Photovoltaic cells parameters extraction using variables reduction and improved shark optimization technique

doi:10.1016/j.ijhydene.2020.01.236

	Photovoltaic cells parameters extraction using variables reduction and improved shark optimization technique
	Chen, Shanshan1 ; Gholami Farkoush, Saeid 2; Leto, Sebastian 3
	2020-03-20
发表期刊	INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
ISSN	0360-3199
EISSN	1879-3487
卷号	45 期号:16 页码:10059-10069
摘要	This article aimed to present a new approach which consists of three-points, and concerns each diode pattern separately. Distinct from traditional curve fitting processes, this approach is based on the simplistic view which flourishes the potential abilities in order to provide the efficient solutions with the least repetitions. The basic reason of this study is to substitute the three – point approach with the previous used approach and set it as core point. By using mentioned points, it reinforces the usage of improved shark smell optimization algorithm and regulates the left parts efficiently. Consequently, it decreases the elaborateness of algorithms. According to the conducted parts comparisons on the three case studies, proved that the presented method has more exactness than the traditional methods. As well as, the investigated the proposed method has high efficiency and presents the optimized solution in various cells type. Also the achieved solutions are stable and is compared with over 17 various algorithms which in whole of the standard deviation of root mean square error for three type of cells is lower than the determined scales in other studies. By having these values, the suggested approach had been predicted to work efficiently in all circumstances like offline analysis and online controlling and it requires an exact, steady approach exploitation tool. © 2020 Hydrogen Energy Publications LLC
关键词	Extraction Mean square error Optimization Parameter extraction Photoelectrochemical cells Photovoltaic cells ISSO Optimization algorithms Optimization techniques Optimized solutions Parameters extraction Photovoltaic systems Root mean square errors Variable reductions
DOI	10.1016/j.ijhydene.2020.01.236
收录类别	EI ; SCIE
语种	英语
WOS研究方向	Chemistry ; Electrochemistry ; Energy & Fuels
WOS类目	Chemistry, Physical ; Electrochemistry ; Energy & Fuels
WOS记录号	WOS:000523719700072
出版者	Elsevier Ltd
EI入藏号	20200908228732
EI分类号	702.1 Electric Batteries ; 802.3 Chemical Operations ; 921.5 Optimization Techniques ; 921.6 Numerical Methods ; 922 Statistical Methods ; 922.2 Mathematical Statistics
原始文献类型	Journal article (JA)
出版地	OXFORD
引用统计	被引频次：11[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.cqcet.edu.cn/handle/39TD4454/3126
专题	智能制造与汽车学院
作者单位	1.Chongqing College of Electronic Engineering, Shapingba District, Chongqing; 401331, China; 2.Department of Electrical Engineering at Yeungnam University, Yeungnam, Korea, Republic of; 3.Department of Engineering, Technical University of Koice, Koice, Slovakia
第一作者单位	重庆电子科技职业大学
推荐引用方式 GB/T 7714	Chen, Shanshan,Gholami Farkoush, Saeid,Leto, Sebastian. Photovoltaic cells parameters extraction using variables reduction and improved shark optimization technique[J]. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY,2020,45(16):10059-10069.
APA	Chen, Shanshan,Gholami Farkoush, Saeid,&Leto, Sebastian.(2020).Photovoltaic cells parameters extraction using variables reduction and improved shark optimization technique.INTERNATIONAL JOURNAL OF HYDROGEN ENERGY,45(16),10059-10069.
MLA	Chen, Shanshan,et al."Photovoltaic cells parameters extraction using variables reduction and improved shark optimization technique".INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 45.16(2020):10059-10069.