粒子群优化
计算机科学
电池(电)
对偶(语法数字)
数学优化
能源管理
功率(物理)
能源消耗
汽车工程
工程类
能量(信号处理)
算法
电气工程
数学
艺术
物理
文学类
量子力学
统计
作者
Ze Zhou,Zhichao Fu,Liyan Zhang,Dongqi Zhao,Shuiying Yu,Qihong Chen
标识
DOI:10.1080/15435075.2024.2313043
摘要
Low hydrogen consumption is an important objective for fuel cell power systems as it impacts both economic efficiency and continuous power supply. This paper addresses the optimization problem of minimizing hydrogen consumption in a hybrid power system comprising dual fuel cells and a single lithium battery. We introduce an energy management method for the multi-period synchronous optimization, incorporating a data processing module and power allocation module. The quasi-periodic loads are predicted using a modified gray-Markov chain model, while the optimization problem is solved using an adaptive constrained particle swarm optimization (ACPSO) algorithm. An initial swarm generation algorithm is introduced to enhance the effectiveness of ACPSO, and a power correction algorithm is integrated to address deviations between predicted and actual loads. The effectiveness and advantages in optimizing hydrogen consumption of the proposed strategy have been demonstrated through simulations and experiments.
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