Energy efficiency and renewable
energy modelling with ETSAP TIAM -
challenges, solutions, and
opportunities
Jay Gregg, Ole...
Motivation for Modeling
• Sustainable Energy for All (SE4ALL)
o Double energy efficiency (reduce global energy
intensity o...
Method
Changes in:
Renewable Energy Profile
Energy Consumption,
GHG Emissions
Costs
Alternative
Scenario
-RenewableEnergy ...
Scenarios
Scenario
Regional
EIIR
Global
EIIR
1.3%
Global
EIIR
2.6%
Regional
RE IRENA
Ref
Regional
RE IRENA
REMap
Global RE...
Scenario Details
• Ref:
o -1.3% CAGR in Primary Energy Intensity of GDP
o RE IRENA reference (IRENA, 2016)
• EE:
o -2.6% C...
Energy Intensity, by Scenario
SE4ALL EE Objective
SE4ALL Reference
SE4ALL RE Objective
(~ ½ way to SE4ALL EE Objective)
SE...
Renewable Energy, by Scenario
SE4ALL RE Objective
IRENA Reference
IRENA REmap
SE4ALL EE Objective
(~ ½ way to SE4ALL RE Ob...
Emissions by Scenario
Emissions Versus Investment Costs
NPV = Net Present Value of investments 2010-2030, 5% discounting
Modelling Conclusions
• Achieving the SE4ALL EE objective on its own promotes
RE deployment half way to the SE4ALL RE obje...
… challenges, solutions, and opportunities
… challenges, solutions, and
opportunities
1. Model Issues
2. Model Enhancements
3. Data Issues
4. Results Issues
1. Model Issues
1.1. Model errors
1000+ errors. Some of the errors were caused by
new developments not always fitting the
existing structu...
1.2. Negative Production
-40.0
-20.0
0.0
20.0
40.0
60.0
80.0
2010 2015 2020 2025 2030
EJ/year
Former Soviet Union Primary ...
1.3. Reporting
Reporting: subsector totals do not match regional
totals; some fuels at the subsector level are not
reporte...
2. Model Enhancements
2.1. RE constraints
RE constraints on final energy- not straightforward to create a constraint on
final energy that accoun...
2.2. Building Envelop
• How to handle efficiency improvements in the
building sector?
– Residential Heating
– Residential ...
2.2. Building Envelop
2.2. Building
Envelop
• Potential is
maximized in all
scenarios-
• Cheap solution
• How to institute
PESTLEG barriers?
(op...
2.3. Traditional Biomass
• Traditional Biomass not separate from modern
biomass
• Proposed Solution: disaggregate in devel...
2.3. Traditional Biomass
3. Data Issues
3.1. Socioeconomic Data
Socio-economic data: 2005 base is dated,
especially after the recession. HOU is crudely
estimated,...
3.1. Socioeconomic Data
Default Values Adjusted Values (Tekcarta Data)
0
1
2
3
4
5
6
2005 2010 2015 2020 2025 2030
Numbero...
3.2. Technology Data
3.2.1. Technology data are dated and some subsectors (end-use demands) do not appear in all regions
(...
4. Results Issues
Results are often counter-intuitive, or not in line
with other findings in the literature
Proposed solut...
Conclusions
• Main strengths: very detailed representation of
technologies
• Main weaknesses: very detailed representation...
Upcoming SlideShare
Loading in …5
×

Energy efficiency and renewable energy modelling with ETSAP TIAM - challenges, opportunities, and solutions

11,660 views

Published on

Energy efficiency and renewable energy modelling with ETSAP TIAM - challenges, opportunities, and solutions

Published in: Data & Analytics
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
11,660
On SlideShare
0
From Embeds
0
Number of Embeds
9,946
Actions
Shares
0
Downloads
15
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Energy efficiency and renewable energy modelling with ETSAP TIAM - challenges, opportunities, and solutions

