摘要
为了同时优化质子交换膜燃料电池(proton exchange membrane fuel cells,PEMFC)系统的效率和输出功率,文章首先建立PEMFC系统的机理模型,并分析系统效率和输出功率特性;其次针对传统灰狼算法(grey wolf optimizer,GWO)的初始化种群不均匀和易出现早熟收敛的问题,引入佳点集种群初始化策略和非线性收敛因子策略,并由此提出一种改进多目标灰狼优化算法(multi-objective grey wolf optimizer,MOGWO),有效改善了灰狼算法的搜索精度和收敛性能;然后针对改进多目标灰狼优化算法求得的Pareto最优解集,使用TOPSIS评价法得出逼近理想解的最佳解,确定PEMFC系统的最佳运行条件;最后对所提出的MOGWO算法进行仿真验证,结果表明该算法能够有效提高PEMFC系统在实际运行中的输出功率和系统效率。
In order to simultaneously optimize the efficiency and output power of the proton exchange membrane fuel cells(PEMFC)system,the mechanism model of the PEMFC system is established,and the system efficiency and output power characteristics are analyzed.Then,in view of the problems of traditional grey wolf optimizer(GWO)such as uneven initialization population and premature convergence,the optimal point cluster group initialization strategy and nonlinear convergence factor strategy are introduced,and an improved multi-objective grey wolf optimizer(MOGWO)algorithm is proposed,which effectively improves the search accuracy and convergence performance of the GWO.For the Pareto optimal solution set obtained by the improved MOGWO algorithm,the TOPSIS evaluation method is used to obtain the best solution approaching the ideal solution,and the best operating conditions of the PEMFC system are determined.Finally,the proposed algorithm is verified by simulation,and the results show that the proposed algorithm can effectively improve the output power and system efficiency of the PEMFC in practical operation.
作者
黄诚
苏建徽
解宝
黄赵军
瞿晓丽
王建国
HUANG Cheng;SU Jianhui;XIE Bao;HUANG Zhaojun;QU Xiaoli;WANG Jianguo(School of Electrical Engineering and Automation,Hefei University of Technology,Hefei 230009,China;Institute of Energy,Hefei Comprehensive National Science Center,Hefei 230051,China)
出处
《合肥工业大学学报(自然科学版)》
北大核心
2025年第1期37-43,共7页
Journal of Hefei University of Technology:Natural Science
基金
安徽省自然科学基金青年资助项目(2208085QE165)
中央高校基本科研业务费专项资金资助项目(PA2021GDGP0060)。
关键词
质子交换膜燃料电池(PEMFC)
输出功率
系统效率
多目标优化
改进灰狼算法
proton exchange membrane fuel cells(PEMFC)
output power
system efficiency
multi-objective optimization
improved grey wolf optimizer
