hydro
resources are developed in the BAU case24.
Solar PV costs are based on the more mature crystalline silicon technology which
accounts for up to 90% of solar PV installations (IRENA, 2015), and forecast to continue
to drop (2.3% pa) albeit at a slower pace than in previous years.
Utility scale battery costs are quoted on a $/kWh basis, and cost projections based on
a report by Deutsche Bank (2015) which took into account several forecasts from BNEF,
EIA and Navigant.
Solar thermal (CSP) capital costs are projected to fall at 2.8% pa on the basis of the
IRENA 2015 CSP LCOE projections. While globally there are many CSP installations in
place, the technology has not taken off and the cost of CSP technology over the past 5
years has not been observed to have fallen as rapidly as solar PV.
Biomass capital costs are based on costs observed in the Asia region which are
significantly less than those observed in OECD countries. Capital costs were assumed
to fall at 0.1% pa. Biogas capital costs were based on anaerobic digestion and assumed
to decline at the same rate as biomass.
23 We standardised on Real 2014 USD with all technologies costs normalised to reflect turnkey capital cost s.
24 Capital costs for large scale hydro projects are assumed to increase to $3,000/kW by 2050 consistent with having the most economically feasible hydro resources developed ahead of less economically feasible resources.
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Ocean energy (wave and tidal) technologies were based on learning rates in the ‘Ocean
Energy: Cost of Energy and Cost Reduction Opportunities’ (SI Ocean, 2013) report
assuming global installation capacities increase to 20 GW by 205025.
Capital costs were discounted at 8% pa across all technologies over the project
lifetimes. Decommissioning costs were not factored into the study.
For technologies that run on imported coal and natural gas, we have factored in the
additional capital cost of developing import / fuel management infrastructure in the
modelling.
For reference, Appendix A tabulates the technology cost assumptions that we have used in
the modelling.
Figure 23 Projected Capital Costs by Technology for BAU and SES
* Battery costs are quoted on a Real 2014 USD $/kWh basis.
25 Wave and tidal costs were averaged.
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Figure 24 Projected Capital Costs by Technology for ASES
* Battery costs are quoted on a Real 2014 USD $/kWh basis.
4.3 Fuel Pricing Outlook
IES has developed a global fuel price outlook which are based on short-term contracts traded
on global commodity exchanges before reverting towards long-term price global fuel price
forecasts based on the IEA’s World Energy Outlook (WEO) 2015 450 scenario26 and a set of
relationships between different fuels that have been inferred from historical relations
between different types of fuels. A summary of the fuel prices expressed on an energy-
equivalent basis ($US/MMBtu HHV) is presented in Figure 25.
The 30% fall from 2014 to 2015 for the various fuels was the result of a continued weakening
of global energy demand combined with increased stockpiling of reserves. Brent crude prices
fell from $155/bbl in mid-2014 to $50/bbl in early 2015. OPEC at the November 2014 meeting
did not reduce production causing oil prices to slump. However, fuel prices are then assumed
to return from the current low levels to formerly observed levels within a 10 year timeframe
based on the time required for there to be a correction in present oversupply conditions to
satisfy softened demand for oil and gas27.
To understand the implications of a lower and higher global fuel prices we also perform fuel
price sensitivity analysis. One of the scenarios is based on a 50% fuel cost increase28 to put
26 The IEA’s 450 scenario is an energy pathway consistent with the goal of limiting global increase in temperature to 2°C by limiting the concentration of greenhouse gases in the atmosphere to 450 parts per million CO2; further information available here: https://www.iea.org/media/weowebsite/energymodel/Methodology_450_Scenario.pdf .
27 Reference: Facts Global Energy / Australian Institute of Energy, F. Fesharaki, “A New World Oil Order Emerging in 2016 and Beyond?”, February 2016, suggest a rebound in prices levels over a 5 to 7 year period as the most “probabl e” scenario.
28 Including biomass prices.
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the study’s fuel prices in the range of the IEA’s Current Policies scenario29 which could be
argued to be closer to the fuel pricing outlook that could be anticipated in a BAU outlook,
while the SES and ASES scenarios could be argued to have fuel prices more consistent with
the IEA’s 450 scenario. We discuss the implications of fuel pricing on the BAU and SES within
the context of electricity pricing in section 9.5.
For reference, we provide the base fuel pricing outlook for each year that was used in the
fuel price modelling in Appendix B. These fuel prices were held constant in the BAU, SES
and ASES scenarios.
Figure 25 IES Base Case Fuel Price Projections to 2050
4.4 Lao PDR Real GDP Growth Outlook
Real GDP growth was assumed to stay relatively high at the current GDP growth rates due to
the focus on industrialisation in the region. Over time, GDP growth was assumed to decline
towards 1.96%30 pa by 2050 as seen in Figure 26. The trend down was assumed to reflect
the economic development outlook of the government to 2035, before there is a transition
towards the world average GDP growth rate. GDP assumptions were kept constant between
BAU, SES and ASES scenarios.
29 The IEA’s current policies scenario assumes no changes in policy from the year of WEO publication.
30 1.96% reflects the previous 5-year GDP growth of the top 10 GDP countries in the world excluding Brazil, China and Russia.
0
5
10
15
20
25
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
Pric
e ($
Rea
l 201
4 U
SD/M
MB
tu)
Crude Oil Dated Brent Fuel Oil Diesel Oil Imported Coal Asian LNG Uranium
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Figure 26 Lao PDR GDP Projection
The industrial sector’s increasing importance has been driven by policy and significant foreign
direct investments in the mineral and hydropower sectors. The GDP composition of Lao PDR
is weighted towards industry in line with the gradual shifting away from agriculture. The
industry share of GDP in Lao PDR was assumed to increase from 33% in 2014 to 60% in 2030,
similar to a number of the other GMS countries. The GDP composition is shown in Figure 27.
Note that this assumption was held constant in the BAU and SES.
Figure 27 Lao PDR GDP Composition
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
20
15
20
17
20
19
20
21
20
23
20
25
20
27
20
29
20
31
20
33
20
35
20
37
20
39
20
41
20
43
20
45
20
47
20
49
GD
P G
row
th (
real
)
26.5
%
20.0
%
15.0
%
33.1
%
60.0
%
60.0
%
40.4
% 20.0
%
25.0
%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2014 2035 2050
Agriculture Industry Services
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4.5 Population Growth
Population was assumed to grow in line with the UN Medium Fertility scenario and is held
constant across all scenarios31.
4.6 Committed Generation Projects in BAU, SES and ASES Scenarios
Committed generation projects are the ones that are under construction or at a stage of
development that is sufficiently advanced for decision for the project to come online to not
be reversed. Table 9 lists Lao PDR’s committed generation projects in addition to the existing
790 MW 32 of hydro generation projects. The capacity column reflects the net capacity
available to the Lao PDR grid after exports to Thailand or Vietnam. Projects with links to other
countries have been highlighted in either green or red corresponding to exports to Thailand
or Vietnam, respectively. The export arrangements were assumed to continue throughout
the modelling horizon.
The Thailand export projects, Xayabouly (Xayaburi), Sepian-Xenamnoy and Nam Ngiep 1 are
also included in the BAU but come online just after 2018.
Table 9 Lao PDR Committed New Entry Assumptions
No. Project Exports To Capacity (MW) Technology COD*
1 Nam Ngiep 2 180 Hydro 2015
2 Hong Sa Thailand 405 Coal 2015
3 Nam Ou 2 120 Hydro 2015
4 Nam Ou 5 240 Hydro 2015
5 Nam Ou 6 180 Hydro 2015
6 Nam Kong 2 66 Hydro 2015
7 Xekaman 1 Viet Nam 64 Hydro 2016
8 Nam Sim 8 Hydro 2016
9 Nam Mang 1 64 Hydro 2016
10 Nam Beng 34 Hydro 2016
11 Nam Sane 3A 69 Hydro 2016
12 Nam Sane 3B 45 Hydro 2016
13 Nam Lik 1 61 Hydro 2017
14 Nam Phay 86 Hydro 2018
15 Nam Tha 1 (Nam Pha) 168 Hydro 2018
16 Xekaman 4 Viet Nam 16 Hydro 2018
* Commercial Operation Date
31 UN Department of Economic and Social Affairs, World Population Prospects: The 2012 Re vision.
32 The capacity quoted is net of export arrangements.
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4.7 Regional Transmission System Integration
The modelling presented in this report assumes transmission in the GMS becomes more
tightly integrated than at present. Given the modelling period is for 35 years, we use a
regional model for the interconnections as illustrated in Figure 2633. The figure shows the
assumed topology of the GMS as well as to countries outside the region (PRC and Malaysia).
Initially, not all transmission connections shown in the diagram are in place. However, over
the modelling period the transmission connections are expanded as required to allow power
exchange between regions to minimise costs and take advantage of diversity in demand and
resource availabilities. Each scenario therefore effectively has a different high-level
transmission development plan34.
Figure 28 Regional Transmission System Model of GMS
33 Currently, there is minimal physical interconnection between each GMS country. The model shows the topology that we have used in the modelling in order to gain an understanding of interregiona l power flows and to develop a very simple high-level transmission development plan.
34 We only consider a high-level transmission development plan based on the regional model shown in order to gain insight on interregional power flows.
THAILAND
MYANMAR
CAMBODIA
VIETNAM
LAO PDR
HanoiLuang Prabang
Vientiane
Mandalay
Yangon
Ho Chi Minh City
Phnom Penh
Bangkok Angkor
Siem Reap
Vientiane
Chiang MaiMM
TH
LAO
CAM
VN-S
VN-C
VN-N
PRC
MAL
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The main differences in the assumptions behind the transmission system enhancements in
each scenario were:
In the BAU, it was assumed that transmission developments occur slowly and a tightly
integrated regional power system is in place from about 2030, but the power sectors
are developed so that there is only a limited level of dependency on imports from
neighbouring countries. This is consistent with power sector planning that seeks to not
be overly dependent on power imports from neighbouring countries.
In the SES and ASES, the transmission system evolves from 2025 and we allow the
transmission system (based on a simplified model of the region) to expand as needed
to optimise the use of a geographically disperse set of renewable energy resources. A
consequence of this is that some countries become significant exporters of power
while others take advantage of power imports from neighbouring countries. In
particular Myanmar and Lao PDR become major power exporters with the beneficiaries
being the other GMS countries.
4.8 Imports and Exports
Lao PDR power exports to neighbouring countries are mainly in the form of projects that are
dedicated35 as noted in 4.5. In addition to these projects, Lao PDR also exports smaller
quantities of power into Thailand and Vietnam via Thakhek and Champasak respectively
(power flows totalling approximately 12 GWh in 2014).
Lao PDR have importing arrangements with Thailand, Vietnam and China. Flows from
Vietnam (34 GWh in 2014) and Thailand (1,137 GWh) provide electricity to areas in Lao PDR
not connected to the grid. The significant flows from Thailand support remote mines such as
the Sepon gold and copper mines, which are not connected to the main Lao PDR grid.
The flows from China totalled 239 GWh in 2014 or the equivalent of 27 MW average demand
and connected to the Luang Prabang and Northern provinces to relieve the pressure of
central Lao PDR plants. Power flows from China were assumed constant throughout the
modelling period.
4.9 Technical Economic Power System Modelling
Technical and economic modelling of the GMS was done in the PROPHET electricity planning
and simulation models. It develops a least cost generation based plan and was used to
simulate the operation of the GMS region as an integrated power system.
A brief overview of the various aspects is provided below:
Planning Module: The Planning Module of Prophet allows for intertemporal
constraints such as energy limits to be preserved when simulating the power system
and developments. It also develops a least cost set of new entrants to satisfy demand
over the 35 year modelling horizon.
35 That is the project is connected to the national grid of the neighbouring country.
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Transmission: The power system was modelled based on the configuration as per
Figure 28 with fixed / scheduled flows (red lines) to power systems outside the GMS
not being explicitly modelled while power transfers within the GMS countries were
optimised as needed to allow supply and demand to balance. This is important with
respect to modelling diversity in demand in the different regions and geographical
variation in generation patterns from supply-driven renewable energy (solar and wind)
and seasonal variation of inflows into the hydro storages (see Figure 28).
