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Integrating probabilistic electricity security of supply
assessment into long-term energy planning exercises:
an automated-data-linking modeling approach.
Nadia MAรZI
MINES ParisTech, PSL
Research University,
CMA - Center for Applied
Mathematics.
,The 74rd Semi-Annual ETSAP workshop
Stuttgart 7-9 November 2018
Jeanโˆ’Yves BOURMAUD
Marion LI
Rรฉseau de Transport
dโ€™Electricitรฉ,
Yacine ALIMOU
2
โ€ข Motivations:
โ€“ Suitability of existing tools and methodologies for long-term energy planning
โ€“ More integrated approach for transition planning
โ€ข Objectives:
โ€“ Test the ability of a long term model (TIMES) to address short-term reliability
issues (tackled by ANTARES)
โ€“ Develop a methodological framework to ensure:
๏ƒผ Cost-effective future plan
๏ƒผ Security of supply requirements
โ€ข Target audience:
โ€“ Long-term energy planners
โ€“ Power system operators
Motivation and scope
3
Energy system model: TIMES-FR
โ€ข TIMES-FR: Energy system model for France developed by CMA-Mines ParisTech
โ€ข Minimizes total discounted energy system cost ๏ƒจ Investment trajectory
โ€ข Representation of the power sector within TIMES
4
Energy system model: TIMES-FR
โ€ข Time horizon of study 2013-2050, split into 84 annual time-slices
5
ANTARES: a probabilistic tool for power systems
โ€ข Probabilistic simulator developed by RTE
โ€ข Open source model since July-2018
โ€ข Balance between supply and demand for the electrical interconnected system
References
6
ANTARES main results
Exchanges between neighbors are
possible, within the limits of the
network
Foreachscenariostudied,ANTARES
optimizestheunitcommitmentinorderto
satisfythedemandatthelowestcost
Loss of load
7
Approach: an automated-data-linking model
๏ฑ The linking model is supported by the development of several R packages
ANTARES-FRTIMES-FR
Bridge.1
Feed-back loop
Global outputs
LOLE criterion
*Init: Initialization
Global input database
ANTARES input
Fixed
TIMES input
Fixed
Init* UpdatedUpdated
Bridge.2
โ€ข Linking model = Databases + steps
Ensuring consistency: Common input data
8
โ€ข VRE load factors(correlation with load)
โ€ข Technical โ€“economic parameters
โ€ข 2030, TIMES power generation portfolio
9
Power dispatch decisions: hourly vs time-slices
Dispatchable
๏ฑ An over-estimation of the residual load duration curve(and its variability) in TIMES
leads to over-use of semi-base technologies(coal)
Non-dispatchable
10
Shortfall risk analysis: LOLE adequacy metric
๏ฑ The power generation mix proposed by TIMES for 2030, does not respect the adequacy
requirements (LOLE < 3hours)
๐‘š๐‘’๐‘Ž๐‘› ๐ฟ๐‘‚๐ฟ๐ท = ๐Ÿ๐Ÿ๐Ÿ•๐’‰,
๐‘ ๐‘ก๐‘‘ ๐ฟ๐‘‚๐ฟ๐ท = 129โ„Ž,
๐‘š๐‘Ž๐‘ฅ๐‘– ๐ฟ๐‘‚๐ฟ๐ท = ๐Ÿ•๐Ÿ”๐Ÿ๐’‰.
11
Why we have a shortage of supply?
