基于改进HHO算法的集中式光伏组件运维成本优化  

Optimization of Operation and Maintenance Cost for Centralized Photovoltaic Modules Based on Improved HHO Algorithm

作　　者：曾晓龙 黄勇 刘泽纬 官洲洋 谭杭 陈进财 ZENG Xiaolong;HUANG Yong;LIU Zewei;GUAN Zhouyang;TAN Hang;CHEN Jincai(College of Intelligent Systems Science and Engineering,Hubei Minzu University,Enshi 445000,China;Da Xiang Technology(Enshi)Co.,Ltd.,Enshi 445000,China)

机构地区：[1]湖北民族大学智能科学与工程学院,湖北恩施445000 [2]达翔技术(恩施)有限公司,湖北恩施445000

出　　处：《湖北民族大学学报(自然科学版)》2025年第1期101-107,125,共8页Journal of Hubei Minzu University:Natural Science Edition

基　　金：教育部产学研创新基金项目(2021RYC06004)。

摘　　要：针对集中式光伏组件定期维护策略下人工成本过度支出、发电量损失成本增加、未及时维护导致故障率升高等问题,构建了以最小日平均运维成本为目标函数的运维模型,并利用改进的哈里斯鹰优化(Harris hawks optimization, HHO)算法对目标函数进行了迭代优化,以求得最优解。该算法通过佳点集和量子计算初始化种群,提高种群的质量和多样性,并加快收敛速度;利用分段非线性映射函数优化猎物逃逸能量参数,增加迭代后期全局探索的可能性;结合黏菌优化算法的多重探索机制和准反向学习方法增强算法在全局范围内的探索能力;通过加入高斯差分变异,避免算法落入局部最优解的困境。结果显示,改进HHO算法相比于传统的定期维护方案,日平均运维成本降低了14.40%;相比于原始HHO算法,收敛迭代次数减少了13.24%。该研究对降低光伏电站的运维成本有一定的参考价值,对提高光伏电站经济效益和促进智能光伏电站发展起到积极的作用。To address the problems of excessive expenditure of labor cost,increased cost of power generation loss,and increased failure rate due to untimely maintenance under the regular maintenance strategy of centralized photovoltaic systems,an operation and maintenance model with the minimum daily average operation and maintenance cost as the objective function was constructed,and the objective function was iterated and optimized using the improved Harris hawks optimization(HHO)algorithm to find the optimal solution.The population was initialized by the good point set and quantum computation to improve the quality and diversity of the population and accelerate the convergence speed;the prey escape energy parameter was optimized by using the segmented nonlinear mapping function to increase the possibility of global exploration at the later stage of the iteration;the multi-exploration mechanism and quasi-reverse learning method of the sticky fungus optimization algorithm were combined to enhance the algorithm′s ability to explore the global range;the algorithm was prevented from falling into the local.The results showed that the improved HHO algorithm reduces the average daily operation and maintenance cost by 14.40%compared to the traditional periodic maintenance scheme,and reduced the number of convergence iterations by 13.24%compared to the original HHO algorithm.The study has certain reference value for reducing the operation cost of photovoltaic power plants,and has a positive effect on improving the economic benefits of photovoltaic power plants and promoting the development of intelligent photovoltaic power plants.

关 键 词：时变周期运维 佳点集 量子计算 准反向学习 高斯差分变异 

分 类 号：TM46[电气工程—电器]