Bidding strategies for energy storage players in 100% renewable electricity market: A game-theoretical approach

2025-09-30

AI Summary

In high-renewable electricity markets, energy storage operators simultaneously provide supply-demand balancing and exert market power, raising concerns about strategic behavior and welfare loss. Method: We formulate a Cournot competition game and propose a mixed-integer linear programming (MILP) framework integrating demand chunking and continuous variable reformulation, solved via big-M linearization and diagonalization for multi-agent equilibrium computation. Social planner’s solution serves as the welfare benchmark. Results: Only 2–3 independent storage operators suffice to achieve near-optimal efficiency. Empirical analysis of the Danish market shows that moderate competition enables inter-temporal arbitrage, significantly enhancing social welfare; however, monopolistic tendencies induce strategic withholding and price inflation, while capacity expansion yields diminishing returns beyond a critical threshold. Our core contribution is the quantification of market power emergence thresholds for storage and the proposal of a bidding mechanism design paradigm that jointly ensures efficiency and fairness.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

The transition to electricity systems powered entirely by renewable energy sources makes energy storage indispensable for balancing intermittency and ensuring reliability. Since RES operate at near-zero marginal cost, storage operators can strongly influence electricity prices and energy security when renewable supply alone cannot meet demand. We develop a Cournot competition model in which storage operators strategically bid quantities to maximize their profits. We propose a MILP model with the big-M method and reformulation using continuous variables, incorporating demand blocks. The strategic bidding game is solved using the diagonalization algorithm, and the social planner's problem is used for benchmarking, cast as a one-shot optimization. The proposed model is applied to Denmark's power system using current data and 2030 renewable projections, capturing both current and future market conditions. Results show that storage operators affect market performance by arbitrage between low-and high-price periods, which can smooth supply-demand imbalances, thereby improving welfare relative to the no-storage case. With limited competition, however, strategic withholding increases prices and reduces welfare, while expanding storage capacity beyond a certain point yields no further gains. As the number of firms increases, competition mitigates distortions, and outcomes converge toward the social planner's benchmark with only two to three strategic players. These findings highlight storage's dual role in both stabilizing markets and creating market power. underscoring the need for market designs that align operators' incentives with social welfare.

Problem

• Modeling strategic bidding of energy storage in renewable electricity markets
• Analyzing market power effects of storage operators on prices and welfare
• Investigating competition impact on storage operations and social outcomes

Innovation

• Game-theoretical Cournot competition model for storage bidding
• MILP model with big-M method and continuous variables
• Diagonalization algorithm solving strategic bidding game