Economics: Capital and operating costs relating to generation plants as per the
assumptions covered in this report allow the Planning Module to model generation and
transmission development in a least cost manner. On top of this, resource constraints
had to be formulated to reflect actual limits such as the maximum renewable resource
and development rates available to each country.
Demand: Demand profiles were constructed from energy and peak demand forecasts
for electricity based on regression models that were developed for each sector of the
electricity industry (commercial, industrial, residential, agricultural and transport). The
monthly and intraday construction of the profiles were performed in Prophet based on
historical data and/or external data sources indicating the seasonal profile of demand
for each country.
Flexible demand: was modelled as MW and GWh/month quantities that can be
scheduled as necessary to reduce system costs. This means that demand tends to be
shifted from periods when supply and demand would otherwise be tight to other times.
The technology for rescheduling demand was assumed to be in place from 2020 in the
SES and ASES scenarios.
Supply: The approach taken for modelling generation supply technologies varied
according to the technology type. This is discussed further below:
- Conventional thermal plant: is modelled as capacity limited plants, with fuel take
or pay contracts applied to generators where relevant and other fuel supply
constraints in place also where relevant – for example, gas supply limits applied to
LNG facilities or offshore gas fields. Examples of such plants include coal, biomass,
gas, and diesel generators.
- Energy limited plants: such as large-scale hydros with reservoirs / storages and CSP
have monthly energy limits corresponding to seasonal variations in energy inflows.
The equivalent capacity factors are based on external reports for hydro and
resource data for CSP (see next point).
- Supply-driven generation forms: Seasonal profiles for wind, solar and run of river
hydros without reservoirs were developed on an hourly basis. For wind and solar
they were derived from monthly resource data collected from a variety of sources
including NASA, NREL36 and accessed via the Solar and Wind Energy Resource Atlas
(SWERA) Toolkit and IRENA Global Atlas. Resource amounts were matched against
actual generation data for known plants to develop equivalent monthly capacity
36 DNI and Wind NASA Low Resolution and NREL DI Moderate Resolution data.
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factors at various high resource pockets in each country. Several traces were built
from known generation traces to provide diversification benefits.
- Pump Storage and battery storage: these are modelled in a similar way to flexible
demand in that demand can be shifted with a capacity and energy limit but the
scheduled demand is stored for generation later with an appropriate energy
conversion efficiency (pumped storages assumed to be 70% and battery storage
systems at 85%).
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5 Business as Usual Scenario
5.1 Business as Usual Scenario
The BAU scenario assumes industry developments consistent with the current state of
planning in Lao PDR and reflective of growth rates in electricity demand consistent with an
IES view of base development, existing renewable energy targets, where relevant,
aspirational targets for electrification rates, and energy efficiency gains that are largely
consistent with the policies seen in the region.
5.2 Demand Growth
Lao PDR’s on-grid electricity demand (including transmission and distribution losses37) is
plotted in Figure 29. Lao PDR’s electricity demand is forecast to increase at a rate of 7.0% pa
over the 35-year period to 2050 with higher growth rates in the earlier years relating to
mining projects followed by a slowdown post-2040 as the economy trends towards long-term
global GDP growth rates.
The industrial sector is forecast to grow the fastest at 8.5% followed by the residential sector
at 5.6%, commercial sector at 5.1% and agriculture at 0.8% per annum as the GDP
composition shifts towards commerce/services and industry with increases in residential
electricity consumption. The transport sector is forecast to hit 800 GWh by 2050 as the
number of cars and uptake of electric cars and motorbikes increase to 15% uptake. Lao PDR
electricity demand is forecast to reach 55 TWh by 2050. Peak demand is plotted below in
Figure 30 and shows peak demand growing at 6.6% pa reaching 8 GW by 2050. The load
factor is assumed to trend towards 75% by 2040 mainly driven by additional industrial loads
impacting the demand base.
The key drivers for demand growth and the demand projections are summarised in Table 10.
37 Note that unless otherwise stated, all other demand charts and statistics include transmission and distribution losses.
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Figure 29 Lao PDR Projected Electricity Demand (2015-50, BAU)
Figure 30 Lao PDR Projected peak Demand (BAU)
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Table 10 Lao PDR Demand and Demand Drivers (BAU)
No. Aspect 2015-30 2030-40 2040-50
1 Demand Growth (pa) 9.7% 5.5% 3.1%
2 GDP Growth (Real, pa) 7.0% 6.5% 3.5%
3 Electrification Rate (Population) 62.6% 97.0% 98.8%
4 Population Growth 1.54% 1.07% 0.78%
5 Per Capita Consumption (kWh) 1,322 3,009 3,995
6 Electricity Elasticity* 7.70 2.28 1.33
7 Electricity Intensity (kWh/USD) 0.337 0.454 0.464
* Electricity elasticity is calculated as electricity demand growth divided by the population growth over the same period
5.3 Installed Capacity Development
The BAU installed capacity (MW) for Lao PDR is plotted in Figure 31 and Figure 32 by
capacity shares for selected years: 2010, 2015, 2020, 2030, 2040 and 2050. The former
shows installed generation capacity by the main generation type categories. We provide
corresponding statistics in Table 11 and
Table 12. Note that the installed capacity numbers exclude currently dedicated generation
that is effectively available to its neighbouring countries as imports and where appropriate
this has been de-rated to reflect supply agreements.
Installed capacity in 2014 increases from 791 MW to 14,000 MW with large-scale hydro
generation accounting for 71% of total installed capacity in 2050. Coal-fired capacity
increases to 405 MW in 2015 with the commissioning of the Hong Sa coal plant and increases
to 1,905 MW by 2050. From 2020, additional renewable capacity is developed to achieve a
10% generation share (excluding large hydro) by 2050 comprised of solar PV, onshore wind,
biomass and run-of-river hydro accounting for 14% capacity share in 2050.
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Figure 31 Lao PDR Installed Capacity (BAU, MW)
Figure 32 Lao PDR Installed Capacity Mix Percentages (BAU, %)
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Table 11 Lao PDR Capacity by Type (BAU, MW)
Resource 2010 2015 2020 2030 2040 2050
Coal 0 405 405 1,005 1,605 1,905
CCS 0 0 0 0 0 0
Diesel 0 0 0 200 200 200
Fuel Oil 0 0 0 0 0 0
Gas 0 0 0 0 0 0
Nuclear 0 0 0 0 0 0
Hydro 330 1,577 2,257 5,509 7,509 10,009
Onshore Wind 0 0 77 377 527 677
Offshore Wind 0 0 0 0 0 0
Biomass 0 0 53 203 323 323
Biogas 0 0 0 0 0 0
Solar 0 0 120 220 320 520
CSP 0 0 0 0 0 0
Battery 0 0 0 0 0 0
Hydro ROR 0 0 100 100 200 400
Geothermal 0 0 0 0 0 0
Pump Storage 0 0 0 0 0 0
Ocean 0 0 0 0 0 0
Off grid 0 0 0 0 0 0
Table 12 Lao PDR Capacity Share by Type (BAU, %)
Resource 2010 2015 2020 2030 2040 2050
Coal 0% 20% 13% 13% 15% 14%
CCS 0% 0% 0% 0% 0% 0%
Diesel 0% 0% 0% 3% 2% 1%
Fuel Oil 0% 0% 0% 0% 0% 0%
Gas 0% 0% 0% 0% 0% 0%
Nuclear 0% 0% 0% 0% 0% 0%
Hydro 100% 80% 75% 72% 70% 71%
Onshore Wind 0% 0% 3% 5% 5% 5%
Offshore Wind 0% 0% 0% 0% 0% 0%
Biomass 0% 0% 2% 3% 3% 2%
Biogas 0% 0% 0% 0% 0% 0%
Solar 0% 0% 4% 3% 3% 4%
CSP 0% 0% 0% 0% 0% 0%
Battery 0% 0% 0% 0% 0% 0%
Hydro ROR 0% 0% 3% 1% 2% 3%
Geothermal 0% 0% 0% 0% 0% 0%
Pump Storage 0% 0% 0% 0% 0% 0%
Ocean 0% 0% 0% 0% 0% 0%
Off grid 0% 0% 0% 0% 0% 0%
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5.4 Projected Generation Mix
Figure 33 plots the generation mix (on an as generated basis38) over time in the BAU case and
Figure 34 plots the corresponding percentage shares. Coal-fired generation initially increases
to 887 GWh with the commissioning of the Hong Sa coal-fired power station in 2015/16 with
the remaining output exported to Thailand39, and grows to 15 TWh by 2050. Large-scale
hydro initially supplied the majority of Lao PDR’s on-grid demand requirements but with the
additional coal and renewable developments, declines to 64% by 2050. Renewable
technologies account for 10% of generation by 2050.
38 Unless otherwise stated, all generation charts and statistics in this report are presented on an “as generated” basis, meaning that generation to cover generator’s auxiliary consumption accounted for.
39 Dedicated capacity to importing countries such as that relating to Hong Sa is no t reflected here.
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Figure 33 Lao PDR Generation Mix (BAU, GWh)
Figure 34 Lao PDR Generation Mix Percentages (BAU, %)
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Table 13 Lao PDR Generation by Type (BAU, GWh)
Resource 2010 2015 2020 2030 2040 2050
Coal 0 887 1,927 8,161 13,036 15,402
CCS 0 0 0 0 0 0
Diesel 0 0 0 58 81 183
Fuel Oil 0 0 0 0 0 0
Gas 0 0 0 0 0 0
Nuclear 0 0 0 0 0 0
Hydro 2,093 4,211 8,698 21,229 28,936 38,569
Onshore Wind 0 0 198 958 1,337 1,716
Offshore Wind 0 0 0 0 0 0
Biomass 0 0 0 1,332 2,126 2,120
Biogas 0 0 0 0 0 0
Solar 0 0 215 392 573 928
CSP 0 0 0 0 0 0
Battery 0 0 0 0 0 0
Hydro ROR 0 0 388 385 775 1,541
Geothermal 0 0 0 0 0 0
Pump Storage 0 0 0 0 0 0
Ocean 0 0 0 0 0 0
Off grid 0 0 0 0 0 0
Table 14 Lao PDR Generation share by Type (BAU, %)
Resource 2010 2015 2020 2030 2040 2050
Coal 0% 17% 17% 25% 28% 25%
CCS 0% 0% 0% 0% 0% 0%
Diesel 0% 0% 0% 0% 0% 0%
Fuel Oil 0% 0% 0% 0% 0% 0%
Gas 0% 0% 0% 0% 0% 0%
Nuclear 0% 0% 0% 0% 0% 0%
Hydro 100% 83% 76% 65% 62% 64%
Onshore Wind 0% 0% 2% 3% 3% 3%
Offshore Wind 0% 0% 0% 0% 0% 0%
Biomass 0% 0% 0% 4% 5% 4%
Biogas 0% 0% 0% 0% 0% 0%
Solar 0% 0% 2% 1% 1% 2%
CSP 0% 0% 0% 0% 0% 0%
Battery 0% 0% 0% 0% 0% 0%
Hydro ROR 0% 0% 3% 1% 2% 3%
Geothermal 0% 0% 0% 0% 0% 0%
Pump Storage 0% 0% 0% 0% 0% 0%
Ocean 0% 0% 0% 0% 0% 0%
Off grid 0% 0% 0% 0% 0% 0%
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5.5 Grid to Grid Power Flows
Figure 35 plots the imports and exports in the BAU with the dotted line representing the net
interchange. Flows reported are in addition to the dedicated plant output such as that from
Hong Sa power plant. Overall flows in the BAU are relatively low up to 2029 when Lao PDR
starts to export to Thailand up to 6,500 GWh a year driven by significant differences in the
levelised cost of electricity – Thailand relies on gas compared to Lao PDR which has significant
hydro resources. Flows into Viet Nam are minimal.
