70th ETSAP meeting
Modelling the energy demand in Spain with MED-Pro
CIEMAT (Madrid), 17 November 2016
Carlos Garcia BarqueroHead Department of Planning and Studies
IDAE
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IDAE´s experience on energy simulation and prospective studies
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• Methodology: EUROSTAT (ESR) and IEA Energy Statistics
• Prospects:
End-use and RES: Monitoring and prospects of energy consumption bysector (main end-use subsectors in industry, transport, services andhouseholds) and fuel (coal, oil, gas, nuclear, electricity, biofuels, biomass,solar, wind and H2);
Energy demand forecasts: in the framework of medium and long-termenergy prospective national projects;
• Tools: country adaptation and application of energy models, i.e. MEDEE-EUR,MURE, EFOM-ENV, POLES and MED-Pro for Spain; MEDEE-SUD for Algeriaand Morocco
• Carried out under the framework of the project “Sectoral studies on energy monitoring (SES)”
• Recent studies:
o Industry: cement, glass, steel alloyso Transport: urban buses, freight transport, private carso Services: shopping centers, hotels, hospitals, private offices, universities,
institutes and public schools; heat pumpso Residential: electricity and heating & cooling EUROSTAT´s surveys, SPAHOUSEC
studies o Renewable: biomass and solar thermal panels
End-use and RES studies
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•Final energy demand long-term simulation:
- End-use energy model developed from MEDEE suite, with focus on energy efficiency &technological improvement
- Submodels: Industry, Transport, Residential, Services and Agriculture
- Disaggregation by sub-sectors, end-uses and intensive processes
- Wide level of insight: 450 equations and 900 variables
• Advantages:
- Flexibility at structure and disaggregation level
- Technological progress and socio-economic changes are main drivers
- Energy efficiency, saving potential and fuel substitution are also considered
- Long-term uncertainty is approached by means of alternative scenarios
• Limitations:
- Significant amount of data for the base year
- Coherent assumptions for the establishment of scenarios are required
• Simulation period:
- Base year, calibration year and up to 30 forecast years for simulation
MED-Pro: Energy Demand Model
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Structure of the model
INPUTS RESULTS
ANNUAL DATA OPTIONAL SUBMODELS SOCIOECONOMICl Socioeconomics Basic Disaggregation Desagregación sectorial F Industrial production
F GDP Macroeconomic consistence F Stock of vehicles
F Population Industry F Trade
F Households • Thermal uses • Industrial Subsectors • Energy Intensive Products F Stock of dwellings
F Equipment ownership • Electric uses • Construction • Steel F Equipment
F Employment • Non energy uses • Private vehicles by types
Transport
l Technicals • ŸPrivate vehicles • Motocycles
F Fuel efficiencies • Public passengers SPECIFIC CONSUMPTION F Specific consumptions Road F Intensive Products
Rail F Vehicles
Air F End uses- Household sector
PARAMETERS • ŸGoods F Tertiary Dwellings
Road F Elasticities Rail F Logistic coeficients Sea
F Conversion coeficients • International sea DEMAND BY ENERGY SOURCE TYPEAgriculture F by industrial branches
• Tractores • Energy Intensive Porducts F by transport mode and type of vehicle
SCENARIOS • Pumping F Electrical appliances
l Socioeconomics • ŸFishing boats F End uses- Tertiary sector
F Population • Thermal uses F by agriculture uses
F Economic growth • Electric uses
F Industrila growth Households
F Energy prices • Cooking and other thermal uses • Urban by zone • Heat Water
F Productivity • ŸLighting and other electrical consumptions • Rural by zone • ŸHeating
• ŸUrban by social class • ŸAir conditioning INDICATORSl Technicals • ŸRural by social class • Electrical apllications F Energy Intensities F Efficiency improvements Tertiary F Elasticities
F Technology penetration • Thermal uses • ŸSubsectors • ŸPublic lighting F Energy expenses
F Market trends • Electric uses F CO2 emissions
• Informal sector
• Public passengers
by bus size
• Freight by truck size
DEMAND PROJECTION MODULE
STRUCTURE
Modelling with Med-Pro: main sources of information and tasks
Tasks
• In-depth analysis of energy consumptionfor the base year
• Research and assessment of sectoralenergy perspectives
• Sectoral disaggregation and preparationof sub-models within the tool
•Coherent assumptions for theestablishment of scenarios and assignmentof variables for each sector
•Econometric contrast of electricity for thewhole simulation period
Sources
• IDAE´s own sources (EE & REStechnologies)
• IDAE´s energy monitoring and technologydeployment studies
• Statistics and socio-economic forecastsfrom public and private institutions
• Medium and long-term trends providedSpanish Government, European Commissionand other international bodies (OCDE, UN,etc.)
