Enhanced Success History Adaptive DE for Parameter Optimization of Photovoltaic Models
In the past few decades, a lot of optimization methods have been applied in estimating the parameter of photovoltaic (PV) models and obtained better results, but these methods still have some deficiencies, such as higher time complexity and poor stability. To tackle these problems, an enhanced succe...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi-Wiley
2021-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2021/6660115 |
id |
doaj-215d14e42f33442dbd6b1f3958b9e3c7 |
---|---|
record_format |
Article |
spelling |
doaj-215d14e42f33442dbd6b1f3958b9e3c72021-02-15T12:52:50ZengHindawi-WileyComplexity1076-27871099-05262021-01-01202110.1155/2021/66601156660115Enhanced Success History Adaptive DE for Parameter Optimization of Photovoltaic ModelsYingjie Song0Daqing Wu1Ali Wagdy Mohamed2Xiangbing Zhou3Bin Zhang4Wu Deng5School of Computer Science and Technology, Shandong Technology and Business University, Yantai 264005, ChinaCollege of Economics & Management, Shanghai Ocean University, Shanghai 201306, ChinaOperations Research Department, Institute of Statistical Studies and Research, Cairo University, Giza 12613, EgyptSchool of Information and Engineering, Sichuan Tourism University, Chengdu 610100, ChinaSchool of Computer Science and Technology, Shandong Technology and Business University, Yantai 264005, ChinaCollege of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, ChinaIn the past few decades, a lot of optimization methods have been applied in estimating the parameter of photovoltaic (PV) models and obtained better results, but these methods still have some deficiencies, such as higher time complexity and poor stability. To tackle these problems, an enhanced success history adaptive DE with greedy mutation strategy (EBLSHADE) is employed to optimize parameters of PV models to propose a parameter optimization method in this paper. In the EBLSHADE, the linear population size reduction strategy is used to gradually reduce population to improve the search capabilities and balance the exploitation and exploration capabilities. The less and more greedy mutation strategy is used to enhance the exploitation capability and the exploration capability. Finally, a parameter optimization method based on EBLSHADE is proposed to optimize parameters of PV models. The different PV models are selected to prove the effectiveness of the proposed method. Comparison results demonstrate that the EBLSHADE is an effective and efficient method and the parameter optimization method is beneficial to design, control, and optimize the PV systems.http://dx.doi.org/10.1155/2021/6660115 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yingjie Song Daqing Wu Ali Wagdy Mohamed Xiangbing Zhou Bin Zhang Wu Deng |
spellingShingle |
Yingjie Song Daqing Wu Ali Wagdy Mohamed Xiangbing Zhou Bin Zhang Wu Deng Enhanced Success History Adaptive DE for Parameter Optimization of Photovoltaic Models Complexity |
author_facet |
Yingjie Song Daqing Wu Ali Wagdy Mohamed Xiangbing Zhou Bin Zhang Wu Deng |
author_sort |
Yingjie Song |
title |
Enhanced Success History Adaptive DE for Parameter Optimization of Photovoltaic Models |
title_short |
Enhanced Success History Adaptive DE for Parameter Optimization of Photovoltaic Models |
title_full |
Enhanced Success History Adaptive DE for Parameter Optimization of Photovoltaic Models |
title_fullStr |
Enhanced Success History Adaptive DE for Parameter Optimization of Photovoltaic Models |
title_full_unstemmed |
Enhanced Success History Adaptive DE for Parameter Optimization of Photovoltaic Models |
title_sort |
enhanced success history adaptive de for parameter optimization of photovoltaic models |
publisher |
Hindawi-Wiley |
series |
Complexity |
issn |
1076-2787 1099-0526 |
publishDate |
2021-01-01 |
description |
In the past few decades, a lot of optimization methods have been applied in estimating the parameter of photovoltaic (PV) models and obtained better results, but these methods still have some deficiencies, such as higher time complexity and poor stability. To tackle these problems, an enhanced success history adaptive DE with greedy mutation strategy (EBLSHADE) is employed to optimize parameters of PV models to propose a parameter optimization method in this paper. In the EBLSHADE, the linear population size reduction strategy is used to gradually reduce population to improve the search capabilities and balance the exploitation and exploration capabilities. The less and more greedy mutation strategy is used to enhance the exploitation capability and the exploration capability. Finally, a parameter optimization method based on EBLSHADE is proposed to optimize parameters of PV models. The different PV models are selected to prove the effectiveness of the proposed method. Comparison results demonstrate that the EBLSHADE is an effective and efficient method and the parameter optimization method is beneficial to design, control, and optimize the PV systems. |
url |
http://dx.doi.org/10.1155/2021/6660115 |
work_keys_str_mv |
AT yingjiesong enhancedsuccesshistoryadaptivedeforparameteroptimizationofphotovoltaicmodels AT daqingwu enhancedsuccesshistoryadaptivedeforparameteroptimizationofphotovoltaicmodels AT aliwagdymohamed enhancedsuccesshistoryadaptivedeforparameteroptimizationofphotovoltaicmodels AT xiangbingzhou enhancedsuccesshistoryadaptivedeforparameteroptimizationofphotovoltaicmodels AT binzhang enhancedsuccesshistoryadaptivedeforparameteroptimizationofphotovoltaicmodels AT wudeng enhancedsuccesshistoryadaptivedeforparameteroptimizationofphotovoltaicmodels |
_version_ |
1714866968406786048 |