Figure 35 Lao PDR Imports and Exports (BAU)
5.6 Generation Fleet Structure
Figure 36 shows the installed generation capacity by the main categories of generation:
thermal, renewable and large-scale hydro, in order to provide greater insight into the basic
structure of installed capacity under the BAU. This highlights that Lao PDR’s BAU projection
is heavily dominated by hydro generation followed by coal-fired generation. Figure 37 shows
the on-grid composition of generation by major categories of generation: thermal, large
hydro and renewable. As could be anticipated, generation closely reflects the BAU’s installed
capacity mix.
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Figure 36 Lao PDR Installed Capacity by Generation Type (BAU, MW)
Figure 37 Lao PDR Generation Mix by Generation Type (BAU, GWh)
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To facilitate later comparison with the SES, Figure 38 plots installed capacity with capacity
being distinguished between the following basic categories: (1) dispatchable capacity, (2)
non-dispatchable capacity; and (3) semi-dispatchable capacity40. This provides some insight
into the operational flexibility of the generation fleet to match demand uncertainty. The
dispatchable category relates to generation that can be controlled and dispatched at short
notice to ramp up or down, non-dispatchable means that the generation is not able to
respond readily to dispatch instructions while the semi-dispatchable category means that the
resource can respond within limits, and in particular is capable of being backed off should
the need arise to for example, avoid overloading the network or “spill” energy in the event
that an over generation situation emerges; solar photovoltaics and windfarms with
appropriately installed control systems can be classified in this category. In the BAU, the
dispatchable percentage starts at 100% with only coal and hydro then as renewables are
added to the system, it still remains above 85% by 2050.
Figure 38 Lao PDR Installed Capacity by Dispatch Status (BAU)
5.7 Reserve Margin and Generation Trends
Figure 39 plots the reserve margin based on nameplate capacity and annual peak demand.
The Lao PDR reserve margin in the BAU hovers around 60% and is higher than the other GMS
countries in the BAU case. This is driven by Lao PDR’s investment in hydro developments,
40 Wind and solar is classified as semi-dispatchable, geothermal and hydro run-of-river is classified as non-dispatchable and all other technologies are classified as dispatchable.
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which are energy limited based on the size of the hydro’s reservoir and seasonal reservoir
inflows41..
Figure 39 Lao PDR Reserve Margin (BAU)
To obtain a better understanding of the broad mix of generation capacity and generation
mix, Figure 40 and Figure 41 show shares in installed capacity and in generation grouped by
the main categories of generator: thermal, large hydro, renewable energy (RE) and large
hydro plus renewable energy.
Figure 40 Lao PDR Capacity Shares by Generation Type (BAU)
41 The amount of energy that a hydro power station can generate depends on the size of its reservoir and the volume of water storage in the reservoir, which in turn increases with inflows to the reservoir and decreases when the hydro power station generates electricity (or water is released or spilled). The term “energy limited” means that at any point in time, based on the volume of water in the reservoir, the hyd ro generator would be able to generate a certain amount of electrical energy.
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Figure 41 plots the generation shares by several different categories of generation. The
thermal generation share increases to almost 30% and renewable energy including large-
scale hydro gradually declines to 70% and maintains that level as more renewable plants
enter the system. The BAU has large-scale hydro being largely exploited to support the
growing power demands in Lao PDR and to a smaller extent the neighbouring countries.
Figure 41 Lao PDR Generation Shares by Generation Type (BAU)
5.8 Electrification and Off Grid
Lao PDR’s grid-based electrification rate for its urban and rural population is assumed to
reach close to 100% by 2030 in the BAU. Due to the limited impact of off-grid in this scenario
it has been decided to only model the central grid-connected power system.
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6 Sustainable Energy Sector Scenario
6.1 Sustainable Energy Sector Scenario
The SES seeks to transition electricity demand towards the best practice benchmarks of
other developed countries in terms of energy efficiency, maximise the renewable energy
development, cease the development of fossil fuel resources, and make sustainable and
prudent use of undeveloped conventional hydro resources. The SES takes advantage of
existing, technically proven and commercially viable renewable energy technologies.
6.2 Demand Growth
Figure 42 plots Lao PDR’s forecast energy consumption from 2015 to 2050 with the BAU
energy trajectory charted as a comparison. The significant savings are due to additional
energy efficiency assumptions relating to the various sectors achieving energy intensity
benchmarks of comparable developed countries in Asia42. The SES demand grows at a
slower rate of 6.4% pa over the period to 2050 with the commercial sector growing at 3.8%
pa, industry growing at 8.2% pa and the residential sector growing at 4.1% pa. The
agricultural sector grows at 0.7% and the uptake of electric transport options occur from
2025 onwards and grows to 800 GWh accounting for 2% of total demand by 2050, or 10%
of all vehicles.
Figure 43 plots peak demand of Lao PDR. The firm blue line represents peak demand before
any flexible demand side resources have been scheduled43. Flexible demand response is
“dispatched” in the model in line with the least cost dispatch of all resources in the power
system. The dashed line represents what peak demand became as a consequence of
scheduling (“time-shifting”) commercial, industrial and residential loads to minimise
system costs. From 2020, the amount of flexible demand was assumed to grow to 10% of
total demand across all sectors by 2050, or 15% if storage methods are included. The load
factor associated with the SES was also assumed to reach 80% (compared to 75% under the
BAU case) by 2030 as a further consequence of enhanced demand side management
measures relative to the BAU.
Key drivers for demand growth and the demand projections are summarised in Table 12.
42 Lao PDR’s industrial energy intensity was trended towards levels commensurate with Hong Kong (2014) by 2050. Hong Kong had the lowest intensity based on the intensity metric of a basket of comparable countries.
43 Flexible demand response is “dispatched” in the model in line with the least cost dispatch of all resources. The solid line represents peak demand as put in the model, while the dashed line represents what peak demand ended up being as a consequence of shifting demand from one period of time to another. This includes scheduling of loads associated with battery storage devices and rescheduling (time-shifting) commercial, industrial and residential loads.
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Figure 42 Lao PDR Projected Electricity Demand (2015-50, SES)
Figure 43 Lao PDR Projected Electricity Demand (SES, MW)
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Table 15 Lao PDR Demand and Demand Drivers (SES)
No. Aspect 2015-30 2030-40 2040-50
1 Demand Growth (pa) 7.3% 5.8% 2.3%
2 GDP Growth (Real, pa) 7.0% 6.5% 3.5%
3 Electrification Rate (Population) 49.3% 78.4% 84.5%
4 Population Growth 1.54% 1.07% 0.78%
5 Per Capita Consumption (kWh) 1,204 2,637 3,382
6 Electricity Elasticity* 7.01 2.19 1.28
7 Electricity Intensity (kWh/USD) 0.307 0.398 0.392
* Electricity elasticity is calculated as electricity demand growth divided by the population growth over the same period
6.3 Installed Capacity Development
Figure 44 plots the installed capacity developments under the SES and Figure 45 plots the
corresponding percentage shares. Table 16 and Table 17 provide the statistical details of
the installed capacity and capacity shares by type including the estimated 2010 levels.
Committed and existing plants are assumed to come online as per the BAU but aren’t
replaced when retired. Planned and proposed thermal and large-scale hydro developments
are assumed to not occur, with the exception of 2,500 MW of large scale hydro to support
renewable developments, and all other generation requirements are instead met by
renewable technologies. Coal and gas fired-generation in the earlier years is very similar to
the BAU due to committed projects. Over time, hydro and coal capacity shares drop from
100% in 2015 as more and more renewable generation, predominantly solar PV, comes
online.
Timing of renewable energy developments are based on the maturity of the technology and
judgments of when it could be readily deployed in Lao PDR. Additional demand in the SES is
mainly met by renewables with 23 GW required to meet 2050 electricity demand from a
current capacity base around 2,000 MW (large-scale and grid connected). Solar PV is to
account for 10 GW, biomass 2 GW, CSP 1 GW, and wind energy 6 GW of the total by 2050.
Battery storage with an equivalent capability of 2 GW is developed to support the significant
amount of solar PV and off-peak load. Small amounts of run-of-river hydro and geothermal
are also developed in the later stages.
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Figure 44 Lao PDR Installed Capacity by Type (SES, MW)
Figure 45 Lao PDR Capacity Shares (SES, %)
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40
20
42
20
44
20
46
20
48
20
50
Cap
acit
y M
W
Coal Hydro Wind Bio Solar CSP Battery Hydro ROR
20%
9%4%
100%
80%
59%
39%
22%15%
15%
26%
22%
21%
4%
7%
9%
13%
18%
32%35%
3%5%
5%
6%5%
5%
5% 8%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2010 2015 2020 2030 2040 2050
Cap
acit
y M
ix
Coal Hydro Wind Bio Solar CSP Hydro ROR Battery
FINAL
Intelligent Energy Systems IESREF: 5973 63
Table 16 Lao PDR Capacity by Type (SES, MW)
Resource 2010 2015 2020 2030 2040 2050
Coal 0 405 405 405 405 405
CCS 0 0 0 0 0 0
Diesel 0 0 0 0 0 0
Fuel Oil 0 0 0 0 0 0
Gas 0 0 0 0 0 0
Nuclear 0 0 0 0 0 0
Hydro 330 1,577 2,692 4,192 4,192 4,192
Onshore Wind 0 0 701 2,801 4,301 5,801
Offshore Wind 0 0 0 0 0 0
Biomass 0 0 105 409 758 1,223
Biogas 0 0 0 36 647 1,101
Solar 0 0 580 1,980 6,080 9,580
CSP 0 0 0 300 900 1,350
Battery 0 0 0 0 890 2,247
Hydro ROR 0 0 100 700 1,000 1,300
Geothermal 0 0 0 0 50 50
Pump Storage 0 0 0 0 0 0
Ocean 0 0 0 0 0 0
Off grid 0 0 0 0 0 0
Table 17 Lao PDR Capacity Share by Type (SES, %)
Resource 2010 2015 2020 2030 2040 2050
Coal 0% 20% 9% 4% 2% 1%
CCS 0% 0% 0% 0% 0% 0%
Diesel 0% 0% 0% 0% 0% 0%
Fuel Oil 0% 0% 0% 0% 0% 0%
Gas 0% 0% 0% 0% 0% 0%
Nuclear 0% 0% 0% 0% 0% 0%
Hydro 100% 80% 59% 39% 22% 15%
Onshore Wind 0% 0% 15% 26% 22% 21%
Offshore Wind 0% 0% 0% 0% 0% 0%
Biomass 0% 0% 2% 4% 4% 4%
Biogas 0% 0% 0% 0% 3% 4%
Solar 0% 0% 13% 18% 32% 35%
CSP 0% 0% 0% 3% 5% 5%
Battery 0% 0% 0% 0% 5% 8%
Hydro ROR 0% 0% 2% 6% 5% 5%
Geothermal 0% 0% 0% 0% 0% 0%
Pump Storage 0% 0% 0% 0% 0% 0%
Ocean 0% 0% 0% 0% 0% 0%
Off grid 0% 0% 0% 0% 0% 0%
FINAL
Intelligent Energy Systems IESREF: 5973 64
6.4 Projected Generation Mix
Grid generation is plotted in Figure 46 and Figure 4744. The corresponding statistics for
snapshot years are provided in Table 19 and Table 20.
Lao PDR’s generation mix in the earlier years to 2020 is similar to the BAU case as committed
new entry are commissioned. Thermal and large hydro projects outside what is deemed
existing or committed (with the exception of some hydro) is not developed and renewable
technology is used to meet the remaining incremental demand.
Coal and large scale hydro decline to a combined 23% generation share by 2050 whereas
solar PV accounts for the highest generation share of 17 TWh or 22%, followed by onshore
wind at 19% then biomass and biogas at a combined 21% then CSP at 8%. All up Lao PDR
generates more than 75 TWh against a demand base of 43 TWh by 2050 with the excess
power exported into neighbouring countries.
