Analyzing Trade in Continuous Intra-Day Electricity Market: An Agent-Based Modeling Approach

• Main Authors: Priyanka Shinde, Ioannis Boukas, David Radu, Miguel Manuel de Villena, Mikael Amelin
• Format: Article
• Language: English
• Published: MDPI AG 2021-06-01
• Series: Energies
• Subjects: intra-day electricity markets; agent-based modeling; adaptive learning; renewable energy sources
• Online Access: https://www.mdpi.com/1996-1073/14/13/3860

In recent years, the vast penetration of renewable energy sources has introduced a large degree of uncertainty into the power system, thus leading to increased trading activity in the continuous intra-day electricity market. In this paper, we propose an agent-based modeling framework to analyze the behavior and the interactions between renewable energy sources, consumers and thermal power plants in the European Continuous Intra-day (CID) market. Additionally, we propose a novel adaptive trading strategy that can be used by the agents that participate in CID market. The agents learn how to adapt their behavior according to the arrival of new information and how to react to changing market conditions by updating their willingness to trade. A comparative analysis was performed to study the behavior of agents when they adopt the proposed strategy as opposed to other benchmark strategies. The effects of unexpected outages and information asymmetry on the market evolution and the market liquidity were also investigated.