Abstract
An agent-based approach is proposed in this book chapter to analyze interactions between the emission and electricity markets. A cap-and-trade system is assumed to be in place to regulate emissions from power generation. Generation companies are modeled as adaptive learning agents that can bid strategically into the electricity market by a Q-learning algorithm. These companies also participate in allowances trading in the emission market by adjusting their own allowances positions. In the simulation, generation companies can value their generation capacity and available allowances to maximize their profits. Three different trading strategies are modeled to mimic the decision-making process of generation companies. This modeling framework can help design a sound emission market by simulating market scenarios with different policies. It can also be used to investigate the operation strategies for generation companies in such an environment.
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Wang, J., Koritarov, V., Kim, JH. (2012). Cap and Trade Modeling in Electricity Markets Using an Agent-Based Approach. In: Zheng, Q., Rebennack, S., Pardalos, P., Pereira, M., Iliadis, N. (eds) Handbook of CO₂ in Power Systems. Energy Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27431-2_5
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DOI: https://doi.org/10.1007/978-3-642-27431-2_5
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