Lecure: Peer-to-peer electricity markets: from a generalized formulation to the impact of agents’ risk and other current challenges
Thursday 6 September Fabio Moret from the Technical University of Denmark will give a colloquium.
Location: Instruction room H, 3mE
Guest of: Dr. Ing. S. Grammatico
Title: Peer-to-peer electricity markets: from a generalized formulation to the impact of agents’ risk and other current challenges
Abstract: Organization in electricity markets is evolving from centralized pool-based to decentralized peer-to-peer structures. Within this decentralized framework, agents are expected to negotiate their energy procurement individually while preserving their privacy. To investigate diverse market layouts (e.g. community-based, full peer-to-peer or hybrid), we propose a generalized formulation of decentralized electricity markets. Clearing markets with such characteristics requires consensus based distributed optimization and application of decomposition techniques to accommodate for the complexity due to privacy issues.
Since power generation is mostly based on non-dispatchable distributed energy resources, any proposed decentralized negotiation mechanism needs to account for uncertainties. This translates to rethinking current centralized approaches to risk management. Consequently, we investigate how market participants internalize heterogeneous risk attitudes and we assess the impact of risk on market dynamics. We then analyze the effect of financial contracts, in the form of Arrow-Debreu securities, to the market equilibrium.
Bio: Fabio Moret received a M.Sc. degree in electrical engineering from the University of Padova, Padova, Italy, and a second M.Sc. degree in sustainable energy from the Technical University of Denmark, Kgs. Lyngby, Denmark. He is a Ph.D. student at the Technical University of Denmark, Centre for Electric Power and Energy, Department of Electrical Engineering. His research interests include decentralized electricity markets, distributed negotiation mechanisms, decomposition techniques for optimization problems and applied game theory.
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