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Environmental/economic power dispatch using a fuzzified multi-objective particle swarm optimization algorithm

机译:基于模糊多目标粒子群算法的环境/经济动力调度

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摘要

The environmental issues that arise from the pollutant emissions produced by fossil-fueled electric power plants have become a matter of concern more recently. The conventional economic power dispatch cannot meet the environmental protection requirements, since it only considers minimizing the total fuel cost. The multi-objective generation dispatch in electric power systems treats economic and emission impact as competing objectives, which requires some reasonable tradeoff among objectives to reach an optimal solution. In this paper, a fuzzified multi-objective particle swarm optimization (FMOPSO) algorithm is proposed and implemented to dispatch the electric power considering both economic and environmental issues. The effectiveness of the proposed approach is demonstrated by comparing its performance with other approaches including weighted aggregation (WA) and evolutionary multi-objective optimization algorithms. All the simulations are conducted based on a typical test power system.
机译:化石燃料发电厂产生的污染物排放引起的环境问题近来已成为人们关注的问题。传统的经济动力调度不能满足环保要求,因为它仅考虑使总燃料成本最小化。电力系统中的多目标发电调度将经济和排放影响视为竞争目标,这需要在目标之间进行合理的权衡以达到最佳解决方案。本文提出了一种模糊多目标粒子群优化算法(FMOPSO),并在考虑经济和环境问题的基础上实现了电力调度。通过将其性能与其他方法(包括加权聚合(WA)和进化多目标优化算法)进行比较,证明了该方法的有效性。所有模拟都是基于典型的测试电源系统进行的。

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