44 Battery storage is not included as storage technologies are generation neutral.
FINAL
Intelligent Energy Systems IESREF: 5973 65
Figure 46 Lao PDR Generation Mix (SES, GWh)
Figure 47 Lao PDR Generation Share (SES, %)
0
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90,0002
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20
50
Gen
erat
ion
(G
Wh
)
Coal Hydro Wind Bio Solar CSP Hydro ROR
17%8% 9%
5%
100%
83%
68%
43%
29%
21%
13%
19%
18%
19%
8%
16%
21%
7%
10%
18%22%
3% 7% 8%
4% 7% 6% 6%
0%
10%
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30%
40%
50%
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70%
80%
90%
100%
2010 2015 2020 2030 2040 2050
Ge
ne
rati
on
Mix
Coal Hydro Wind Bio Solar CSP Hydro ROR
FINAL
Intelligent Energy Systems IESREF: 5973 66
Table 18 Lao PDR Generation by Fuel (SES, GWh)
Resource 2010 2015 2020 2030 2040 2050
Coal 0 887 1,128 3,342 2,798 1,745
CCS 0 0 0 0 0 0
Diesel 0 0 0 0 0 0
Fuel Oil 0 0 0 0 0 0
Gas 0 0 0 0 0 0
Nuclear 0 0 0 0 0 0
Hydro 2,093 4,211 9,614 16,020 17,382 15,902
Onshore Wind 0 0 1,807 7,117 10,908 14,707
Offshore Wind 0 0 0 0 0 0
Biomass 0 0 0 2,869 5,328 8,575
Biogas 0 0 0 249 4,545 7,718
Solar 0 0 1,038 3,532 10,887 17,091
CSP 0 0 0 1,010 3,939 6,100
Battery 0 0 0 0 0 0
Hydro ROR 0 0 504 2,698 3,877 5,009
Geothermal 0 0 0 0 334 333
Pump Storage 0 0 0 0 0 0
Ocean 0 0 0 0 0 0
Off grid 0 0 0 0 0 0
Table 19 Lao PDR Generation Share by Fuel (SES, %)
Resource 2010 2015 2020 2030 2040 2050
Coal 0% 17% 8% 9% 5% 2%
CCS 0% 0% 0% 0% 0% 0%
Diesel 0% 0% 0% 0% 0% 0%
Fuel Oil 0% 0% 0% 0% 0% 0%
Gas 0% 0% 0% 0% 0% 0%
Nuclear 0% 0% 0% 0% 0% 0%
Hydro 100% 83% 68% 43% 29% 21%
Onshore Wind 0% 0% 13% 19% 18% 19%
Offshore Wind 0% 0% 0% 0% 0% 0%
Biomass 0% 0% 0% 8% 9% 11%
Biogas 0% 0% 0% 1% 8% 10%
Solar 0% 0% 7% 10% 18% 22%
CSP 0% 0% 0% 3% 7% 8%
Battery 0% 0% 0% 0% 0% 0%
Hydro ROR 0% 0% 4% 7% 6% 6%
Geothermal 0% 0% 0% 0% 1% 0%
Pump Storage 0% 0% 0% 0% 0% 0%
Ocean 0% 0% 0% 0% 0% 0%
Off grid 0% 0% 0% 0% 0% 0%
FINAL
Intelligent Energy Systems IESREF: 5973 67
6.5 Grid to Grid Power Flows
Figure 48 plots the imports and exports in the SES with the dotted line representing the net
interchange. Lao PDR imports and exports more in the SES than the BAU due to optimising
generation across the region rather than on a country by country basis. Lao PDR exports to
all of its neighbouring countries with the majority of flows into northern Viet Nam and
Thailand. The power imports also come from Thailand due to diversification of renewable
resource profiles coinciding with peak demands and demand troughs throughout the year,
but mainly driven by the need to export power into Viet Nam. Lao PDR is a net exporter of
power of up to 23 TWh by 2050.
Figure 48 Lao PDR Imports and Exports (SES)
6.6 Generation Fleet Structure
As for the BAU, to gain insight into the nature of the mix of generation technologies deployed
in the SES, we present a number of additional charts. Figure 49 and Figure 50 show Lao PDR’s
installed capacity and generation by type for the SES – this is heavily biased towards
renewable generation forms. For Lao PDR, the only fossil-fuel based generation relates to
the Hong Sa coal project.
-80,000
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20
49
Flo
ws
(GW
h)
Imports Exports Net
FINAL
Intelligent Energy Systems IESREF: 5973 68
Figure 49 Lao PDR Installed Capacity by Generation Type (SES, MW)
Figure 50 Lao PDR Generation Mix by Generation Type (SES, MW)
0
5,000
10,000
15,000
20,000
25,000
30,000
Cap
acit
y, M
W
Fossil Fuel Large Hydro Renewable
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
Gen
erat
ion
, GW
h
Fossil Fuel Large Hydro Renewable
FINAL
Intelligent Energy Systems IESREF: 5973 69
Figure 51, shows the dispatchable, semi-dispatchable and non-dispatchable components of
installed capacity and it can be seen that semi-dispatchable increases to around 61% of the
total system capacity compared to around 9% in the BAU by 2050. Based on operational
simulations with this resource mix, it appears to be operationally feasible, and generation
forms that provide storage and flexibility in the demand side play important roles. It is clear
that short-term renewable energy solar and wind forecasting systems will be important, as
will real-time updates on demand that can be controlled. Furthermore, control systems that
can allow the dispatch of flexible resources on both supply and demand sides of the industry
and across the region will be required.
Figure 51 Lao PDR Installed Capacity by Dispatch Status (SES, MW)
6.7 Reserve Margin and Generation Trends
Figure 52 plots the reserve margin under the SES. Figure 53 and Figure 54, respectively, show
the installed capacity mix and generation mix for different categories of generation in the
power system. Generation projects are built in Lao PDR well above the power requirements
in the country to support power flows into the neighbouring countries - explaining the
reserve margin trajectory. Renewable generation including large-scale hydro reaches 98% or
77% without large-scale hydro with the only fossil fuel project being the Hong Sa coal project
which exports the majority of its power into Thailand. It is worth noting conventional reserve
margin measures are generally not suited to measuring high renewable energy systems in
the same context used for thermal-based systems. Renewable technologies generally have
much lower capacity factors and require more capacity to meet the same amount of energy
produced from thermal-based technologies.
0
5,000
10,000
15,000
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25,000
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49
Cap
acit
y, M
W
Dispatchable Non-Dispatchable Semi-Dispatchable
FINAL
Intelligent Energy Systems IESREF: 5973 70
Figure 52 Lao PDR Reserve Margin (SES)
Figure 53 Lao PDR Installed Capacity Shares for SES by Generation Type
0%
50%
100%
150%
200%
250%
300%
350%
20
15
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20
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20
47
20
49
Reserve Margin Renewable Capacity
Hydro Capacity Fossil Fuel Capacity
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
20
15
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20
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20
49
Caa
city
Sh
are
Fossil Fuel Large Hydro Renewable Renewable + Large Hydro
FINAL
Intelligent Energy Systems IESREF: 5973 71
Figure 54 Lao PDR Generation Shares for SES by Generation Type
6.8 Electrification and Off-Grid
Lao PDR’s grid electrification rate for its urban and rural population is assumed to reach close
to 100% by 2030 as per the BAU.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
20
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Gen
erat
ion
Sh
are
Fossil Fuel Large Hydro Renewable Renewable + Large Hydro
FINAL
Intelligent Energy Systems IESREF: 5973 72
7 Advanced Sustainable Energy Sector Scenario
7.1 Advanced Sustainable Energy Sector Scenario
The ASES assumes that the power sector is able to more rapidly transition towards a 100%
renewable energy technology mix under an assumption that renewable energy is deployed
more than in the SES scenario with renewable energy technology costs declining more
rapidly compared to BAU and SES scenarios.
7.2 Demand Growth
Figure 55 plots Lao PDR’s forecast energy consumption from 2015 to 2050 with the BAU
and SES energy trajectory charted with a dashed line for comparison. The SES energy
savings against the BAU are due to allowing Lao PDR’s energy demand to transition towards
energy intensity benchmarks of comparable developed countries in Asia. The ASES applies
an additional 10% energy efficiency against the SES demands which is partially offset with
additional transport demands associated with higher uptake rates.
The ASES demand grows at a slower rate of 6.1% pa over the period from 2015 to 2050
with the commercial sector at 3.5% pa, industry growing at 7.8% pa and the residential
sector growing at 4.1% pa. Demand from the transport sector in the ASES is doubled and
grows to 1,618 GWh or 4% of total demand by 2050 accounting for 20% of all vehicles.
Figure 56 plots the peak demand of Lao PDR. The firm blue line represents peak demand in
Cambodia without any demand side management impacts. Demand side management
reflects demand responses to tight supply and network conditions. This is assumed to grow
to as much as 17.5% of demand across all sectors by 2050, representing the portion of
flexible demand that is not met through technology means (i.e. battery storage). The load
factor associated with the ASES is also assumed to reach 80% (compared to 75% under the
BAU case) by 2030 as a further consequence of enhanced demand side management
measures relative to the BAU.
Key drivers for demand growth and the demand projections are summarised in Table 17.
FINAL
Intelligent Energy Systems IESREF: 5973 73
Figure 55 Lao PDR Projected Electricity Demand (2015-50, ASES)
Figure 56 Lao PDR Projected Electricity Demand (ASES, MW)
0
10
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30
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60
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20
50
Ener
gy (
inc
loss
es,
TWh
)
Agriculture Industry Commercial Residential
Transport BAU SES
0
1,000
2,000
3,000
4,000
5,000
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20
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50
Pea
k D
eman
d (
MW
)
FINAL
Intelligent Energy Systems IESREF: 5973 74
Table 20 Lao PDR Demand and Demand Drivers (ASES)
No. Aspect 2015-30 2030-40 2040-50
1 Demand Growth (pa) 6.4% 6.0% 2.9%
2 GDP Growth (Real, pa) 7.0% 6.5% 3.5%
3 Electrification Rate (Population) 41.4% 58.7% 60.0%
4 Population Growth 1.54% 1.07% 0.78%
5 Per Capita Consumption (kWh) 1,115 2,358 3,052
6 Electricity Elasticity* 6.49 2.12 1.29
7 Electricity Intensity (kWh/USD) 0.284 0.356 0.354
* Electricity elasticity is calculated as electricity demand growth divided by the population growth over the same period
7.3 Installed Capacity Development
Figure 57 plots the installed capacity developments under the SES and Figure 58 plots the
corresponding percentage shares. Table 21 and Table 22 provide the statistical details of the
installed capacity and capacity shares by type including the 2010 levels.
The ASES retires the coal plant earlier than in the SES under a 100% renewable generation
target across the region. Total installed capacity increases to almost 30 GW or 10% higher
than in the SES, with solar PV accounting for 33% of total installed capacity, or almost 10 GW,
supported by 3,710 MW equivalent of battery storage for generation deferral. Onshore wind
accounts for 7,300 MW or 25% and large scale hydro remains at 4,100 MW as per the SES. A
significant portion of this capacity is dedicated to exports noting Lao PDR ASES only demand
reaching 5,625 MW by 2050.