• Manufacturer associations and privatecompanies of the energy sector
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Example of global scenarios for MED-ProReference• Globalization, economic development and growth in world trade• Similar present economic and energy trends• XX% annual GDP growth for 2000-2030• EU energy market progress• Oil prices from YY $05/bbl in 2000 to ZZ $05/bbl in 2030. Gas prices …• Light decrease of energy taxes
Lower growth
• Downturn, with lower economic growth (GDP) and social integration
• High increase of oil prices and subsequent oscillations
• Similar evolution of energy taxes
Hight reduction of ENV impacts
• Greater economic growth (GDP), lower during first years
• Substantial progress in climate change EU policy, limited emissions of GHG in the energy sector
• Lower environmental impacts, targeted fiscal policy and harmonization at EU level
• Similar increase of oil prices, greater for gas and lower for coal
• Significant increase of energy taxes for end-users, internalization of externalcosts and environmental benefits
Greater growth
• Greater economic growth (GDP), in particular during first years
• Intensive market, wide economic integration and lower public participation in the economic growth
• Similar evolution of energy prices
• Decrease of energy taxes
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Reference Scenario: main inputs
0
10
20
30
40
50
60
1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020
$95/b
arr
il
Year
Oil international prices
30,0
32,0
34,0
36,0
38,0
40,0
1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020
Millo
ne
s
Year
Evolution of Population
Source: INE
25303540455055606570758085
1980 1985 1990 1995 2000 2005 2010 2015 2020
Billo
ne
s p
tas. 1
986
Year
Evolution of GDP
Source: MEH
0
50
100
150
200
250
1980 1985 1990 1995 2000 2005 2010 2015 2020
Bas
e 1
995=100
Evolution of GDP by sector
Agricultura Industria Servicios
Source: MEH
Source: EC
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Reference Scenario: main results
1990 1995 2000 2005 2010 2015 2020
Final consumption (ktoe) 64.961 72.026 79.916 87.726 92.413 98.063 103.715
Final Energy Intensity (tep/Mpta 86) 1,66 1,73 1,65 1,62 1,54 1,44 1,32
0
20000
40000
60000
80000
100000
120000
0,0
0,2
0,4
0,6
0,8
1,0
1,2
1,4
1,6
1,8
2,0
1980 1985 1990 1995 2000 2005 2010 2015 2020
kto
e
(toe/M
pta
)
Evolution of final energy consumption and energy intensity in Spain
Energía (ktep) Intensidad total (tep/Mpta 86)
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Reference Scenario: results for household sector
0,00
0,05
0,10
0,15
0,20
0,25
0,30
0
2000
4000
6000
8000
10000
12000
14000
1980 1985 1990 1995 2000 2005 2010 2015 2020
Intensidad energética en el sector residencial: consumo de energía sobre PIB (tep/106pta)
Consumo energético de los hogares
Intensidad total
Gasóleo11,1%
GLP22,6%
Gas natural10,1%
Electricidad32,1%
Solar0,2%
2000
Combustibles sólidos24,0 %
Gasóleo11,2%
GLP17,0%
Gas natural17,2%
Electricidad36,0%
Solar2,0%
2010
Combustibles sólidos16,7 %
Gasóleo10,9%
GLP15,4%
Gas natural20,9%
Electricidad36,6%
Solar2,2%
2020
Combustibles sólidos13,9 %
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1980 1985 1990 1995 2000 2005 2010 2015 2020
Intensidad energética en el sector residencial: consumo por hogar (tep/hogar)
Consumo energético por hogar Consumo eléctrico por hogar
Consumo no eléctrico por hogar
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• MEDPro (EEf)
• REMap (RES)• TIMES (EMod)
• ECf
• RESc-b
• ECp
• RESc-b
SINERGIA
MINETUR
IDAESGPES/CIEMAT
Results Results
Base Input
Input
Contrast
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Models interaction under SINERGIA (so far)
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