๏ฑ Energy balance (TIMES) versus power balance (ANTARES)
๏ฑ Shortage hours occur at the peak of residual load = low VRE power output
๏ฑ TIMES underestimates the impact of:
๏ฑ Variability of VRE (climatic conditions)
๏ฑ Operational constraints of the thermal fleet
๏ƒ˜ Generation capacity is insufficient to satisfy demand
Example of the median scenario
Chosen lever: capacity credit values
12
Taming TIMES: capacity credit updating
๏ฑ Updating the capacity credit values over installed technologies has the potential to ensure
the LOLE criterion (LOLE <= 3 hours)
๐’Ž๐’†๐’‚๐’ ๐‘ณ๐‘ถ๐‘ณ๐‘ซ = ๐Ÿ๐Ÿ๐Ÿ• ๐’‰
๐’Ž๐’†๐’‚๐’ ๐‘ณ๐‘ถ๐‘ณ๐‘ซ = ๐Ÿ. ๐Ÿ”๐Ÿ’ ๐’‰(< ๐Ÿ‘ ๐’‰),
13
Generation power mix: optimality question?
๏ฑ The last iterations activated to satisfy the LOLE criterion require a huge investment
๏ฑ Initial underestimation of investment cost : 28%
Base year
operating cost +
unsupplied energy cost
+ spilled energy cost
14
โ€ข What is new?
โ€“ Probabilistic adequacy assessment methodology
โ€“ Automated linking approach in contrast with soft-linking approach
โ€“ Bi-directional linking exercise(feed-back loops)
โ€ข What are the main caveats?
โ€“ Electrical interconnections not taken into account
โ€“ Need to assess adequacy for all milestone-years, and not only 2030
โ€ข Key messages
โ€“ The capacity mix proposed by TIMES for 2030 does not meet electricity security of
supply requirements
โ€“ Feedback loops between TIMES and ANTARES have the potential to ensure
sufficient firm capacity(supply) to meet demand
โ€“ The methodological framework proposed introduces the electricity security of
supply issue into long-term energy planning exercises
Concluding thoughts
The 74rd Semi-Annual ETSAP workshop
Stuttgart 7-9 November 2018
For further information
yacine.alimou@mines-paristech.fr
nadia.maizi@mines-paristech.fr
jean-yves.bourmaud@rte-france.com
marion.li@rte-france.com

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Integrating probabilistic assessment of security of electricity supply into long-term energy planning exercises: an automated-data-linking modeling approach

  • 1. Integrating probabilistic electricity security of supply assessment into long-term energy planning exercises: an automated-data-linking modeling approach. Nadia MAรZI MINES ParisTech, PSL Research University, CMA - Center for Applied Mathematics. ,The 74rd Semi-Annual ETSAP workshop Stuttgart 7-9 November 2018 Jeanโˆ’Yves BOURMAUD Marion LI Rรฉseau de Transport dโ€™Electricitรฉ, Yacine ALIMOU
  • 2. 2 โ€ข Motivations: โ€“ Suitability of existing tools and methodologies for long-term energy planning โ€“ More integrated approach for transition planning โ€ข Objectives: โ€“ Test the ability of a long term model (TIMES) to address short-term reliability issues (tackled by ANTARES) โ€“ Develop a methodological framework to ensure: ๏ƒผ Cost-effective future plan ๏ƒผ Security of supply requirements โ€ข Target audience: โ€“ Long-term energy planners โ€“ Power system operators Motivation and scope
  • 3. 3 Energy system model: TIMES-FR โ€ข TIMES-FR: Energy system model for France developed by CMA-Mines ParisTech โ€ข Minimizes total discounted energy system cost ๏ƒจ Investment trajectory โ€ข Representation of the power sector within TIMES
  • 4. 4 Energy system model: TIMES-FR โ€ข Time horizon of study 2013-2050, split into 84 annual time-slices
