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Loss Allocation in Joint Transmission and Distribution Peer-to-Peer Markets

Large deployment of distribute energy resources and the increasing awareness of end-users towards their energy procurement are challenging current practices of electricity markets. A change of paradigm, from a top-down hierarchical approach to a more decentralized framework, has been recently researched, with market structures relying on multi-bilateral trades among market participants. In order to guarantee feasibility in power system operation, it is crucial to rethink the interaction with system operators and the way operational costs are shared in such decentralized markets. We propose here to include system operators, both at transmission and distribution level, as active actors of the market, accounting for power grid constraints and line losses. Moreover, to avoid market outcomes that discriminate agents for their geographical location, we analyze loss allocation policies and their impact on market outcomes and prices.
Submitted to "IEEE Transactions on Power Systems" on January 15, 2020 - Revised on May 6, 2020 and on August 6, 2020 - Accepted on September 13, 2020
- CY Cergy Paris University France
- Technical University of Denmark Denmark
- Université de Rennes 1 France
- Conservatoire national des arts et métiers France
- École Normale Supérieure France
Optimal power flow, [SPI] Engineering Sciences [physics], Network charges, Peer-to-peer trading ,loss allocation, optimal power flow, network charges, Loss allocation, Optimization and Control (math.OC), FOS: Mathematics, Peer-to-peer trading, Mathematics - Optimization and Control
Optimal power flow, [SPI] Engineering Sciences [physics], Network charges, Peer-to-peer trading ,loss allocation, optimal power flow, network charges, Loss allocation, Optimization and Control (math.OC), FOS: Mathematics, Peer-to-peer trading, Mathematics - Optimization and Control
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).28 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
