Impacts of market power from renewables with different market concentrations on electricity markets under high renewable penetration

Abstract

• The interactions between strategic bidding behaviors and electricity markets under different market concentration levels are modeled. • A multi-agent RL algorithm that incorporates the Bandit Algorithm and model planning is proposed. • Strategic bidding by renewables under high market concentration induces severe curtailment and high prices. • Strategic bidding by renewables effectively mitigates the “missing money” problem. With the in-depth development of decarbonization in the power system, renewables will gradually occupy a dominant position in the electricity spot market. The significant impact of renewable energy market power on the electricity market under high renewable penetration has emerged as a critical concern, particularly in countries with high market concentration like China. This paper explores how the market power and the market concentration of renewables impact the operation and pricing of the electricity market at elevated renewable penetration. The game-theoretic interactions between strategic bidding behaviors and electricity markets under different market concentration levels are modeled through a bi-level optimization framework. A novel algorithm based on multi-agent reinforcement learning is put forward to efficiently solve the model with multiple generation companies in a provincial power system. The proposed model and algorithm are applied to the West Inner Mongolia of China. The results show that strategic bidding by renewables under high market concentration induces severe curtailment and high prices through physical and financial withholding. Although reduced concentration drives rapid price declines, converged levels remain substantially higher than those in marginal cost bidding scenarios, demonstrating that strategic bidding effectively mitigates the price suppression effect caused by renewable energy expansion.

Topics & Concepts