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Models in local energy planningThe REAM model as an example
2008-04-11
Profu i Gö teborg AB
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431 34 M ö lndal
031 – 720 83 90
031 – 720 83 93
031 – 720 83 99
070 – 564 28 20
www.profu.se
Profu
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Hemsida:
John Johnsson
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Profu is an independent consulting and
research firm founded in 1987. Profu has
18 employees who provide our customers
with qualified analyses and recommen-
dations in the fields of energy, climate,
environment and waste.Pro
fu
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Profu and energy planning
• Participated in 35-40 energy plans/strategies
• Energy planning since 1980, both as researchersand as consultants
• Handbooks in energy planning, Swedish andinternational version
• Model development: KRAM in Skaraborg, 1997REAM for EU (3-nity), 2008
• During 2007-08, finished local projects inHärnösand and Hjo. On-going projects in Habo,Mullsjö and Mark.Participating in Path-to-RES and 3-nity projects
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The planning process
Introduction Orientation Main studyEvaluationDecision
Carrythrough
RapportsFeed-back
Generate two or morescenarios to describe theuncertain future. Energy
flows, technologies,emissions and costs
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The model in the planning process
Generate consistent scenarios for the plan/strategy
• Handle all alternatives on the same basis – both supply technologies and efficiency measures
• Handle the complex energy system, both in detail and to give the comprehensive view of the system
• Handle the influences to the energy system: energy prices, taxes, policy instruments, new technologies, emissions restrictions, …
• Analysis the competition between different solutions
• Follow-up the consequences of the system development
• …
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0
20
40
60
80
100
120
140
160
Reference scenario 2015, -5% 2015, -10%
[GWh]
Biopellets
Wood
Biomass
Light oil
Elc
Operation elc50%
14%
36%
42%
7%
51%
42%
7%
51%
Energy supply – HjoExcl. Industry and Transportation - 2015
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0
1
2
3
4
5
6
Reference scenario 2015, -5% 2015, -10%
[kton]
Single family - Other
District heating
Public Service
Privat service
Multifamily-CC
Single family - CC
Local CO2 emissions - HjoHeating sector - 2015
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Tools in the planning process
• Specialised models such as REAM and KRAM
• Excel
• Other models
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The REAM model
• Developed and used during 2006-2008 in the 3-nity project
• Based on the KRAM model and Profus and IFEsexperiences of local energy planning
• Developed by Profu
• Will be distributed from May 2008
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Result presentation
Calculation algorithm
Model structure
General description
The REAM model
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The REAM model, 1
• Simulation model for local/regional energy planning
• The stationary energy system
• Geographical dimension
• Analyses development of the energy system over time
• Heating, Cooling and Electricity
• Flexible degree of detail
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The REAM model, 2
• Supply technologies as well as energy efficiency measures
• Large scale conversion technologies and small scale
• Includes costs, technologies and emissions
• Analyses the development on a least cost basis
• ReferensEnergySystem-oriented
• Language flexibility, partly unit flexibility
• File-explorer look-alike
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The REAM model
Result presentation
Calculation algorithm
Model structure
General description
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Principal RES
En
ergy
dem
an
dE
nergy
dem
an
d
Ind
ustry
Hou
seh
old
s/Servic
e
Distr
ict h
eat g
rid
Ele
ctric
ity g
rid
Power plant
Combined heat
and power
District heating
plant
Water/Wind/Solar/Wave
Oil
Bio energy
Gas
Oil/Gas
Bio
Coal/CokeCoal/CokeE
ner
gy
dem
an
dE
nergy
dem
an
d
Ind
ustry
Hou
seh
old
s/Servic
e
Distr
ict h
eat g
rid
Ele
ctric
ity g
rid
Power plant
Combined heat
and power
District heating
plant
Water/Wind/Solar/Wave
Oil
Bio energy
Gas
Oil/Gas
Bio
Coal/CokeCoal/Coke
Coo
ling
El a
pp
lian
ces
En
ergy d
eman
d
Hea
ting
En
ergy d
em
an
dE
nerg
y d
eman
d
boilers
Gas
Oil
Bio
Heat pump
Cooling device
Wood stove
Bio
Electricity
Oil
Gas
Coo
ling
El a
pp
lian
ces
En
ergy d
eman
d
Hea
ting
En
ergy d
em
an
dE
nerg
y d
eman
d
boilers
Gas
Oil
Bio
Heat pump
Cooling device
Wood stove
Bio
Electricity
Oil
Gas
Overview level Demand category level
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Energy system / model structure
Urban area
Region Demand technologies
Households
Industry
Primary sector
etc
Community 1
Rural area
Area Demand category
other
Buildings Direct elec. heating
Oil boiler
Wood stove
Cooling unit
Elec. to appliances
District heating
etc.
