Xiupeng Chen

Phd student, University of Groningen


Email: [email protected]


Faculty of Science and Engineering

University of Groningen



Optimal Bidding Strategies in Network-Constrained Demand Response: A Distributed Aggregative Game Theoretic Approach


Journal article


Xiupeng Chen, J. Scherpen, N. Monshizadeh
European Control Conference, 2024

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APA   Click to copy
Chen, X., Scherpen, J., & Monshizadeh, N. (2024). Optimal Bidding Strategies in Network-Constrained Demand Response: A Distributed Aggregative Game Theoretic Approach. European Control Conference.


Chicago/Turabian   Click to copy
Chen, Xiupeng, J. Scherpen, and N. Monshizadeh. “Optimal Bidding Strategies in Network-Constrained Demand Response: A Distributed Aggregative Game Theoretic Approach.” European Control Conference (2024).


MLA   Click to copy
Chen, Xiupeng, et al. “Optimal Bidding Strategies in Network-Constrained Demand Response: A Distributed Aggregative Game Theoretic Approach.” European Control Conference, 2024.


BibTeX   Click to copy

@article{xiupeng2024a,
  title = {Optimal Bidding Strategies in Network-Constrained Demand Response: A Distributed Aggregative Game Theoretic Approach},
  year = {2024},
  journal = {European Control Conference},
  author = {Chen, Xiupeng and Scherpen, J. and Monshizadeh, N.}
}

Abstract

Demand response has been a promising solution for accommodating renewable energy in power systems. In this study, we consider a demand response scheme within a distribution network facing an energy supply deficit. The utility company incentivizes load aggregators to adjust their pre-scheduled energy consumption and generation to match the supply. Each aggregator, which represents a group of prosumers, aims to maximize its revenue by bidding strategically in the demand response scheme. Since aggregators act in their own self-interest and their revenues and feasible bids influence one another, we model their competition as a network-constrained aggregative game. This model incorporates power flow constraints to prevent potential line congestion. Given that there are no coordinators and aggregators can only communicate with their neighbours, we introduce a fully distributed generalized Nash equilibrium seeking algorithm to determine the optimal bidding strategies for aggregators in this game. Within this algorithm, only estimates of the aggregate and certain auxiliary variables are communicated among neighbouring aggregators. We demonstrate the convergence of this algorithm by constructing an equivalent iteration using the forward-backward splitting technique.





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