  • 5. 5 ANTARES: a probabilistic tool for power systems โ€ข Probabilistic simulator developed by RTE โ€ข Open source model since July-2018 โ€ข Balance between supply and demand for the electrical interconnected system References
  • 6. 6 ANTARES main results Exchanges between neighbors are possible, within the limits of the network Foreachscenariostudied,ANTARES optimizestheunitcommitmentinorderto satisfythedemandatthelowestcost Loss of load
  • 7. 7 Approach: an automated-data-linking model ๏ฑ The linking model is supported by the development of several R packages ANTARES-FRTIMES-FR Bridge.1 Feed-back loop Global outputs LOLE criterion *Init: Initialization Global input database ANTARES input Fixed TIMES input Fixed Init* UpdatedUpdated Bridge.2 โ€ข Linking model = Databases + steps
  • 8. Ensuring consistency: Common input data 8 โ€ข VRE load factors(correlation with load) โ€ข Technical โ€“economic parameters โ€ข 2030, TIMES power generation portfolio
  • 9. 9 Power dispatch decisions: hourly vs time-slices Dispatchable ๏ฑ An over-estimation of the residual load duration curve(and its variability) in TIMES leads to over-use of semi-base technologies(coal) Non-dispatchable
  • 10. 10 Shortfall risk analysis: LOLE adequacy metric ๏ฑ The power generation mix proposed by TIMES for 2030, does not respect the adequacy requirements (LOLE < 3hours) ๐‘š๐‘’๐‘Ž๐‘› ๐ฟ๐‘‚๐ฟ๐ท = ๐Ÿ๐Ÿ๐Ÿ•๐’‰, ๐‘ ๐‘ก๐‘‘ ๐ฟ๐‘‚๐ฟ๐ท = 129โ„Ž, ๐‘š๐‘Ž๐‘ฅ๐‘– ๐ฟ๐‘‚๐ฟ๐ท = ๐Ÿ•๐Ÿ”๐Ÿ๐’‰.
  • 11. 11 Why we have a shortage of supply? ๏ฑ Energy balance (TIMES) versus power balance (ANTARES) ๏ฑ Shortage hours occur at the peak of residual load = low VRE power output ๏ฑ TIMES underestimates the impact of: ๏ฑ Variability of VRE (climatic conditions) ๏ฑ Operational constraints of the thermal fleet ๏ƒ˜ Generation capacity is insufficient to satisfy demand Example of the median scenario Chosen lever: capacity credit values
  • 12. 12 Taming TIMES: capacity credit updating ๏ฑ Updating the capacity credit values over installed technologies has the potential to ensure the LOLE criterion (LOLE <= 3 hours) ๐’Ž๐’†๐’‚๐’ ๐‘ณ๐‘ถ๐‘ณ๐‘ซ = ๐Ÿ๐Ÿ๐Ÿ• ๐’‰ ๐’Ž๐’†๐’‚๐’ ๐‘ณ๐‘ถ๐‘ณ๐‘ซ = ๐Ÿ. ๐Ÿ”๐Ÿ’ ๐’‰(< ๐Ÿ‘ ๐’‰),
  • 13. 13 Generation power mix: optimality question? ๏ฑ The last iterations activated to satisfy the LOLE criterion require a huge investment ๏ฑ Initial underestimation of investment cost : 28% Base year operating cost + unsupplied energy cost + spilled energy cost
  • 14. 14 โ€ข What is new? โ€“ Probabilistic adequacy assessment methodology โ€“ Automated linking approach in contrast with soft-linking approach โ€“ Bi-directional linking exercise(feed-back loops) โ€ข What are the main caveats? โ€“ Electrical interconnections not taken into account โ€“ Need to assess adequacy for all milestone-years, and not only 2030 โ€ข Key messages โ€“ The capacity mix proposed by TIMES for 2030 does not meet electricity security of supply requirements โ€“ Feedback loops between TIMES and ANTARES have the potential to ensure sufficient firm capacity(supply) to meet demand โ€“ The methodological framework proposed introduces the electricity security of supply issue into long-term energy planning exercises Concluding thoughts
  • 15. The 74rd Semi-Annual ETSAP workshop Stuttgart 7-9 November 2018 For further information yacine.alimou@mines-paristech.fr nadia.maizi@mines-paristech.fr jean-yves.bourmaud@rte-france.com marion.li@rte-france.com