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Hybrid particle swarm optimization of electricity market participation portfolio

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This paper proposes a novel hybrid particle swarm optimization methodology to solve the problem of optimal participation in multiple electricity markets. The decision time is usually very important when planning the participation in electricity markets. This environment is characterized by the time available to take action, since different electricity markets have specific rules, which requires participants to be able to adapt and plan their decisions in a short time. Using metaheuristic optimization, participants' time problems can be resolved, because these methods enable problems to be solved in a short time and with good results. This paper proposes a hybrid resolution method, which is based on the particle swarm optimization metaheuristic. An exact mathematical method, which solves a simplified, linearized, version of the problem, is used to generate the initial solution for the metaheuristic approach, with the objective of improving the quality of results without representing a significant increase of the execution time.

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Artificial intelligence Electricity markets Hybrid resolution methods Portfolio optimization Metaheuristic optimization

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