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Demand category
• Homogeneous demand groups
• Total energy demand (per type)
• Load curves
• Small Scale Technologies (demand technology)
• Extra investments (e.g. central heating and chimney/tank)
• Calculation rate
• VAT
• Emission fee share
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Small scale technologies
• Supply and efficiency technologies
• Heating, cooling and electricity
• The technologies are described by:
• Fuel(s) with maximal share
• Efficiency (per fuel), [%]
• Capacities (residual, upper, lower, fix), [EU/year]
• Grid connections
• Investment, [MU/EU]
• Life length, [years]
• Extra investments, [MU/EU]
• Variable cost (per fuel), [MU/EU]
• Emission coefficients (per fuel), [µg, mg, g /EUfuel]
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Input data for local energy planning
• Energy demand (per sector and geographical area)
• Supply technologies (per sector and geographical area)
• Technical data (e.g. efficiency and capacity)
• Economy (e.g. investments, fixed and variable cost)
• Emissions (e.g. Sulphur, NOx and CO2)
• Energy measures (per sector and geographical area)
• Technical data (e.g. reduction and capacity)
• Economy (e.g. investments, fixed and variable cost)
• Energy carriers• Prices
• Taxes
• Possible restrictions
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Sources to the present situation
Elc. grid statisticsDistrict heating statisticsLocal investigationsTenant associationsMunicipal estate companiesOther estate companiesEnergy companiesTechnical administrationsEnergy advisory serviceConsultantsNational investigationsThe chimney sweeperThe national statistic bureauKey persons
…
ReferenceEnergySystem to
identify unbalances in the numbersand to prepare for the modelanalysis
[GWh]
Oljepanna
Elpanna
Vedpanna
Direktel
VP
Olja/el
Olja/ved
Ved/el
Olja/ved/el
Pelletspanna
Fjärrvärme
VP-direktel
Oljepanna
Elpanna
Direktel
VP
BC olja/pellets
Olja/el
Fjärrvärme
Oljepanna
Elpanna
Direktel
VP
Olja/el
Fjärrvärme
BC olja/pellets
Oljepanna
Elpanna
Direktel
VP
Olja/el
Fjärrvärme
BC olja/pellets
Oljepanna
Elpanna
Vedpanna
Direktel
VP
Blockcentral
Olja/el
Olja/ved
Ved/el
Olja/ved/el
OP-Pulsonex
Pelletspanna
VP-direktel
Småhus i centralorten
0,9
1,6
0,4
15,0
3,6
0,3
4,3
1,0
1,5
0,3
5,7
1,1
1,2
1,8
0,6
15,8
1,4
0,4
6,3
0,4
Flerfamiljshus i
centralorten
2,5
0,0
4,0
1,0
0,0
0,0
11,4
3,3
0,0
4,2
0,4
12,7
0,3
0,0
1,1
0,0
0,0
3,9
0,0
Privata lokaler i
centralorten
0,0
0,0
1,2
0,0
4,3
0,0
0,0
0.1
0,0
0,0
3,9
0,0
Offentliga lokaler i
centralorten
0,0
0,0
0.1
0,0
4,3
1,2
0,5
6,2
8,0
2,4
0,3
0,1
4,8
2,1
0,8
0.0
1,5
1,5
Ej tätort
1,6
0,6
8,8
8,4
1,0
,4
0.0
1,9
0,6
35,7
18,9
5,3
4,9
29.4
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Flexibilities
• Structure
• Detail
• Language
• Monetary units
• Energy units: Watt or Joule
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The REAM presentation
Result presentation
Calculation algorithm
Model structure
General description
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Calculation algorithm – small scale
• The model is driven by the changes in the demand categories (market changes)
• Replacing phased-out capacity, alternative
• Replacing technologies with variable cost > new total cost
• The substitution is made on the basis of lowest total cost
• Alternatively is the development specified by the user
• The calculation of the total cost in a specific period is based on the assumptions only in this period →sequential calculations
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Substituting phased-out capacity
New technology
Energy
TimeT1 T2 T3 T4
ResidualTechnology 2
ResidualTechnology 1
T5
New technology
New technology
New technology
New technology
New technology
Total demand
New technology
New technology
New …
New …
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Supply and efficiency measures• Optimal level for supply vs. efficiency measures on a cost basis
• Supply and efficiency handles in the same way
Total demand, [GWh]
Specific cost, [€/MWh]
Cost curveEfficiency measures
Cost curveSupply technology 1
Tota
l dem
and
Optimal level of efficiency measures
Efficiency package 1
E -
P 2
E –
P 3
E –
P …
E –
P …
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Calculation algorithm – large scale• Dispatch model (total variable cost ranking)
• Alternatively user specified production schedule
Example - District heating production
0
5
10
15
20
25
30
35
40
45
50
Jan Jan Feb Feb Mar Mar Apr Apr May May Jun Jun Jul Jul Aug Aug Sep Sep Oct Oct Nov Nov Dec Dec
[GWh]
Biooil-HP
Biomass-CHP
Municipal Waste-CHP
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The REAM presentation
Result presentation
Calculation algorithm
Model structure
General description
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Result presentation
• Flexible presentation system
• File-explorer look-alike structure
• Tables and diagrams
• Possible to export to Excel, pdf-files, …
• Crystal reports-system
• Results from all levels, geographical areas and energy types
• Energy supply
• Energy production
• Emissions (also external emissions from fuels)
• Costs (fuel costs, taxes, fee costs, fixed and variable cost and capital cost)
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Results in the model
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Extra
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