FINAL
Intelligent Energy Systems IESREF: 5973 75
Figure 57 Lao PDR Installed Capacity by Type (ASES, MW)
Figure 58 Lao PDR Capacity Shares (ASES, %)
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
20
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50
Cap
acit
y M
W
Coal Hydro Wind Bio Solar CSP Battery Hydro ROR
20%
9%4%
100%
80%
59%
38%
19%14%
15%
26%
25%
25%
4%
6%
7%
13%
18%
28%33%
3%
4% 5%
6%
5% 4%
11% 13%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2010 2015 2020 2030 2040 2050
Cap
acit
y M
ix
Coal Hydro Wind Bio Solar CSP Hydro ROR Battery
FINAL
Intelligent Energy Systems IESREF: 5973 76
Table 21 Lao PDR Capacity by Type (ASES, MW)
Resource 2010 2015 2020 2030 2040 2050
Coal 0 405 405 405 405 0
CCS 0 0 0 0 0 0
Diesel 0 0 0 0 0 0
Fuel Oil 0 0 0 0 0 0
Gas 0 0 0 0 0 0
Nuclear 0 0 0 0 0 0
Hydro 330 1,577 2,692 4,192 4,192 4,192
Onshore Wind 0 0 701 2,801 5,301 7,301
Offshore Wind 0 0 0 0 0 0
Biomass 0 0 105 422 752 1,069
Biogas 0 0 0 22 533 855
Solar 0 0 580 1,980 6,080 9,580
CSP 0 0 0 300 900 1,350
Battery 0 0 0 116 2,330 3,710
Hydro ROR 0 0 100 700 1,000 1,300
Geothermal 0 0 0 0 50 50
Pump Storage 0 0 0 0 0 0
Ocean 0 0 0 0 0 0
Off grid 0 0 0 0 0 0
Table 22 Lao PDR Capacity Share by Fuel (ASES, %)
Resource 2010 2015 2020 2030 2040 2050
Coal 0% 20% 9% 4% 2% 0%
CCS 0% 0% 0% 0% 0% 0%
Diesel 0% 0% 0% 0% 0% 0%
Fuel Oil 0% 0% 0% 0% 0% 0%
Gas 0% 0% 0% 0% 0% 0%
Nuclear 0% 0% 0% 0% 0% 0%
Hydro 100% 80% 59% 38% 19% 14%
Onshore Wind 0% 0% 15% 26% 25% 25%
Offshore Wind 0% 0% 0% 0% 0% 0%
Biomass 0% 0% 2% 4% 3% 4%
Biogas 0% 0% 0% 0% 2% 3%
Solar 0% 0% 13% 18% 28% 33%
CSP 0% 0% 0% 3% 4% 5%
Battery 0% 0% 0% 1% 11% 13%
Hydro ROR 0% 0% 2% 6% 5% 4%
Geothermal 0% 0% 0% 0% 0% 0%
Pump Storage 0% 0% 0% 0% 0% 0%
Ocean 0% 0% 0% 0% 0% 0%
Off grid 0% 0% 0% 0% 0% 0%
FINAL
Intelligent Energy Systems IESREF: 5973 77
7.4 Projected Generation Mix
ASES grid generation is plotted in Figure 59 and generation shares in Figure 60. The
corresponding statistics for snapshot years are provided in Table 24 and Table 25. Lao PDR’s
generation mix in the earlier years to 2020 is similar to the BAU case as committed new
generation projects are commissioned and this has largely been kept the same.
Of the renewable technologies, by 2050, onshore wind generation contributes the highest
generation share of 19 TWh or 26% closely followed by solar PV at 24%. Biomass fills the
baseload role in the power system as gas and coal plants from other countries retire earlier
than in the SES. By 2030, more than 90% of all generation is from renewable sources (includes
large-scale hydro) and moves towards 100% by 2050.
FINAL
Intelligent Energy Systems IESREF: 5973 78
Figure 59 Lao PDR Generation Mix (ASES, GWh)
Figure 60 Lao PDR Generation Mix (ASES, %)
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,0002
01
0
20
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46
20
48
20
50
Gen
erat
ion
(G
Wh
)
Coal Hydro Wind Bio Solar CSP Hydro ROR
17% 14%8%
100%
83%
62%
43%
27%23%
11%
20%
23%26%
4%
9%
15%
10%
6%
10%
19%
24%
3% 7% 9%
7% 7% 7%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2010 2015 2020 2030 2040 2050
Ge
ne
rati
on
Mix
Coal Hydro Wind Bio Solar CSP Hydro ROR
FINAL
Intelligent Energy Systems IESREF: 5973 79
Table 23 Lao PDR Generation by Type (ASES, GWh)
Resource 2010 2015 2020 2030 2040 2050
Coal 0 887 2,354 3,077 1,689 0
CCS 0 0 0 0 0 0
Diesel 0 0 0 0 0 0
Fuel Oil 0 0 0 0 0 0
Gas 0 0 0 0 0 0
Nuclear 0 0 0 0 0 0
Hydro 2,093 4,211 10,295 15,786 15,662 16,408
Onshore Wind 0 0 1,807 7,117 13,444 18,510
Offshore Wind 0 0 0 0 0 0
Biomass 0 0 690 2,963 5,253 3,758
Biogas 0 0 0 156 3,721 3,006
Solar 0 0 1,038 3,532 10,887 17,091
CSP 0 0 0 1,010 3,939 6,100
Battery 0 0 0 0 0 0
Hydro ROR 0 0 348 2,698 3,877 5,009
Geothermal 0 0 0 0 334 333
Pump Storage 0 0 0 0 0 0
Ocean 0 0 0 0 0 0
Off grid 0 0 0 0 0 0
Table 24 Lao PDR Generation Share by Type (ASES, %)
Resource 2010 2015 2020 2030 2040 2050
Coal 0% 17% 14% 8% 3% 0%
CCS 0% 0% 0% 0% 0% 0%
Diesel 0% 0% 0% 0% 0% 0%
Fuel Oil 0% 0% 0% 0% 0% 0%
Gas 0% 0% 0% 0% 0% 0%
Nuclear 0% 0% 0% 0% 0% 0%
Hydro 100% 83% 62% 43% 27% 23%
Onshore Wind 0% 0% 11% 20% 23% 26%
Offshore Wind 0% 0% 0% 0% 0% 0%
Biomass 0% 0% 4% 8% 9% 5%
Biogas 0% 0% 0% 0% 6% 4%
Solar 0% 0% 6% 10% 19% 24%
CSP 0% 0% 0% 3% 7% 9%
Battery 0% 0% 0% 0% 0% 0%
Hydro ROR 0% 0% 2% 7% 7% 7%
Geothermal 0% 0% 0% 0% 1% 0%
Pump Storage 0% 0% 0% 0% 0% 0%
Ocean 0% 0% 0% 0% 0% 0%
Off grid 0% 0% 0% 0% 0% 0%
FINAL
Intelligent Energy Systems IESREF: 5973 80
7.5 Grid to Grid Power Flows
Figure 61 plots the imports and exports in the ASES with the dotted line representing the net
interchange. The power flows in the ASES is similar in magnitude to the SES with most of the
power exported to Thailand around 2025 and into the central and north regions of Viet Nam
from 2030. Similar to the SES, imports into Lao PDR come from Thailand due to diversification
benefits and additional power flows required into Viet Nam due to its significant shift from
fossil fuels to renewable energy.
Figure 61 Lao PDR Imports and Exports (ASES, GWh)
7.6 Generation Fleet Structure
To gain insight into the nature of the mix of generation technologies deployed in the ASES,
we present a number of additional charts. Figure 62 and Figure 63 show Lao PDR’s installed
capacity by generation type for the SES – this is clearly biased towards renewable generation
forms as there are no additional thermal projects built after 2015. For Lao PDR, a
considerable amount of non-renewable energy continues to feature in the generation mix in
the earlier years before declining to 0 by 2050.
-80,000
-60,000
-40,000
-20,000
0
20,000
40,000
60,000
20
15
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49
Flo
ws
(GW
h)
Imports Exports Net
FINAL
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Figure 62 Lao PDR Installed Capacity by Type (ASES, MW)
Figure 63 Lao PDR Generation Mix by Type (ASES, GWh)
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Figure 64 shows the dispatchable, semi-dispatchable and non-dispatchable components of
installed capacity and it can be seen that semi-dispatchable increases to around 65% of the
total system capacity compared to around 9% in the BAU by 2050. Based on operational
simulations with this resource mix, it appears to be operationally feasible, and generation
forms that provide storage and having flexibility in the demand side play important roles. It
is clear that short-term renewable energy solar and wind forecasting systems will be
important, as will real-time updates on demand that can be controlled. Furthermore, control
systems that can allow the dispatch of flexible resources on both supply and demand sides
of the industry will be required.
Figure 64 Lao PDR Installed Capacity by Dispatch Status (ASES, MW)
7.7 Reserve Margin and Generation Trends
Figure 65 plots the reserve margin under the ASES. Figure 66 and Figure 67, respectively,
show the installed capacity mix and generation mix for different categories of generation in
the power system. The ASES reserve margin trends past 100% as Lao PDR has projects built
to supply power into Viet Nam and to a smaller extent to the other neighbouring countries.
It is worth noting conventional reserve margin measures are generally not suited to
measuring high renewable energy systems in the same context used for thermal-based
systems. Renewable technologies generally have much lower capacity factors and require
more capacity to meet the same amount of energy produced from thermal-based
technologies.
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Figure 65 Lao PDR Reserve Margin (ASES)
Figure 66 Lao PDR Installed Capacity Shares for ASES by Generation Type
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Figure 67 Lao PDR Generation Shares for ASES by Generation Type
7.8 Electrification and Off-Grid
Lao PDR’s grid-electrification rate for its urban and rural population is assumed to reach close
to 100% by 2030 as per the BAU.
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8 Analysis of Scenarios
Sections 5, 6 and 7 presented projections of capacity and generation mix for the BAU, SES
and ASES scenarios respectively. In order to understand the implications of the SES and ASES
over the BAU, we have formulated a set of metrics to assist in their comparison.
These are as follows:
Overall energy consumption per year;
Peak electricity demand per year;
Renewable energy percentage comparisons;
Carbon emissions measures;
Hydro power developments;
Analysis of bioenergy situation;
A number of simple security of supply measures; and
Interregional power flows.
8.1 Energy and Peak Demand
Figure 68 compares the total electricity consumption of the BAU, SES and ASES with Figure
69 plotting the percentage reduction in electricity consumption of the SES relative to the
BAU and ASES relative to the BAU. As can be seen the energy consumption of SES is lower
than the BAU with the main driver being enhancements in energy efficiency in the SES. The
reduction in energy in the ASES is partially offset by the doubling of electric transport
demand.
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Figure 68 Lao PDR Electricity Demand Comparison
Figure 69 Lao PDR Percentage Reduction in Electricity Demand
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Figure 70 compares peak load and shows the same relativities. This is attributable to
improvements in load factor (80% in SES and ASES). On top of this the SES and ASES has
contributions from flexible and controllable demand that allows reductions in peak
demand consumption (not shown here).
Figure 70 Lao PDR Peak Demand Comparison
8.2 Energy intensity
Figure 71 plots the per capita electricity consumption per annum across the scenarios.
Electricity consumption includes all electricity consumption across the country. In the BAU,
per capita consumption levels increase at a rate of 5.4% to reach 5,200 kWh pa which is
significantly less than Hong Kong’s current level. In the ASES and SES, it increases more slowly
at 4.8% pa and 4.5% pa, respectively, due tohigher energy efficiency savings. It should be
noted that GDP growth assumptions remain constant across all scenarios with the difference
in the ASES and SES being measures taken to improve energy efficiency.
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Figure 71 Lao PDR Per Capita Consumption Comparison (kWh pa)
8.3 Generation Mix Comparison
Figure 72 and Figure 73 below show the renewable capacity and generation mix between the
two scenarios. Renewable capacity (including large-scale hydro) reaches 85% in the BAU,
which is equivalent to a 74% generation share driven by significant large-hydro exploitation.
The SES and ASES reaches 100% renewable capacity and generation capacity by 2050.
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Singapore - 2014 HK - 2014 Japan - 2014
Taiwan - 2014
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Figure 72 Lao PDR Renewable Installed Capacity Mix
Figure 73 Lao PDR Renewable Generation Mix Comparison
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8.4 Carbon Emissions
Figure 74 and Figure 75 show the carbon intensity of Lao PDR’s power system and the total
per annum carbon emissions respectively. The intensity trajectory goes up in the BAU as
more coal enters the scenario reaching 0.22t-CO2e/MWh by 2050. The SES gets to 0.02t-
CO2e/MWh by 2050 and the ASES is 100% carbon emissions free45. In terms of total carbon
emissions, the shift towards the SES and ASES saves up to 12 and 13 mt-CO2e, respectively,
or the equivalent to a 93% and 100% saving from the BAU. The emissions savings are
relatively small due to the large amount of large-hydro generation in the BAU.
