Summary
Can we turn the Energy Crisis into an opportunity that advances the clean energy transition? Yes, we can, and we pave the path leading to just and equitable decarbonization. Debates that followed extreme events in Europe and the US pointed to a “wind of change” for the power market design and the price discovery process. Operators are put in the corner, inheriting market schedules that they more and more amend using their judgement, whereas they are also accountable for their out-of-market decisions. The process is inherently sub-optimal and costly! Extreme events may turn annual market revenues into daily energy costs!
I will explore innovative ideas in Generalized Linear Programming and adaptive robust optimization with data-driven uncertainty sets, to support network and reliability related operator decisions, and novel machine learning developments to remove computational barriers while maintaining interpretability. Tackling major obstacles that derive from non-convexities, externalities, and uncertainty (to date open problems), leveraging demand adaptability, and combining optimization with economic theory, I will break new ground by (i) defining efficient, adaptive, and robust prices that minimize the gap between market outcomes and operator decisions, and (ii) designing innovative protection mechanisms that dynamically delineate the (blurred) boundaries between systems and markets encoding crisis resilience and shielding from catastrophic financial impacts.
CRISP will break the barriers that have restricted power markets to “half-markets” for more than 30 years tapping adaptable demand and set the foundations for efficient scheduling and correct investment signals in innovation, infrastructure, resource adequacy, and sustainability. The theoretical and computational breakthroughs will benefit a wide class of problems (scheduling, routing, and others) and are also relevant to integrated grids and systems hampered similarly by climate change and extreme events.
I will explore innovative ideas in Generalized Linear Programming and adaptive robust optimization with data-driven uncertainty sets, to support network and reliability related operator decisions, and novel machine learning developments to remove computational barriers while maintaining interpretability. Tackling major obstacles that derive from non-convexities, externalities, and uncertainty (to date open problems), leveraging demand adaptability, and combining optimization with economic theory, I will break new ground by (i) defining efficient, adaptive, and robust prices that minimize the gap between market outcomes and operator decisions, and (ii) designing innovative protection mechanisms that dynamically delineate the (blurred) boundaries between systems and markets encoding crisis resilience and shielding from catastrophic financial impacts.
CRISP will break the barriers that have restricted power markets to “half-markets” for more than 30 years tapping adaptable demand and set the foundations for efficient scheduling and correct investment signals in innovation, infrastructure, resource adequacy, and sustainability. The theoretical and computational breakthroughs will benefit a wide class of problems (scheduling, routing, and others) and are also relevant to integrated grids and systems hampered similarly by climate change and extreme events.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101165616 |
| Start date: | 01-12-2024 |
| End date: | 30-11-2029 |
| Total budget - Public funding: | 1 499 490,00 Euro - 1 499 490,00 Euro |
Cordis data
Original description
Can we turn the Energy Crisis into an opportunity that advances the clean energy transition? Yes, we can, and we pave the path leading to just and equitable decarbonization. Debates that followed extreme events in Europe and the US pointed to a “wind of change” for the power market design and the price discovery process. Operators are put in the corner, inheriting market schedules that they more and more amend using their judgement, whereas they are also accountable for their out-of-market decisions. The process is inherently sub-optimal and costly! Extreme events may turn annual market revenues into daily energy costs!I will explore innovative ideas in Generalized Linear Programming and adaptive robust optimization with data-driven uncertainty sets, to support network and reliability related operator decisions, and novel machine learning developments to remove computational barriers while maintaining interpretability. Tackling major obstacles that derive from non-convexities, externalities, and uncertainty (to date open problems), leveraging demand adaptability, and combining optimization with economic theory, I will break new ground by (i) defining efficient, adaptive, and robust prices that minimize the gap between market outcomes and operator decisions, and (ii) designing innovative protection mechanisms that dynamically delineate the (blurred) boundaries between systems and markets encoding crisis resilience and shielding from catastrophic financial impacts.
CRISP will break the barriers that have restricted power markets to “half-markets” for more than 30 years tapping adaptable demand and set the foundations for efficient scheduling and correct investment signals in innovation, infrastructure, resource adequacy, and sustainability. The theoretical and computational breakthroughs will benefit a wide class of problems (scheduling, routing, and others) and are also relevant to integrated grids and systems hampered similarly by climate change and extreme events.
Status
SIGNEDCall topic
ERC-2024-STGUpdate Date
24-11-2024
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