PEM燃料电池系统多目标模糊粒子群优化

Ren Yuan, Zhong Zhidan, Zhang Bo, Lv Feng, Xu Huili
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引用次数: 1

摘要

提出了质子交换膜燃料电池(PEMFC)发电系统的多目标模糊粒子群优化算法。PEM燃料电池发电系统的效率随着输出功率的增大而降低。因此,一个最佳的效率应该存在,并应导致成本效益的PEM燃料电池发电系统。在优化方法中,同时考虑了效率和经济两个方面。针对上述目标函数,采用最小最小优化算法求解一组Pareto最优解。在各种操作条件下验证了所提出的优化器的性能。实验和仿真结果表明,该优化器运行良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-objective fuzzy particle swarm optimization in PEM fuel cell systems
This paper proposed multi-objective fuzzy particle swarm optimization (MOFPSO) for the Proton Exchange Membrane Fuel Cells (PEMFC) generation system. The PEM fuel cell generation system efficiency decreases as its output power increases. Thus, an optimum efficiency should exist and should result in a cost-effective PEM fuel cell generation system. In the optimization approach, the efficient and economic aspects are considered simultaneously. MOFPSO algorithm is used to find a set of Pareto optimal solutions with respect to the aforementioned objective functions. The performance of the proposed optimizer is demonstrated under various operating conditions. Both experimental and simulation results show the optimizer works well.
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