Figure 74 Lao PDR Carbon Intensity Comparison
Figure 75 Lao PDR Carbon Emissions Comparison
45 We assume zero emissions from hydro and bio-generation.
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8.5 Hydro Power Developments
Table 22 lists the hydro generation projects and commissioning year under the three
scenarios. Hydro projects are assumed to be refurbished as required to maintain operations
throughout the modelling horizon. As discussed earlier, projects such as Xekaman 4 located
in other countries but dedicated to exports are included as projects in the export markets
(with capacities adjusted accordingly)46.
Table 25 Lao PDR Hydro Power Developments for BAU, SES, ASES
Hydro Project Installed Capacity
(MW)
Year Commissioned
BAU SES ASES
Nam Ngiep 2 180 2015 2015 2015
Nam Ou 2 120 2015 2015 2015
Nam Ou 5 240 2015 2015 2015
Nam Ou 6 180 2015 2015 2015
Nam Kong 2 66 2015 2015 2015
Xekaman 1 64.4 2016 2016 2016
Nam Sim 8 2016 2016 2016
Nam Mang 1 64 2016 2016 2016
Nam Beng 34 2016 2016 2016
Nam Sane 3A 69 2016 2016 2016
Nam Sane 3B 45 2016 2016 2016
Nam Lik 1 61 2017 2017 2017
Nam Phay 86 2018 2018 2018
Nam Tha 1 (Nam Pha) 168 2018 2018 2018
Xekaman 4 16 2018 2018 2018
Xayabouly (Mekong) 65 2020
Projects not developed in the SES and ASES
Sepian-Xenamnoy 56 2021
Nam Ngiep 1 21 2021
Nam Pha 130 2021
Nam Phak 45 2021
8.6 Analysis of Bioenergy
Figure 76 shows a projection of the biomass available for the GMS (converted to GWh) and
the total biomass generation for each scenario for the GMS. The shaded pink area represents
46 The hydro projects for future construction selected here are example or generic hydro projects only and do not mean that we have a particular preference for those hydro projects compared to others.
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the projected total technical biomass resource availability47 while the solid lines show the
biomass consumption used by each scenario. The projected available biomass was based on
forecast growth rates in the agricultural sectors of each country. It was assumed that no
more than 75% of the total projected available biomass resource was used. The remainder
of the bioenergy requirements for each scenario was then assumed to be satisfied by biogas
technologies.
Figure 77 shows a similar chart to Figure 76 for the GMS except for biogas. The green shaded
area in this chart represents the amount of biogas available (again in units of GWh) and the
corresponding generation from biogas in each scenario. This shows that the SES and ASES
are dependent on biogas while the BAU is assumed to not deploy this technology. Based on
the projections the biomass and biogas resources available to the region can be seen to be
sufficient to support the amount of biomass and biogas generation to 2050.
Figure 76 Projected Biomass Availability and Consumption in the BAU, SES and
ASES scenarios for the GMS as a whole
47 Projections of biomass availability developed by IES based on baselines established from information on biomass and biogas potential reported in ‘Renewable Energy Developments and Potential in the Greater Mekong Subregion’, ADB (2015) report.
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Figure 77 Projected GMS Biogas Requirements
8.7 Security of Supply Indicators
Figure 78 plots the energy reserve margin calculated as the difference between the maximum
annual potential production from all plants accounting for energy limits and the annual
electricity demands in percentage terms. For exporting countries like Lao PDR the energy
reserve margins are generally high as seen in the SES and ASES cases where generation is
optimised across the region. As noted previously, an energy reserve margin is more suited
to measuring systems that are renewables-based.
Figure 78 Lao PDR Security of Supply Measure: Energy Reserve
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Figure 79 charts the percentage of electricity generated using domestic resources. The
percentage generated using domestic fuel sources starts above 95% and increases over
time. In the BAU the coal supply supporting 1,900 MW of coal-fired generation including
the Hong Sa coal project is sourced domestically. In all scenarios, the variations below 100%
are due to power imports into Lao PDR.
Figure 79 Lao PDR Security of Supply Measure: Percentage of Electricity
Generated by Domestic Resources
Figure 80 below plots the highest share of generation from a particular fuel source. In the
BAU, the dominance is held by large-scale hydro generation throughout the horizon. The SES
is dominated by large-scale hydro up until 2040 before solar PV captures 22% generation
share towards 2050. The ASES follows the same trend as the SES except wind energy solar
PV dominates the generation mix towards 2050 followed by solar PV at 24%. Across all
scenarios, it is clear that the SES and ASES generation mixes are a lot more diversified than
in the BAU.
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Figure 80 Lao PDR Security of Supply Measure: Maximum Dominance of a
Technology in Generation Mix
Figure 81 plots the dependence on coal in all scenarios. The AES and SES trajectories decline
as expected whereas the BAU increases to 25% by 2050 as 1,900 MW of coal projects
dedicated to Lao PDR is brought into the mix to meet increasing demands.
Figure 81 Lao PDR Security of Supply Measure: Coal Share
8.8 Interregional Power Flows
Figure 82 compares the net flows in and out of Lao PDR. It is clear Lao PDR is a net exporter
given its significant renewable resource and development potential. Lao PDR primarily
exports to Viet Nam through its interconnections into the north and central regions of Viet
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Nam. By 2050, its gross export limit is 1,000 MW into Lao PDR, 3,000 MW into Thailand, and
10,000 MW into Viet Nam for the SES and ASES cases.
Figure 82 Lao PDR Imports (positive) and Exports (negative) (GWh)
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9 Economic Implications
In this section we consider the economic implications of the three scenarios and examine in
particular: (1) the levelised cost of electricity (LCOE) generation for the entire system, (2)
investment costs, (3) total operating and capital expenditure including the cost of energy
efficiency and (4) implications for job creation. It should be noted that the analysis presented
in this section is done for the purpose of comparison, and that the prices and costs provided
are dependent on the fuel price projections and technology cost assumptions that were used
in the scenarios and which have been listed in Appendix A and Appendix B. The analysis in
this section is also supported by sensitivity analysis to examine how changes in fuel prices
impact the LCOE and to examine how a carbon price would affect electricity costs.
9.1 Overall Levelised Cost of Electricity (LCOE)
The comparison of the LCOE (only includes generation costs) is shown in Figure 83. The LCOE
for the BAU starts to decrease as more large-scale hydro is deployed then gradually increases
as coal inputs start to rise, and large-scale hydro CAPEX increases as resource exploitation
becomes more difficult. By 2050 the BAU trends towards $67/MWh. The ASES and SES
initially decline then increase together to approximately $76/MWh by 2050 driven by
investment into more expensive renewable energy technologies relative to conventional coal
and large-scale hydro. This LCOE analysis does not include the cost of externalities48.
48 A detailed study on the cost of externalities is presented in the following reference: Mark Z. Jacobson et al., “100% Clean and Renewable Wind, Water, and Sunlight (WWS) All Sector Energy Roadmaps for 139 Countries of the World”, 13 December 2015, available: https://web.stanford.edu/group/efmh/jacobson/Articles/I/CountriesWWS.pdf .
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Figure 83 Lao PDR LCOE for Generation
9.2 LCOE Composition
High integration levels of renewable energy forms like wind and solar can avoid fuel
consumption and hence fuel costs. In order to understand the structure of the LCOE from
the previous section we provide decomposed versions of the LCOE in Figure 83 for the BAU,
Figure 84 for the SES and Figure 85 for the ASES. This reveals an important trend in the
structure of the cost of electricity: a thermal-dominated system has a high portion of its costs
as fuel costs while a renewable energy dominated power system is more heavily biased
towards capital costs.
The capital costs in the BAU increases slightly from 2030 because of increasing large-hydro
CAPEX and fuel costs increase as the coal share of generation increases over time. The SES
and ASES cost structures are very similar due to the similar generation developments with
the SES – the CAPEX in both gradually increases with the investment into battery storage,
biogas and CSP technology.
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Figure 84 Lao PDR LCOE Composition in BAU
Figure 85 Lao PDR LCOE Composition in SES
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Figure 86 Lao PDR LCOE Composition in ASES
9.3 Cumulative Capital Investment
The following section details the investment costs of meeting demand in Lao PDR taking into
account exports. The reallocated investment and operating costs of net exporting countries
will be reduced according to the percentage of power that is exported.
Figure 87 shows the cumulative investment in generation CAPEX and energy efficiency in
millions of Real 2014 USD. Figure 87 shows the BAU requiring the most capital investment
by the end of the modelling horizon primarily driven by the higher BAU demands. The SES
and ASES includes investment in energy efficiency measures and greater investments in CSP,
biogas and battery storage to defer generation post-2035 with the ASES requiring the least
investment because of lower demands. The lower demand in SES and ASES owing to energy
efficiency gains has a clear impact on investments.
The breakdown of costs by generation type are presented in Figure 88, Figure 89 and Figure
90. These charts include pro-rated investment costs relating to the dedicated capacity of
export units such as the Hong Sa coal project and Xekaman 4, classified as ‘investment for
export.
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Figure 87 Lao PDR Cumulative Investment (Real 2014 USD)
Figure 88 Lao PDR Cumulative Investment by Type (BAU, Real 2014 USD)
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Figure 89 Lao PDR Cumulative Investment by Type (SES, Real 2014 USD)
Figure 90 Lao PDR Cumulative Investment by Type (ASES, Real 2014 USD)
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Figure 91, Figure 92 and Figure 93 plot the cumulative investment split for imports and
exports. The BAU investment cost is made up of projects to supply domestic requirement
and dedicated projects for exports. By 2050, $27 billion is required to develop the BAU
generation requirements, and $18 billion for exports primarily made up of hydro projects. In
the SES, $22 billion is required to develop generation projects (and energy efficiency) in Lao
PDR, with a further $25 billion invested in projects within Lao PDR for exporting. The ASES
requires $19 billion with an additional $32 billion invested in Lao PDR from neighbouring
countries to export surplus resource potential. Note the projects for export, mainly to Viet
Nam, in the SES and ASES are mainly renewable energy developments as the region moves
away from its reliance on fossil-fuel technologies.
Figure 91 Lao PDR Cumulative Investment of BAU (Real 2014 USD)
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Figure 92 Lao PDR Cumulative Investment of SES (Real 2014 USD)
Figure 93 Lao PDR Cumulative Investment of ASES (Real 2014 USD)
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9.4 Operating Costs, Amortised Capital Costs and Energy Efficiency Costs
Figure 94 plots the total CAPEX, OPEX and energy efficiency costs as a proportion of total
forecast GDP49. Capital expenditure has been amortised over the life of the project to derive
annual capex figures. The BAU rises to almost 5.5% of GDP mainly driven by the ramp up in
new entry with respect to increasing demands in Lao PDR. The BAU requires a higher cost
outlay to 2030 but converges to the SES towards 2050 to around 4% of GDP. The ASES
remains the lowest cost option across the horizon among the three scenarios. Figure 95,
Figure 96, and Figure 97 plots the total annual system cost for each of the scenarios.
Figure 94 Total CAPEX, OPEX and Energy Efficiency over GDP
49 Figures have been adjusted for exports
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Figure 95 Total System Cost by Type (BAU)
Figure 96 Total System Cost by Type (SES)
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Figure 97 Total System Cost by Type (ASES)
Figure 98 and Figure 99 plots the difference in amortised CAPEX, OPEX and energy efficiency
costs between the SES and BAU, and ASES and BAU respectively. The costs have also been
adjusted for exports and imports. Positive amounts represent an additional investment
required in either the SES or ASES and negative amounts correspond to cost savings.
For the SES against BAU case, fuel savings of up to $300 million occur post 2030 when more
coal capacity comes online whereas additional CAPEX in the SES is needed over and above
the BAU in the period from 2030-2045. This is due to higher renewable energy technology
costs against low cost conventional coal and large-scale hydro. Post-2045 hydro reaches
$3,000/kW against lower renewable technology costs causing a flip from additional CAPEX
expenditure to savings in the SES case. After taking into account the $230 million energy
efficiency cost, the SES comes out slightly ahead of the BAU by about $200 million a year by
2050.
