Health assessment of photovoltaic modules based on fuzzy theory and combined weights

doi:10.3969/j.issn.1000-1565.2020.01.014

Abstract

Abstract: Photovoltaic energy has been widely used for its energy regeneration and clean nature, and has broad development prospects. However, the health status during its operation directly affects the safety of power system operation, power quality and economy. Therefore, it is necessary to evaluate the health status of PV(photovoltaic)modules to achieve the purpose of ‘early detection and early treatment’. In this paper, fuzzy theory, cloud model, analytic hierarchy process and entropy weight method are used to establish the health assessment model of PV modules. Taking the operating parameters, environmental parameters and patrol parameters as the main basis, considering the multi-level and multi-factor of the PV module status information, the complex problems are decomposed and a hierarchical index system for PV module status assessment is established. According to the analytic hierarchy process(AHP)and the entropy weight method, - DOI:10.3969/j.issn.1000-1565.2020.01.014基于模糊理论和组合权重的光伏组件健康状况评估贾玲¹,黄丽华¹,刘雪飞²,韩璟琳²,唐巍³(1. 河北农业大学机电工程学院,河北保定 071000;2.国网河北省电力有限公司经济技术研究院,河北石家庄 050021;3.中国农业大学信息与电气工程学院,北京 100083)摘要:光伏能源以其能源再生和清洁为特点得到广泛应用,并具有广阔发展前景,然而其运行过程中的健康状况直接影响电力系统运行的安全性、经济性和电能质量,因此需要对光伏组件进行健康状况评估,以达到“早发现,早治疗”的目的.综合运用模糊理论、云模型及层次分析法和熵权法建立了光伏组件健康状况评估模型.以运行参数、环境参数、巡视参数为主要依据,考虑到光伏组件状况的多层次性和多因素性,进而将复杂问题进行分解,建立了光伏组件状况评估的层次指标体系.根据层次分析法(AHP)和熵权法确定权重向量模型,利用云模型建立模糊关系,依此建立光伏组件健康状况评估模型,对层次指标体系中的各层次的权重向量模型和模糊关系模型进行模糊运算,最终得到光伏组件健康状况的隶属度.实例分析表明,该方法是可行有效的.关键词:光伏组件;健康评估;模糊理论;云模型;组合权重中图分类号:TM 615 文献标志码:A 文章编号:1000-1565(2020)01-0095-09Health assessment of photovoltaic modules based on fuzzy theory and combined weightsJIA Ling¹,HUANG Lihua¹,LIU Xuefei²,HAN Jinglin²,TANG Wei³(1.College of Mechanical and Electrical Engineering,Agricultural University of Hebei,Baoding 071000,China;2. Economic Research Institute,State Grid Hebei Electric Power Co. Ltd.,Shijiazhuang 050021,China;3.School of Information and Electrical Engineering, China Agricultural University,Beijing 100083,China)Abstract: Photovoltaic energy has been widely used for its energy regeneration and clean nature, and has broad development prospects. However, the health status during its operation directly affects the safety of power system operation, power quality and economy. Therefore, it is necessary to evaluate the health status of PV(photovoltaic)modules to achieve the purpose of ‘early detection and early treatment’. In this paper, fuzzy theory, cloud model, analytic hierarchy process and entropy weight method are used to establish the health assessment model of PV modules. Taking the operating parameters, environmental parameters and patrol parameters as the main basis, considering the multi-level and multi-factor of the PV module status information, the complex problems are decomposed and a hierarchical index system for PV module status assessment is established. According to the analytic hierarchy process(AHP)and the entropy weight method, - 收稿日期:2019-07-07 项目基金:国家自然科学基金资助项目(51377162);国网河北省电力有限公司项目(SGHEJY00GHJS1900028) 第一作者:贾玲(1994—),女,河北保定人,河北农业大学在读硕士研究生.E-mail:876535449@qq.com 通信作者:黄丽华(1963—),女,山东荣成人,河北农业大学教授,博士,主要从事配电系统及其自动化、人工智能方面的研究. E-mial:962382758@163.com第1期贾玲等:基于模糊理论和组合权重的光伏组件健康状况评估the weight vector model is determined, and the cloud model is used to establish the fuzzy relationship. According to the health status of the PV module, the condition evaluation model is established, and the weight vector model and the fuzzy relationship model of each level in the hierarchical index system are established. The fuzzy operation is performed to finally obtain the membership degree of the health status of the photovoltaic module. Case analysis shows that the method is feasible and effective.

Key words: photovoltaic module, health assessment, fuzzy theory, cloud model, combined weight

CLC Number:

TM615

JIA Ling,HUANG Lihua,LIU Xuefei,HAN Jinglin,TANG Wei. Health assessment of photovoltaic modules based on fuzzy theory and combined weights[J]. Journal of Hebei University (Natural Science Edition), 2020, 40(1): 95-103.

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