Climate-Energy-Economy Modeling:Scenarios for Designing a Sustainable Economy Transition
International Beirut Energy Forum 201925/9/2019
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Chiheb BoudenEcole Nationale d’Ingénieurs de Tunis
NATIONAL PRODUCTION TREND [KTOE]
Projections of the electricity demand
3
4
Energy Surplus
* Development of the demand* Implementation of the institutional framework, i.e. SOEs (STEG, ETAP, STIR)
* Growing awareness about the predictable energy deficit* Integration of Energy management and creation of specialized entity
* Energy transition in the industry* Institutional reform* Integration of IPP in electricity
Promoting:* Energy Efficiency* Renewable Energies* Natural Gas
Mto
e
Evolution of Energy Balance
95
8781
72
6056
59
5148
0
10
20
30
40
50
60
70
80
90
100
2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Energy Independance rate
FOCUS ON THE ELECTRICITY PRODUCTION SYSTEM
• Based on the voltage’s type, customers are connected to:Low Voltage customers (230/400V) primarily residential sectorMedium Voltage (10 kV, 15 kV et 30 kV)High Voltage (90 kV, 150 kV, 225 kV et 400 kV)
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Services12%
Tourism5%
Transport4%
Pumping and sanitary services
9%
Agriculture8%
Industries: extractive, food,
textile, paper and publishing, chemical,
construction materials, metal
62%HV & MV Electricity Consumption in 2016
ELECTRICITY DEMAND
471 MW / 9%
1 639 MW30%
1 040 MW19%
2 024 MW37%
302 MW / 5%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
5 476 MW
Cyclescombinés
Thermiques à vapeur
Turbines à combustion
Renouve-lables
IPP
3,3 TWh19%
8,4 TWh46%
3,7 TWh20%
2,2 TWh12%
0,5 TWh / 3%
18,1 TWh
677 ktep18%
1 480 ktep38%
994 ktep26%
687 ktep18%
3,8 Mtep
308 tep/GWh
272 tep/GWh
184 tep/GWh
218 tep/GWh
3 % d’ER
Electricity Supply by Technology (2016)
Electricity Demand
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Load Curve For 2009
Ele
ctric
ityD
eman
din
MW
Annual Electricity Demand
10
9 july 2019Night Peak
Day Peak
LOAD CURVE (SUMMER 2019)
Evolution of the demand daily profile
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Evolution amongst years
Tunisian Electricity Strategy
Enhence Electricity Efficiency (improve specific consumption)
Diversify the primary resources & create an balanced electricity MixObjectives:
• 12% Renewable Electricity by 2020• 30% Renewable Electricity by 2030
Re-create a reserve margin (10 to 15%)
Strengthen the grid to allow absorbtion of Renewable Electricity
Carry-out the project of Interconnection with Europe
Develop a pumed-Storage Hydroelectricity system (Large scale Storage)
Implement the smart grid
Wind Energy Potential8 GW
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PV Potential:900 GW
Renewable energies potentials
Biomass PotentialMillions Tons6
SDHWS Potential2millions m4
The Tunisian Solar Plan: 30% of Renewable Electricity by 2030
245
775
1305
1755250
555
868
30
155
392
642
150
450
45
80
100
0
500
1000
1500
2000
2500
3000
3500
4000
4500
2015 2020 2025 2030
E. Eolienne Centrales PV PV Individuel CSP Biomasse
257
MW
4%
1225
MW
14% 24
82M
W 2
4%
3815
MW
30%
Secteur Filière Capacité Période prévue de mise en service
STEGPV Systems 300 MW
South of Tunisia
2017-2020Wind Energy 80 MW
Tbaga (Kébili)
PPP & Self consumption
PV Systems 350 MW
Wind Energy 270 MW
All All sectors 1250 MW 2021-2025
All All sectors 1250 MW 2026-2030
The Tunisian Solar Plan
Expected Objectives: Contribute to achieve the objectives of 12% and 30% of
Renewable Electricity respectively by 2020 and 2030
Planned Projects
What are Next Steps?
• Presentation of APPLIED insights about long-term impacts of the national strategy
• Governmental inquiries (effects on energy budget, security of supply, …) • Economic impacts (GDP, evolution of the demand, prices,…)• Social considerations (job creation, development of the industry,…)• Environmental impacts (emissions gains and adaptation to NAMA)
• Need for a Modelling tool and development of Insights
CREATION OF A MODELLING GROUP
• OSeMOSYS and TEMOA could be considered as the most suitable models for our case Easy access to source code and different developed versions Effective information dissemination actions Accessibility to manuals Availability of capacity building and training Rapid growth: Wide range of flexibility and variability
Some Characteristics• A bottom-up, dynamic and linear optimisation model generator for long-run integrated assessment and energy
planning
• Aimed to calculate the lowest net present cost of an energy system to meet given demands and constraints
• Programming language: GNU MathProg (GMPL) language
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CHOICE:OSeMOSYS to model the Tunisian power system
Open Source energy Modelling SYStems « OSeMOSYS »
Supply Shares and Impacts: Reference Energy System
Natural Gas Imports
Natural Gas Production
Wind
New CCGT/GT
Hydro run‐of‐river
Hydro Dam
T&D
Dist. Solar PV
Dist. Solar PV with battery
Grid Expansion
Backstop 1
Backstop 2
Traditional stove
Electric stove
Gas stove
Diesel car
Electric car
Air conditioning
Biomass collection
Diesel import Basktop Air Conditioning
Backstop Transport
Backstop Cooking
Gas distribution
Recharge
Electricity generation from Biomass
Electricity generation from CSP
OSeMOSYS features
emissionsRE integration
Techno-economic
Reserve margin
Start-up costs
Online capacitiesDemand modelling
Subsidies
End-users
Interconnections
Socio-economic
System reliability
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Open Source energy Modelling SYStems « OSeMOSYS »
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BAU: 18684.81 M$-2010 vs. RE: 19015.37 M$-2010
Supply Shares and Impacts: Discounted Costs
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BAU Scenario RE Scenario
Supply Shares and Impacts: Capacities Shares
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BAU Scenario RE Scenario
Supply Shares and Impacts: Electricity Mix
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Supply Shares and Impacts: Job Creation
BAU Optimal Capacity Shares by 2030 RE Optimal Capacity Shares by 2030
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Supply Shares and Impacts: Job Creation
• Train a multi-diciplinary group on « energy-Economy Modeling »
• Develop Energy Scenarii
• Develop energy-climate-Economy insights
• Create an « Energy-Climate-Economy » research & Consulting group
OBJECTIVES
GIZ Bureau Expert International
International Trainers /
International Experts / Scientists
Other Team Members: 2 Engineers
Modeling Group
5 PhD Students + 12 Master Students
Senior Researchers(Multidisciplinary)
Ministries /
Official Institutions(STEG, ANME, ITCEQ, INS, ……)
CapacityBuilding
Consulting / technical Support
Identification of the Research Subjects
Supply of Data
Answer to the ResearchQuestions
Comments / Analysis
Training
Tutoring / Supervision
FormationApprovisionnement en données
Consulting / Scientific Support
Co-Supervision
Co-Supervision
THE GROUP ORGANIZATION
THANK YOU FOR YOUR KIND ATTENTION