The ASES experiences cost savings in CAPEX compared to the BAU due to the reduced
demand. Fuel cost savings are double that compared to the previous chart due to lower
bioenergy generation required. By 2050 the net impact of OPEX, CAPEX and energy efficiency
produces a net saving of $520 million a year by 2050.
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Figure 98 Difference in CAPEX, OPEX and Energy Efficiency Costs (SES and BAU)
Figure 99 Difference in CAPEX, OPEX and Energy Efficiency Costs (ASES and BAU)
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Figure 100 NPV of System Costs (2015-2050) over period 2015 to 2050
Figure 100 charts the net present value of the power system costs by component using an
8% and 15% discount rate. Figures are tabulated in Table 26. The BAU is comprised of a higher
percentage of fuel costs, whereas the ASES has the highest percentage relating to capital
costs. The total NPV difference between the BAU and ASES is approximately $1 billion under
an 8% discount rate
Table 26 NPV of System Costs (Real USD 2014)
NPV ($m’s) BAU @
8% SES @
8% ASES @
8% BAU @
15% SES @
15% ASES @
15%
Fuel Cost 2,451 1,462 1,252 796 502 516
Capital Cost 11,378 11,430 10,330 4,837 4,871 4,394
FOM 1,003 1,015 950 434 427 393
VOM 299 629 588 102 213 201
Energy Efficiency 0 469 798 0 151 267
Total 15,130 15,005 13,918 6,168 6,164 5,770
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9.5 Fuel Price Sensitivity
Figure 101 plots the LCOE of the BAU, SES and ASES as discussed in section 9.2. In addition,
it plots the LCOE for a 50% increase to all fuel prices50, which reflects the difference
between IEA’s crude oil pricing under the 450 Scenario and the Current Policies Scenario
($95/bbl and $150/bbl respectively). It can be seen that the LCOE of the BAU rises more
(up to $5/MWh) against a fuel price increase compared with smaller increases in the SES
and ASES as would be anticipated as a direct consequence of having a higher thermal
generation share in the BAU compared to renewable energy in the SES and ASES. The SES
increases, and the ASES to a smaller extent, as a consequence of bioenergy generation, but
still less sensitive to fuel price shocks than the BAU.
Figure 101 Lao PDR Fuel Price Sensitivity ($/MWh)
9.6 Impact of a Carbon Price
In a similar way to the previous section, Figure 102 plots the LCOE under the BAU, SES and
ASES and the LCOE under a carbon price scenario. The carbon scenario puts a $20/t-CO2
impost throughout the entire modelled period. This is intended to show the sensitivity of
the BAU, SES and ASES to a carbon price. In a similar way to the previous section, this shows
50 Coal prices, natural gas prices, uranium prices, biomass prices, biogas prices, diesel and fuel oil.
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that LCOE in the SES and ASES is insensitive to carbon prices by 2050 while for the BAU, it
adds an additional $4 Real 2014 USD/MWh to the LCOE because of its coal generation.
Figure 102 Lao PDR Carbon Sensitivities ($/MWh)
9.7 Renewable Technology Cost Sensitivity
Figure 103 shows the LCOE sensitivity to 20% and 40% decreases in renewable technology
costs. As expected the ASES followed by the SES is the most sensitive with potential declines
of up to $19/MWh from the base under the highest sensitivity case. The results also show
that a 20% drop in the assumed renewable technology CAPEX will bring the LCOE in line with
the BAU.
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Figure 103 Renewable Technology Cost Sensitivities ($/MWh)
9.8 Jobs Creation
To assess the implications for Job Creation for each scenario we applied the methodology
used by the Climate Institute of Australia. The methodology is summarised in Appendix C.
The numbers of jobs created for each of the scenarios are shown in Figure 104, Figure 105
and Figure 106. The job categories shown include: manufacturing, construction, operations
and maintenance and fuel supply management. Figure 107 provides a comparison of total
jobs created for BAU, SES and ASES. The key observations are:
Across all scenarios, manufacturing and construction account for most of the jobs with
a much smaller share attributable to O&M and fuel supply.
The BAU job creation profile peaks at around 17,000 jobs compared to SES job creation
peaking towards 58,000 or more than three times that in the BAU. This is entirely driven
by renewable energy developments that require more jobs in the manufacturing and
construction phases.
The ASES job creation peaks at 70,000 jobs, or more than four times that of the BAU
driven by even more renewable energy projects required as the region moves towards
a 100% renewable generation target by 2050.
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Different skills are required between the scenarios, BAU has people working on
conventional coal and hydro, whereas the SES and ASES has people mainly working on
solar & battery storage systems.
Note that the manufacturing and fuel supply jobs shown to be created may not be
created within Lao PDR with manufacturing of equipment and fuel management (for
imported fuels) occurring in other countries.
Figure 104 Job Creation by Category (BAU)
Figure 105 Job Creation by Category (SES)
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Figure 106 Job Creation by Category (ASES)
Figure 107 Total Job Creation Comparison BAU, SES and ASES
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10 Conclusions
In this report we have presented the findings of power system modelling of Lao PDR’s
power system for a Business as Usual (BAU), Sustainable Energy Sector (SES) and Advanced
SES (ASES) scenarios for Lao PDR’s. The BAU outlook assumed that future power sector
developments would be based on continued large scale hydro development and coal. The
SES and ASES have both taken measures to deploy a maximal amount of renewable energy
and energy efficiency measures in order to provide some alternative scenarios for the
country. The SES and ASES both also assume a more rapid program of cross-border
interconnection in the GMS, which allows the region to more fully exploit diversity in
demand as well as geographically dispersed areas with high renewable energy potential.
10.1 Comparison of Scenarios
The following are the key conclusions that have been drawn from the analysis presented in
this report:
The SES delivers an energy efficiency gain beyond the BAU case of about 21% compared
to the BAU. The ASES delivers efficiency gains of 28% after doubling transport
electricity demand.
By 2030, the SES and ASES are able to achieve a power system that can respectively
deliver some 91% and 96% of generation from renewable energy (including large-scale
hydro). This compares to 75% in the BAU.
By 2050, the SES and ASES are able to achieve a power system that delivers 98% and
100% of generation from renewable energy resources (including large-scale hydro). In
contrast 75% of generation in the BAU is provided by renewable energy resources by
205051.
By 2050, the SES and ASES avoids around 12 and 13 million tons of greenhouse gas
emissions per year compared to the BAU. All scenarios achieve very low carbon
intensities given Lao PDR’s dependence on large-scale hydro in the BAU.
Compared to the SES, by 2050, the country has avoided developing 1500 MW of coal,
and 1905 MW of coal in the ASES. The SES and ASES would be able to mitigate against
externalities and potential health risks associated with developing these projects52.
The SES and ASES compared to the BAU have not needed to develop some 5817 MW
of large scale hydro projects.
Based on some simple measures for energy security:
- Under the ASES and SES, Lao PDR benefits from a more diverse mix of technologies
and is not as dependent on a single source of primary energy as the BAU; for
example, the BAU is highly dependent on large-scale hydro and coal, while the
51 Large-scale hydro is included
52 Further information on health impacts related to coal projects is provided in the Harvard University study: Cropper et. al. “The Health Effects of Coal Electricity Generation in India”, 2012, available from: http://www.rff.org/files/sharepoint/WorkImages/Download/RFF-DP-12-25.pdf.
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ASES and SES diversifies supply across a range of renewable energy technologies
with no generation type accounting for more than 30% of the generation share by
2050;
- All of the scenarios have close to 100% of electricity generated from domestically
controlled and managed resources. Under each of the scenarios a small amount of
power is imported from Thailand because of mismatches in renewable resource
profiles furthering the argument for strong interconnection amongst the GMS
countries under a sustainable energy scenario; and
- The ASES and SES achieve a reliable power system through coordination on both
the supply and demand side of the industry, with similar energy reserve margins
as the BAU after accounting for exports. Though as a measure of energy supply
storage and flexibility the ASES and SES overall is lower than the BAU, which means
that the BAU would be more resilient against extreme events. This enhances the
need to pursue an integrated regional power system through cross-border trading.
While modelling has shown that the ASES and SES is operationally feasible (even
with less directly dispatchable resources in the SES compared to the BAU), stress
testing of the BAU, SES and ASES scenarios against more significant threats to the
operation of the power system would likely not be handled as well compared to
the BAU. More work to understand and develop appropriate mitigation measures
is required.
10.2 Economic Implications
10.2.1 Cost of Electricity
Based on the outcomes of modelling the BAU, SES and ASES scenarios, we also examined the
following issues in relation to electricity costs: (1) levelised cost of electricity, (2) investment
requirements, (3) sensitivity of electricity prices to fuel price shocks, and (4) the implications
of a price on carbon equivalent emissions for electricity prices. Based on this analysis we draw
the following conclusions:
The BAU requires higher levels of capital investment than the SES and ASES, and in
relation to generation costs, the ASES across the modelling period delivers a lower
overall generation cost (dollar terms);
Under the SES and ASES significant benefits are gained in the form of avoided fuel costs
and this contributes to achieving a lower overall dollar cost for Lao PDR. The
observation is made that the composition of LCOE under the SES and ASES is largely
driven by investment costs, hence exposure to fuel shocks is significantly reduced; and
The LCOE under the SES and ASES is also largely insensitive to a carbon price, as could
be reasonably anticipated for a power system that is entirely dominated by renewable
energy.
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10.2.2 Investment Implications
From 2015 to 2050, the total cumulative investment in BAU, SES and ASES is respectively:
$27 billion, $22 billion, and $19 billion (Real 2014 USD). The composition of the investments
between BAU and the SES/ASES are quite different:
76% of the cumulative investments in the BAU are directed to hydro, followed by 16%
coal, the rest being a combination of renewables;
In the SES/ASES, investments are more diverse:
- SES has 38% solar and battery, 22% hydro, 14% wind, 13% energy efficiency and
the rest bioenergy; and
- ASES has 32% solar and battery, 25% energy efficiency, 18% hydro, 15% wind and
the rest bioenergy.
10.2.3 Jobs Creation
The SES and ASES scenarios both result in quite different technology mixes for Lao PDR
compared to the BAU. The SES and ASES have different implications for the workforce that
would need to be developed to support each scenario. Based on estimates of job creation,
we estimate that53:
The BAU from 2015 to 2050 would be accompanied by the creation of some 475,452
jobs years54 (40% manufacturing, 44% construction, 14% operations and maintenance,
and 2% fuel supply);
The SES would involve the creation of some 1.24 million job years (33% in
manufacturing, 56% in construction, 11% in operations and maintenance and 0.3% in
fuel supply); and
The ASES would involve the creation of 1.4 million job years (33% in manufacturing,
56% in construction, 10% in operations and maintenance and 0.2% in fuel supply).
10.3 Identified Barriers for the SES and ASES
The following barriers specific to Lao PDR were identified in the country assessment report:
There needs to be an increased focus on energy efficiency as electricity demand ramps
up in line with expected GDP growth over the next 10 years. To date there has not
been much work carried out by the government institutions in forming guidelines or
integrating energy efficiency measures into existing energy policy direction.
There are currently no specific policies or strategies on renewable energy promotion;
Lack of coordination between stakeholders in renewable energy projects;
53 Based on the employment factors presented in Appendix C.
54 A job year is one job for one person for one year. We use this measure to make comparisons easier across each scenario as the number of jobs created fluctuates from year to year.
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Renewable energy policy has not yet been clearly stated in the National Socio-
economic Development Plans or in strategies on growth and poverty reduction, as well
as five year plans of the government;
Lack of specific regulations and laws on renewable energies;
It is not clear who is responsible for approval of renewable energy projects;
Users have insufficient knowledge and understanding on renewable energy;
Lack of public funding support for the renewable energy sector, especially for research
and development;
Absence of energy pricing regulation is a risk for investors;
Insufficient information on renewable energy potential for provincial level; and
Electricity access rate in remote areas is still low due to high cost of grid extension.
