The evolutionary game equilibrium theory on power market bidding involving renewable energy companies

In the electricity bidding market, power generation companies and distribution-oriented grid enterprises face increasingly complex and dynamic decision-making challenges that cannot be fully captured by static or one-shot approaches. To address these challenges, this study proposes a novel evolutionary game-theoretic framework featuring a "mixed-strategy distortion" mechanism, which introduces adaptive periodic adjustments in bidding ranges. This extension to classical evolutionary models reveals how cyclical constraints and strategic disruptions influence the emergence of cooperative equilibria and market dynamics. The study develops a theoretical framework for analyzing long-term stable equilibria in asymmetric evolutionary games involving distinct groups of power generators, underpinned by a renewable energy grid-connected benefit coordination model. Theoretical analyses are validated through dynamic simulations that examine the interplay of key parameters, including generation costs, local market demands, bidding ranges, and production capacities. The results demonstrate how variations in these factors influence the evolution of bidding strategies, providing insights into the stability of competitive equilibria in electricity markets. Furthermore, the findings highlight that rational adjustments to bidding intervals can mitigate distortions, reduce electricity prices, and promote dynamic market stability. By advancing the understanding of adaptive bidding strategies in competitive electricity markets, this research offers actionable insights for policy development, market regulation, and strategic decision-making for power generation enterprises and grid operators. These contributions provide a foundation for the design of more efficient market mechanisms, promoting both economic efficiency and sustainable energy transitions.