Horizontal and vertical crossover of Harris hawk optimizer with Nelder-Mead simplex for parameter estimation of photovoltaic models

•An improved Harris Hawks Optimizer (CCNMHHO) is proposed for photovoltaic systems.•The performance of CCNMHHO is compared with some well-known competitive algorithms.•Three PV models are simulated to verify the effectiveness of CCNMHHO.•This method has enhanced the convergence speed and accuracy in...

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Veröffentlicht in:	Energy conversion and management Jg. 223; S. 113211
Hauptverfasser:	Liu, Yun, Chong, Guoshuang, Heidari, Ali Asghar, Chen, Huiling, Liang, Guoxi, Ye, Xiaojia, Cai, Zhennao, Wang, Mingjing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Elsevier Ltd 01.11.2020 Elsevier Science Ltd
Schlagworte:	administrative management Algorithms Cell culture Convergence Crisscross optimization algorithm Crossovers Data exchange energy conversion estimation exhibitions extraction Harris Hawk optimization information exchange materials Mathematical models measurement Nelder-Mead simplex algorithm Optimization Parabuteo unicinctus Parameter estimation Photovoltaic cells Photovoltaic models Photovoltaics population Radiance Solar cells solar collectors temperature Harris Hawk optimization Parameter estimation Nelder-Mead simplex algorithm Photovoltaic models Crisscross optimization algorithm
ISSN:	0196-8904, 1879-2227
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Abstract	•An improved Harris Hawks Optimizer (CCNMHHO) is proposed for photovoltaic systems.•The performance of CCNMHHO is compared with some well-known competitive algorithms.•Three PV models are simulated to verify the effectiveness of CCNMHHO.•This method has enhanced the convergence speed and accuracy in various conditions. An improved Harris hawks optimization is proposed in this work to facilitate the simulation of an efficient photovoltaic system and extraction of unknown parameters, which combines horizontal and vertical crossover mechanism of the crisscross optimizer and Nelder-Mead simplex algorithm, named CCNMHHO. In CCNMHHO, the cores appeared in the crisscross optimizer are utilized to enrich the information exchange between the individuals and avoid the problem of dimensional stagnation of individuals all through the iterations. Hence, it enhances to change to improve the population quality and prevent the shortcoming of falling into a local optimum. In contrast, the Nelder-Mead simplex algorithm is employed in the proposed CCNMHHO methodology. Nelder-Mead simplex helps to improve individual searching capabilities in performing the local search phase and showing a faster convergence to optimal values. Compared to some algorithms that have a competitive performance in dealing with this type of problem, CCNMHHO has a faster convergence speed, and it shows high stability. In different environments, the experimental data obtained by this improved Harris hawks Optimization can reveal a high agreement with the measurement data. The experimental results show that the proposed method not only is very competitive in extracting the unknown parameters of different PV models compared to other state-of-the-art algorithms but also perform well in dealing with the complex outdoor environments such as different temperature and radiance. Therefore, we observed that the CCNMHHO could be considered as a reliable and efficient method in solving a class of cases for the assessment of unknown parameters of solar cells and photovoltaic models. For post-publication guidance, supports, and materials for this research, please refer to the supporting homepage: http://aliasgharheidari.com.
