Market Design

Market design focuses on creating efficient and equitable systems for allocating resources, with a current emphasis on optimizing electricity markets. Research utilizes reinforcement learning, particularly Markov game models and algorithms like multi-agent policy proximal optimization, to simulate and evaluate different market structures, considering interactions between spot, ancillary, and financial markets. This approach aims to improve market performance indicators such as economic efficiency and system reliability, addressing challenges posed by increasing renewable energy integration. The resulting insights can inform the design of more robust and adaptable energy markets.