Other barriers to the development of renewable energy include:
Awareness barriers among policy makers;
Significantly higher capital investment costs compared to conventional fuels;
Technical barriers including expertise and lack of standards for renewable energy
systems; and
There is currently also a lack of effective and considered measures relating to adverse
social and environmental impacts of large scale hydropower projects.
10.4 Recommendations
The following are key recommendations to reduce the barriers and “enable” the SES and
ASES:
Formation of more comprehensive energy policies to create an environment that
promotes investment in renewable energy technologies and energy efficiency
measures. Investor confidence in renewable energy investments will be enhanced by
having a stable and clear policy framework that, for example, provides a structured and
clear approach for renewable energy investors and steps by which to enter into offtake
agreements.
Formation of electricity pricing policies and mechanisms that encourage efficient
behavior and investment in generation technologies, transmission and distribution
equipment and end use energy consumption.
Conduct more detailed assessments of renewable energy potential and make the
results publicly available to enable prospective investors to understand the potential,
identify the best opportunities and subsequently take steps to explore investment and
deployment.
Knowledge transfer and capability building in the renewable energy technologies and
energy efficiency for policy makers, staff working in the energy industry, as well as
within education institutions to ensure the human capacity is being developed to
support a national power system that has a high share of generation from renewable
energy.
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Investments in ICT systems to allow for greater real-time monitoring, control and
forecasting of Cambodia’s national power system, including SCADA/EMS, and smart-
grid technology and renewable energy forecasting systems and tools. This will enable
efficient real-time dispatch and control of all resources in Cambodia’s national power
system and will create an environment more conducive for the management of high
levels of renewable energy in the generation mix.
Take measures to encourage cross-border power trade in the region, as this works to
the advantage of exploiting scattered renewable energy resource potentials and
diversity in electricity demand. In particular:
- Develop an overarching transmission plan that has been informed by detailed
assessments and plans to leverage renewable energy potential in the region and
diversity in demand and hydrological conditions. For Lao PDR, we see that under
the SES and ASES the country becomes an exporter of a more diverse mix of
resources (solar, hydro and wind) as compared to the BAU where the country is
mainly an exporter of hydro. In the SES and ASES Lao PDR’s potential in solar and
wind is leveraged to the benefit of the region.
- Enhance technical standards and transmission codes in each country to allow for
better interoperation of national power systems.
- Establish dispatch protocols to better coordinate real-time dispatch of power
systems in the region to make the best use of real-time information and
continuously updated demand and renewable generation forecasts.
- Develop a framework to encourage energy trade in the region, and in particular
towards a model that can support multilateral power trading via a regional power
market or exchange (for example).
Take measures to improve power planning in the region to:
- Explicitly account for project externalities and risks;
- Evaluate a more diverse range of scenarios including those with high levels of
renewable energy;
- Take into consideration energy efficiency plans;
- Take into consideration overarching plans to have tighter power system
integration within the region; and
- Carefully evaluate the economics of off-grid against grid connection where this is
relevant.
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Appendix A Technology Costs
Table 27 sets out the technology cost assumptions that were used in the modelling
presented in this report for the BAU and SES scenarios. Table 28 sets out the technology
costs used in the ASES. The technology costs of coal and gas do not include overheads
associated with infrastructure to develop facilities for storing / managing fuel supplies.
These costs were however accounted for in the modelling.
Figure 108 and Figure 109 presents the levelised cost of new entry generation based on
assumed capacity factors. LCOE levels presented in Section 9 are based on weighted
average LCOE’s and modelled output and will differ from the LCOE’s presented here. The
LCOE for battery storage is combined with solar PV technology assuming 75% of generation
is stored for off-peak generation.
Table 27 Technology Costs Assumptions for BAU and SES Scenarios
Technology Capital Cost (Unit: Real 2014 USD/kW)
Technology 2015 2030 2040 2050
Generic Coal 2,492 2,474 2,462 2,450
Coal with CCS 5,756 5,180 4,893 4,605
CCGT 942 935 930 926
GT 778 772 768 764
Wind Onshore 1,450 1,305 1,240 1,175
Wind Offshore 2,900 2,610 2,480 2,349
Hydro Large 2,100 2,200 2,275 2,350
Hydro Small 2,300 2,350 2,400 2,450
Pumped Storage 3,340 3,499 3,618 3,738
PV No Tracking 2,243 1,250 1,050 850
PV with Tracking 2,630 1,466 1,231 997
PV Thin Film 1,523 1,175 1,131 1,086
Battery Storage - Small 600 375 338 300
Battery - Utility Scale 500 225 213 200
Solar Thermal with Storage 8,513 5,500 4,750 4,000
Solar Thermal No Storage 5,226 4,170 3,937 3,703
Biomass 1,800 1,765 1,745 1,725
Geothermal 4,216 4,216 4,216 4,216
Ocean 9,887 8,500 7,188 5,875
Biogas (AD) 4,548 4,460 4,409 4,359
*Battery technology quoted on a $/kWh basis
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Figure 108 Levelised Cost of New Entry (BAU & SES, $/MWh)
0
50
100
150
200
250
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49
Leve
lised
Co
st o
f G
ener
atio
n (
$/M
Wh
)
Hydro Wind Coal
Gas Bio Solar
CSP PV + Battery [75%] Hydro ROR
Geothermal Pump Storage
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Table 28 Technology Costs Assumptions for ASES Scenarios
Technology Capital Cost (Unit: Real 2014 USD/kW)
Technology 2015 2030 2040 2050
Generic Coal 2,492 2,462 2,450 2,437
Coal with CCS 5,756 4,893 4,605 4,334
CCGT 942 930 926 921
GT 778 768 764 761
Wind Onshore 1,450 1,240 1,175 1,113
Wind Offshore 2,900 2,480 2,349 2,225
Hydro Large 2,100 2,275 2,350 2,427
Hydro Small 2,300 2,400 2,450 2,501
Pumped Storage 3,340 3,618 3,738 3,861
PV No Tracking 2,243 1,050 850 688
PV with Tracking 2,630 1,231 997 807
PV Thin Film 1,523 1,131 1,086 1,043
Battery Storage - Small 600 338 300 267
Battery - Utility Scale 500 213 200 188
Solar Thermal with Storage 8,513 4,750 4,000 3,368
Solar Thermal No Storage 5,226 3,937 3,703 3,483
Biomass 1,800 1,745 1,725 1,705
Geothermal 4,215 4,215 4,216 4,215
Wave 9,886 7,187 5,875 4,802
Biogas (AD) 4,548 4,358 4,308 4,259
*Battery technology quoted on a $/kWh basis
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Figure 109 Levelised Cost of New Entry (ASES, $/MWh)
0
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150
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lised
Co
st o
f G
ener
atio
n (
$/M
Wh
)
Hydro Wind Coal
Gas Bio Solar
CSP PV + Battery [75%] Hydro ROR
Geothermal Pump Storage
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Appendix B Fuel Prices
Table 29 sets out the Free on board (FOB) fuel price assumptions that were used in the
modelling presented in this report. This fuel price set was common to all three scenarios.
Table 29 Fuel Price Assumptions (Real 2014 USD/GJ)
Year Coal Gas Diesel Uranium Fuel Oil Biomass Biogas
2015 2.39 10.08 13.34 0.72 9.13 2.57 1.00
2016 2.51 11.88 15.24 0.76 10.49 2.62 1.00
2017 2.63 12.91 15.28 0.80 11.68 2.67 1.00
2018 2.74 13.72 16.41 0.80 12.43 2.72 1.00
2019 2.86 14.47 17.53 0.80 13.18 2.78 1.00
2020 2.98 15.16 18.64 0.80 13.93 2.83 1.00
2021 3.10 15.81 19.73 0.80 14.65 2.89 1.00
2022 3.21 16.46 20.80 0.80 15.36 2.95 1.00
2023 3.33 17.10 21.86 0.80 16.06 3.01 1.00
2024 3.45 17.72 22.90 0.80 16.76 3.07 1.00
2025 3.56 18.34 23.93 0.80 17.44 3.13 1.00
2026 3.56 18.29 23.86 0.80 17.39 3.19 1.00
2027 3.56 18.24 23.79 0.80 17.34 3.25 1.00
2028 3.56 18.19 23.72 0.80 17.29 3.32 1.00
2029 3.56 18.14 23.65 0.80 17.24 3.39 1.00
2030 3.56 18.09 23.58 0.80 17.19 3.45 1.00
2031 3.56 18.06 23.53 0.80 17.15 3.52 1.00
2032 3.56 18.02 23.49 0.80 17.12 3.59 1.00
2033 3.56 17.99 23.44 0.80 17.08 3.67 1.00
2034 3.56 17.96 23.40 0.80 17.05 3.74 1.00
2035 3.56 17.92 23.35 0.80 17.02 3.81 1.00
2036 3.56 17.89 23.30 0.80 16.98 3.89 1.00
2037 3.56 17.86 23.26 0.80 16.95 3.97 1.00
2038 3.56 17.83 23.21 0.80 16.92 4.05 1.00
2039 3.56 17.79 23.16 0.80 16.88 4.13 1.00
2040 3.56 17.76 23.12 0.80 16.85 4.21 1.00
2041 3.56 17.76 23.12 0.80 16.85 4.29 1.00
2042 3.56 17.76 23.12 0.80 16.85 4.38 1.00
2043 3.56 17.76 23.12 0.80 16.85 4.47 1.00
2044 3.56 17.76 23.12 0.80 16.85 4.56 1.00
2045 3.56 17.76 23.12 0.80 16.85 4.65 1.00
2046 3.56 17.76 23.12 0.80 16.85 4.74 1.00
2047 3.56 17.76 23.12 0.80 16.85 4.84 1.00
2048 3.56 17.76 23.12 0.80 16.85 4.93 1.00
2049 3.56 17.76 23.12 0.80 16.85 5.03 1.00
2050 3.56 17.76 23.12 0.80 16.85 5.13 1.00
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Appendix C Methodology for Jobs Creation
This section briefly summarises the methodology that we adopted for jobs creation. The
methodology that we have adopted has been based on an approach developed by the
Institute for Sustainable Futures at the University of Technology, Sydney and used by the
Climate Institute of Australia55. In essence the jobs created in different economic sectors
(manufacturing, construction, operations & maintenance and fuel sourcing and
management) can be determined by the following with the information based on the
numbers provided in Table 30.
Figure 110 Job Creation Calculations
We have applied this methodology to the results in each scenario discussed in this report in
order to make estimates of the jobs creation impacts and allow comparisons to be made56.
55 A description of the methodology can be found in the following reference: The Climate Institute, “Clean Energy Jobs in Regional Australia Methodology”, 2011, available: http://www.climateinstitute.org.au/verve/_resources/cleanenergyjobs_methodology.pdf .
56 The percentage of local manufacturing and local fuel supply is assumed to be 1 to reflect the total job creation potential in total.
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Table 30 Employment Factors for Different Technologies
Annual decline
applied to
employment
multiplier
Co
nst
ruct
ion
tim
e
Co
nst
ruct
ion
Man
ufa
ctu
rin
g
Op
era
tio
ns
&
mai
nte
nan
ce
Fue
l
Technology 2010- 20 2020-30 years per MW per MW per MW per GWh
Black coal 0.5% 0.5% 5 6.2 1.5 0.2 0.04 (include
in O&M) Brown coal 0.5% 0.5% 5 6.2 1.5 0.4
Gas 0.5% 0.5% 2 1.4 0.1 0.1 0.04
Hydro 0.2% 0.2% 5 3.0 3.5 0.2
Wind 0.5% 0.5% 2 2.5 12.5 0.2
Bioenergy 0.5% 0.5% 2 2.0 0.1 1.0
Geothermal 1.5% 0.5% 5 3.1 3.3 0.7
Solar thermal
generation
1.5% 1.0% 5 6.0 4.0 0.3
SWH 1.0% 1.0% 1 10.9 3.0 0.0
PV 1.0% 1.0% 1 29.0 9.0 0.4