Published December 2023
| v1
Conference Paper
Pricing Uncertainty in Stochastic Multi-Stage Electricity Markets
Abstract
This work proposes a pricing mechanism for multi-stage electricity markets that does not explicitly depend on the choice of dispatch procedure or optimization method. Our approach is applicable to a wide range of methodologies for the economic dispatch of power systems under uncertainty, including multi-interval dispatch, multi-settlement markets, scenario-based dispatch, and chance-constrained dispatch policies. We prove that our pricing scheme provides both ex-ante and expost dispatch-following incentives by simultaneously supporting per-stage and ex-post competitive equilibria. In numerical experiments on a ramp-constrained test system, we demonstrate the benefits of scheduling under uncertainty and show how our price decomposes into components corresponding to energy, intertemporal coupling, and uncertainty.
Copyright and License
© 2023 IEEE.
Acknowledgement
The authors thank Subhonmesh Bose (UIUC), Nathan Dahlin (UIUC), and Feng Zhao (ISO NE) for insightful conversations. The authors acknowledge support from NSF Graduate Research Fellowship (DGE-1745301), NSF grants CNS-2146814, CPS-2136197, CNS-2106403, NGSDI-2105648, ECCS 1931662, ECCS 1932611, and Caltech Resnick Sustainability Institute and S2I grants.
Additional details
- National Science Foundation
- NSF Graduate Research Fellowship DGE-1745301
- National Science Foundation
- CNS-2146814
- National Science Foundation
- ECCS-2136197
- National Science Foundation
- CNS-2106403
- National Science Foundation
- CNS-2105648
- National Science Foundation
- ECCS-1931662
- National Science Foundation
- ECCS-1932611
- Resnick Sustainability Institute
- California Institute of Technology
- Calter Center for Sensing to Intelligence
- Accepted
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2023-12-13published print
- Caltech groups
- Resnick Sustainability Institute, Caltech Center for Sensing to Intelligence (S2I)