  1. 1. Energy efficiency and renewable energy modelling with ETSAP TIAM - challenges, solutions, and opportunities Jay Gregg, Olexandr Balyk, Cristian Hernán Cabrera Pérez Systems Analysis, Technical University of Denmark jsgr@dtu.dk
  2. 2. Motivation for Modeling • Sustainable Energy for All (SE4ALL) o Double energy efficiency (reduce global energy intensity of GDP by half) o Double global renewable energy share (18 to 36%) o Transition away from traditional biomass and ensure electricity access to everyone o …by 2030 • Reduce CO2 emissions, prevent >2°C warming GDP = Gross Domestic Product
  3. 3. Method Changes in: Renewable Energy Profile Energy Consumption, GHG Emissions Costs Alternative Scenario -RenewableEnergy Targets for 2010-2030 -Energy Intensity Targets for 2010-2030 -Increased Energy Access & Phase-out Traditional Biomass Current: -Carbonprice -RenewableEnergy Profile -Energy efficiency trends -Traditional biomass use -Technology profiles ETSAP-TIAM Reference Scenario Assessment of Regional Potentials Sector &Subsector Potentials ETSAP-TIAM
  4. 4. Scenarios Scenario Regional EIIR Global EIIR 1.3% Global EIIR 2.6% Regional RE IRENA Ref Regional RE IRENA REMap Global RE Doubling SE4ALL Energy Access i. Base ii. RefRegional fixed fixed iii. RefGlobal fixed fixed iv. RE fixed fixed v. EE fixed fixed vi. EE&RE fixed fixed vii. EE&RE&EA fixed fixed included viii. EEfree&REflex min ix. EEflex&REfree min x. EEflex&REflex min min xi. EEflex&REflex&EA min min included EIIR = Energy Intensity Improvement Rate IRENA = International Renewable Energy Agency RE = Renewable Energy SE4ALL = United Nations Sustainable Energy for All Initiative
  5. 5. Scenario Details • Ref: o -1.3% CAGR in Primary Energy Intensity of GDP o RE IRENA reference (IRENA, 2016) • EE: o -2.6% CAGR in Energy Intensity • RE: o IRENA REmap 2030 Realistic Potential (IRENA, 2016) o SE4ALL RE doubling: 36% global RE share of Final Energy (including traditional biomass) • EA: o Complete phase out of traditional biomass & at least 750 kWh/year/capita electricity consumption in all regions IRENA = International Renewable Energy Agency EE = Energy Efficiency, measured in Energy Intensity of GDP RE = Renewable Energy EA = Energy Access CAGR = Compound Annual Growth Rate SE4ALL = United Nations Sustainable Energy for All Initiative
  6. 6. Energy Intensity, by Scenario SE4ALL EE Objective SE4ALL Reference SE4ALL RE Objective (~ ½ way to SE4ALL EE Objective) SE4ALL = United Nations Sustainable Energy for All Initiative EE = Energy Efficiency, measured in energy intensity of GDP RE = Renewable Energy
  7. 7. Renewable Energy, by Scenario SE4ALL RE Objective IRENA Reference IRENA REmap SE4ALL EE Objective (~ ½ way to SE4ALL RE Objective) SE4ALL = United Nations Sustainable Energy for All Initiative EE = Energy Efficiency, measured in energy intensity of GDP RE = Renewable Energy
  8. 8. Emissions by Scenario
  9. 9. Emissions Versus Investment Costs NPV = Net Present Value of investments 2010-2030, 5% discounting
  10. 10. Modelling Conclusions • Achieving the SE4ALL EE objective on its own promotes RE deployment half way to the SE4ALL RE objective. • …and vice versa • Taken alone, the EE objective reduces emissions more than the RE objective, but is also more expensive. Both together reduce more than either alone, for only slightly more cost. i.e., it is cost effective to pursue EE and RE together. • Achieving the SE4ALL objectives is compatible with keeping global warming under 2° (between 50 and 66% probability), but additional measures will likely be necessary. EE = Energy Efficiency, measured in energy intensity of GDP RE = Renewable Energy SE4ALL = United Nations Sustainable Energy for All Initiative
  11. 11. … challenges, solutions, and opportunities
  12. 12. … challenges, solutions, and opportunities 1. Model Issues 2. Model Enhancements 3. Data Issues 4. Results Issues
  13. 13. 1. Model Issues
  14. 14. 1.1. Model errors 1000+ errors. Some of the errors were caused by new developments not always fitting the existing structure. Proposed solution: use a GIT version control (done) and a review process (opportunity)
  15. 15. 1.2. Negative Production -40.0 -20.0 0.0 20.0 40.0 60.0 80.0 2010 2015 2020 2025 2030 EJ/year Former Soviet Union Primary Energy Production Renewable except hydro and biomass Hydro Biomass Traditional Biomass Nuclear Gas Oil Coal Erratic behavior of natural gas in FSU. Dramatic shifts, negative production of Oil. Proposed solution: Caused by synthetic fuels; these were disabled them to get rid of the negative value for production-export (done). Coal 5.3 5.1 5.8 6.3 8.0 Oil 5.2 5.7 6.0 -29.6 -33.0 Gas 18.2 19.2 18.3 75.5 82.0 Nuclear 0.7 0.6 2.4 3.0 3.6 Traditional Biomass 0.0 0.0 0.0 0.0 0.0 Biomass 0.7 0.7 0.8 0.8 0.8 Hydro 0.9 1.0 1.2 1.6 1.6 Renewables 0.0 0.0 0.0 0.2 0.2
