Synchronization Games in P2P Energy Trading

Olga Saukh, Franz Papst, Sergii Saukh

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

The rise of distributed energy generation technologies along with grid constraints, and conventional non-consumer centric business models, is leading many to explore alternative configurations of the energy system. Particularly popular are peer-to-peer energy trading models in which the role of the energy company is replaced with a trustless transaction layer based on a public blockchain. However, to ensure stable operation of microgrids, an energy company is required to constantly balance supply and demand. In this paper, we study the problem that arises from the conflicting goals of prosumers (to make money) and network operators (to keep the network stable) that have to co-exist in future energy systems. We show that prosumers can play large-scale synchronization games to benefit from the system. If they synchronize their actions to artificially increase energy demand on the market, the resulting power peaks will force the microgrid operator to use backup generation capacities and, as a consequence, contribute to the increased profit margins for prosumers. We study synchronization games from a game-theoretical point of view and argue that even non-cooperative selfish prosumers can learn to play synchronization games independently and enforce undesired outcomes for consumers and the grid. We build a simple model where prosumers independently run Q-learning algorithms to learn their most profitable strategies and show that synchronization games constitute a Nash equilibrium. We discuss implications of our findings and argue the necessity of appropriate mechanism design for stable microgrid operation.
LanguageEnglish
Title of host publicationProceedings of the IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids
Subtitle of host publicationWorkshop on AI in Energy Systems
Number of pages6
StatusPublished - 31 Oct 2018
EventIEEE SmartGridComm: International Conference on Communications, Control, and Computing Technologies for Smart Grids: Workshop on AI in Energy Systems - Comwell Hotel Hvide Hus, Aalborg, Denmark
Duration: 29 Oct 201831 Oct 2018
http://sgc2018.ieee-smartgridcomm.org

Conference

ConferenceIEEE SmartGridComm: International Conference on Communications, Control, and Computing Technologies for Smart Grids
CountryDenmark
CityAalborg
Period29/10/1831/10/18
Internet address

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Synchronization
Industry
Learning algorithms
Profitability

Cite this

Saukh, O., Papst, F., & Saukh, S. (2018). Synchronization Games in P2P Energy Trading. In Proceedings of the IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids: Workshop on AI in Energy Systems

Synchronization Games in P2P Energy Trading. / Saukh, Olga; Papst, Franz; Saukh, Sergii.

Proceedings of the IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids: Workshop on AI in Energy Systems. 2018.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Saukh, O, Papst, F & Saukh, S 2018, Synchronization Games in P2P Energy Trading. in Proceedings of the IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids: Workshop on AI in Energy Systems. IEEE SmartGridComm: International Conference on Communications, Control, and Computing Technologies for Smart Grids, Aalborg, Denmark, 29/10/18.
Saukh O, Papst F, Saukh S. Synchronization Games in P2P Energy Trading. In Proceedings of the IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids: Workshop on AI in Energy Systems. 2018.
Saukh, Olga ; Papst, Franz ; Saukh, Sergii. / Synchronization Games in P2P Energy Trading. Proceedings of the IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids: Workshop on AI in Energy Systems. 2018.
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