AbstractList	An improved Harris hawks optimization is proposed in this work to facilitate the simulation of an efficient photovoltaic system and extraction of unknown parameters, which combines horizontal and vertical crossover mechanism of the crisscross optimizer and Nelder-Mead simplex algorithm, named CCNMHHO. In CCNMHHO, the cores appeared in the crisscross optimizer are utilized to enrich the information exchange between the individuals and avoid the problem of dimensional stagnation of individuals all through the iterations. Hence, it enhances to change to improve the population quality and prevent the shortcoming of falling into a local optimum. In contrast, the Nelder-Mead simplex algorithm is employed in the proposed CCNMHHO methodology. Nelder-Mead simplex helps to improve individual searching capabilities in performing the local search phase and showing a faster convergence to optimal values. Compared to some algorithms that have a competitive performance in dealing with this type of problem, CCNMHHO has a faster convergence speed, and it shows high stability. In different environments, the experimental data obtained by this improved Harris hawks Optimization can reveal a high agreement with the measurement data. The experimental results show that the proposed method not only is very competitive in extracting the unknown parameters of different PV models compared to other state-of-the-art algorithms but also perform well in dealing with the complex outdoor environments such as different temperature and radiance. Therefore, we observed that the CCNMHHO could be considered as a reliable and efficient method in solving a class of cases for the assessment of unknown parameters of solar cells and photovoltaic models. For post-publication guidance, supports, and materials for this research, please refer to the supporting homepage: http://aliasgharheidari.com. •An improved Harris Hawks Optimizer (CCNMHHO) is proposed for photovoltaic systems.•The performance of CCNMHHO is compared with some well-known competitive algorithms.•Three PV models are simulated to verify the effectiveness of CCNMHHO.•This method has enhanced the convergence speed and accuracy in various conditions. An improved Harris hawks optimization is proposed in this work to facilitate the simulation of an efficient photovoltaic system and extraction of unknown parameters, which combines horizontal and vertical crossover mechanism of the crisscross optimizer and Nelder-Mead simplex algorithm, named CCNMHHO. In CCNMHHO, the cores appeared in the crisscross optimizer are utilized to enrich the information exchange between the individuals and avoid the problem of dimensional stagnation of individuals all through the iterations. Hence, it enhances to change to improve the population quality and prevent the shortcoming of falling into a local optimum. In contrast, the Nelder-Mead simplex algorithm is employed in the proposed CCNMHHO methodology. Nelder-Mead simplex helps to improve individual searching capabilities in performing the local search phase and showing a faster convergence to optimal values. Compared to some algorithms that have a competitive performance in dealing with this type of problem, CCNMHHO has a faster convergence speed, and it shows high stability. In different environments, the experimental data obtained by this improved Harris hawks Optimization can reveal a high agreement with the measurement data. The experimental results show that the proposed method not only is very competitive in extracting the unknown parameters of different PV models compared to other state-of-the-art algorithms but also perform well in dealing with the complex outdoor environments such as different temperature and radiance. Therefore, we observed that the CCNMHHO could be considered as a reliable and efficient method in solving a class of cases for the assessment of unknown parameters of solar cells and photovoltaic models. For post-publication guidance, supports, and materials for this research, please refer to the supporting homepage: http://aliasgharheidari.com.
ArticleNumber	113211
Author	Heidari, Ali Asghar Wang, Mingjing Ye, Xiaojia Chong, Guoshuang Chen, Huiling Liang, Guoxi Liu, Yun Cai, Zhennao
Author_xml	– sequence: 1 givenname: Yun surname: Liu fullname: Liu, Yun organization: Department of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China – sequence: 2 givenname: Guoshuang surname: Chong fullname: Chong, Guoshuang organization: China Industrial Control Systems Cyber Emergency Response Team, Beijing 100040, China – sequence: 3 givenname: Ali Asghar orcidid: 0000-0001-6938-9948 surname: Heidari fullname: Heidari, Ali Asghar email: as_heidari@ut.ac.ir, aliasgha@comp.nus.edu.sg, t0917038@u.nus.edu organization: School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran – sequence: 4 givenname: Huiling orcidid: 0000-0002-7714-9693 surname: Chen fullname: Chen, Huiling email: chenhuiling.jlu@gmail.com organization: Department of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China – sequence: 5 givenname: Guoxi orcidid: 0000-0003-4754-6644 surname: Liang fullname: Liang, Guoxi organization: Department of Information Technology, Wenzhou Polytechnic, Wenzhou 325035, China – sequence: 6 givenname: Xiaojia surname: Ye fullname: Ye, Xiaojia email: yxj@lixin.edu.cn organization: Shanghai Lixin University of Accounting and Finance, Shanghai 201209, China – sequence: 7 givenname: Zhennao surname: Cai fullname: Cai, Zhennao email: cznao@wzu.edu.cn organization: Department of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China – sequence: 8 givenname: Mingjing surname: Wang fullname: Wang, Mingjing email: mingjingwang@duytan.edu.vn organization: Institute of Research and Development, Duy Tan University, Da Nang 550000, Viet Nam
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Snippet	•An improved Harris Hawks Optimizer (CCNMHHO) is proposed for photovoltaic systems.•The performance of CCNMHHO is compared with some well-known competitive... An improved Harris hawks optimization is proposed in this work to facilitate the simulation of an efficient photovoltaic system and extraction of unknown...
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SubjectTerms	administrative management Algorithms Cell culture Convergence Crisscross optimization algorithm Crossovers Data exchange energy conversion estimation exhibitions extraction Harris Hawk optimization information exchange materials Mathematical models measurement Nelder-Mead simplex algorithm Optimization Parabuteo unicinctus Parameter estimation Photovoltaic cells Photovoltaic models Photovoltaics population Radiance Solar cells solar collectors temperature
Title	Horizontal and vertical crossover of Harris hawk optimizer with Nelder-Mead simplex for parameter estimation of photovoltaic models
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