  16. 16. 1.3. Reporting Reporting: subsector totals do not match regional totals; some fuels at the subsector level are not reported at the sector level. Proposed solution: The difference is likely due to non-fuel use. Sort out and redefine queries (in process) Total global final energy (EJ) SE4ALL EEflex & REflex 2010 2030 by region 325.82 444.02 by fuel 325.82 444.02 by scenario 325.82 444.02 by sector 325.82 444.02 by sub-sector 365.13 549.40
  17. 17. 2. Model Enhancements
  18. 18. 2.1. RE constraints RE constraints on final energy- not straightforward to create a constraint on final energy that accounts for upsteam consumption. Some post processing calculations are necessary to account for line losses. Proposed Solution: Create spreadsheet template to set constraints (done) but this requires post-processing (opportunity to simplify) Region Electricity 2010 2015 2020 2025 2030 AFR Central 0.84 0.85 0.85 0.86 0.87 AUS Central 0.86 0.86 0.87 0.87 0.87 CAN Central 0.89 0.89 0.89 0.89 0.89 CHI Central 0.95 0.95 0.94 0.94 0.94 CSA Central 0.81 0.82 0.83 0.84 0.85 EEU Central 0.82 0.82 0.83 0.84 0.85 FSU Central 0.81 0.82 0.83 0.84 0.85 IND Central 0.68 0.72 0.76 0.79 0.83 JPN Central 0.90 0.90 0.90 0.90 0.90 MEA Central 0.81 0.82 0.82 0.83 0.83 MEX Central 0.79 0.80 0.82 0.83 0.85 ODA Central 0.85 0.85 0.85 0.86 0.86 SKO Central 0.91 0.91 0.91 0.91 0.91 USA Central 0.89 0.89 0.89 0.89 0.89 WEU Central 0.88 0.88 0.88 0.88 0.88
  19. 19. 2.2. Building Envelop • How to handle efficiency improvements in the building sector? – Residential Heating – Residential Cooling – Commercial Heating – Commercial Cooling • Investment  Some service demand met – No fuel consumption or fuel costs • Air seal, walls, floor, roof (done), and deep retrofit (opportunity)
  20. 20. 2.2. Building Envelop
  21. 21. 2.2. Building Envelop • Potential is maximized in all scenarios- • Cheap solution • How to institute PESTLEG barriers? (opportunity) PESTLEG = political, economic, social, technological, legal, environmental, and governmental
  22. 22. 2.3. Traditional Biomass • Traditional Biomass not separate from modern biomass • Proposed Solution: disaggregate in developing regions (done) create pathways for phase-out (done). Potentials estimated from GCAM. More dynamic modeling could be possible in theory (opportunity)
  23. 23. 2.3. Traditional Biomass
  24. 24. 3. Data Issues
  25. 25. 3.1. Socioeconomic Data Socio-economic data: 2005 base is dated, especially after the recession. HOU is crudely estimated, and doesn’t appear to be based on any background data. Elasticities are crudely estimated (not much data available). Proposed solution: Update with best available data sources (done), update elasticities (opportunity)
  26. 26. 3.1. Socioeconomic Data Default Values Adjusted Values (Tekcarta Data) 0 1 2 3 4 5 6 2005 2010 2015 2020 2025 2030 Numberofpeople AFR AUS CAN CHI CSA EEU FSU IND JPN MEA MEX ODA SKO USA WEU Global 0 1 2 3 4 5 6 2005 2010 2015 2020 2025 2030 Numberofpeople AFR AUS CAN CHI CSA EEU FSU IND JPN MEA MEX ODA SKO USA WEU Global e.g. number of people per household
  27. 27. 3.2. Technology Data 3.2.1. Technology data are dated and some subsectors (end-use demands) do not appear in all regions (e.g. clothes drying in China) Proposed solutions: update tech database (opportunity) and demands (partly done). 3.2.2. Overly ambitious base scenario- Optimistic prices/potential for renewable energy resources. Proposed solution: revisit assumptions about RE. Create adjustable mechanism/parameters for social barriers (opportunity- instead, we used constraints) 3.3.3. Naming irregularities. “Natural Gas” is used for industry and RESNGA and COMNGA are used for residential and commercial; Lubricants and Distillates are ambiguously named according to sector (i.e., need to rename to Lubricants (TRA) vs. Lubricants (IND) and Distillates (TRA) vs. Distillates (IND)); What is IPIS? Proposed solution: Rename tech and fuel in a standard way, create a legend online (opportunity… task)
  28. 28. 4. Results Issues Results are often counter-intuitive, or not in line with other findings in the literature Proposed solution: This could be good or bad; important to revisit the input assumptions (opportunity) and model structure (opportunity) in order to justify the findings.
  29. 29. Conclusions • Main strengths: very detailed representation of technologies • Main weaknesses: very detailed representation of technologies • A lot of maintenance work is needed to keep ETSAP-TIAM relevant. • Where do we want to go with ETSAP-TIAM? • What are the main upcoming scientific questions that ETSAP-TIAM is poised to address? (e.g., Sustainable development?)

×