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An agent-based approach is proposed in this paper 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 Q-learning algorithm. These companies also participate in allowances...
The demise of the native franchise markets and emergence of competitive markets for electricity generation service is changing the way that electricity is and will be priced and is making increasingly difficult for market participants to appraise the prospects for the future electricity market. As a result, conventional generation expansion planning (GEP) problems determining the least-cost capacity...
In this presentation, the authors propose a new framework for a generation expansion planning (GEP) applicable in a competitive environment using a genetic algorithm (GA). Unlike the traditional approaches, the new GEP in a competitive market is very complex due to conflicts among generation companies (GENCOs). The objective function of each GENCO for investment decision-making is to maximize its...
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