An Imitation Learning Based Algorithm Enabling Priori Knowledge Transfer in Modern Electricity Markets for Bayesian Nash Equilibrium Estimation

Ziqing Zhu, Ka Wing Chan, Siqi Bu, Ze Hu, Shiwei Xia

Research output: Contribution to journalJournal articlepeer-review

Abstract

The Nash Equilibrium (NE) estimation in bidding games of electricity markets is the key concern of both generation companies (GENCOs) for bidding strategy optimization and the Independent System Operator (ISO) for market surveillance. However, existing methods for NE estimation in emerging modern electricity markets (FEM) are inaccurate and inefficient because the priori knowledge of bidding strategies before any environment changes, such as load demand variations, network congestion, and modifications of market design, is not fully utilized. In this paper, a Bayes-adaptive Markov Decision Process in FEM (BAMDP-FEM) is therefore developed to model the GENCOs’ bidding strategy optimization considering the priori knowledge. A novel Multi-Agent Generative Adversarial Imitation Learning algorithm (MAGAIL-FEM) is then proposed to enable GENCOs to learn simultaneously from priori knowledge and interactions with changing environments. The obtained NE is a Bayesian Nash Equilibrium (BNE) with priori knowledge transferred from the previous environment. In the case study, the superiority of this proposed algorithm in terms of convergence speed compared with conventional methods is verified. It is concluded that the optimal bidding strategies in the obtained BNE can always lead to more profits than NE due to the effective learning from the priori knowledge. Also, BNE is more accurate and consistent with situations in real-world markets.

Original languageEnglish
Number of pages13
JournalIEEE Transactions on Power Systems
DOIs
Publication statusE-pub ahead of print - 12 Dec 2023

Scopus Subject Areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

User-Defined Keywords

  • Imitation Learning
  • Bayesian Nash Equilibrium
  • electricity market
  • bidding game
  • knowledge transfer

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