Solar photovoltaic model parameter identification using robust niching chimp optimization
•A niching concept is inspired to enhance the original ChOA.•RN-ChOA proposes a novel constraint handling technique.•The RN-ChOA is applied to estimate parameters on the SM55, SW255, and KC200GT.•RN-ChOA is compared with ten well-known algorithms. Researchers are becoming increasingly interested in...
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| Vydané v: | Solar energy Ročník 239; s. 179 - 197 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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New York
Elsevier Ltd
01.06.2022
Pergamon Press Inc |
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| ISSN: | 0038-092X, 1471-1257 |
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| Abstract | •A niching concept is inspired to enhance the original ChOA.•RN-ChOA proposes a novel constraint handling technique.•The RN-ChOA is applied to estimate parameters on the SM55, SW255, and KC200GT.•RN-ChOA is compared with ten well-known algorithms.
Researchers are becoming increasingly interested in studying how to accurately estimate the parameters of solar PV models. In this regard, this paper proposes a newly proposed nature-inspired technique named chimp optimization algorithm (ChOA) to create accurate and dependable PV models, such as single diode, double diodes, three diodes, and PV module models. In the PV models’ parameters estimation using optimization algorithms, two significant concerns need to be addressed: classifying various local/global optima and preserving these optimum values until the termination. Since ChOA is a general optimizer, it lacks an operator to address the two issues mentioned above. In order to address the mentioned problems, this paper embeds the niching technique in ChOA that includes the personal best qualities of PSO and a local search technique. In addition, a novel constraint handling approach is utilized to ensure that the algorithm is robust in tackling PV Models’ parameters estimation constraints. The outcome of RN-ChOA is evaluated using seven well-known optimization algorithms, including the whippy Harris hawks optimization algorithm (WHHOA), performance-guided JAYA (PGJAYA), enriched Harris hawks optimization algorithm (EHHOA), improved JAYA (IJAYA), birds mating optimizer (BMO), flexible particle swarm optimization algorithm (FPSO), chaotic biogeography-based optimizer (CBBO), and generalized oppositional teaching-learning algorithm (GOTLA), as well as dynamic Levy flight ChOA (DLF-ChOA) and weighted ChOA (WChOA) as the most recent modified version of ChOA. Furthermore, the performance of the RN-ChOA method has been assessed in a practical application for parameter evaluation of three widely-used commercial modules, namely, multi-crystalline (KC200GT), polycrystalline (SW255), and mono-crystalline (SM55), under a variety of temperature and irradiance conditions that cause changes in the photovoltaic model’s parameters. The findings demonstrate the robustness and excellent performance of the suggested approach. |
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| AbstractList | •A niching concept is inspired to enhance the original ChOA.•RN-ChOA proposes a novel constraint handling technique.•The RN-ChOA is applied to estimate parameters on the SM55, SW255, and KC200GT.•RN-ChOA is compared with ten well-known algorithms.
Researchers are becoming increasingly interested in studying how to accurately estimate the parameters of solar PV models. In this regard, this paper proposes a newly proposed nature-inspired technique named chimp optimization algorithm (ChOA) to create accurate and dependable PV models, such as single diode, double diodes, three diodes, and PV module models. In the PV models’ parameters estimation using optimization algorithms, two significant concerns need to be addressed: classifying various local/global optima and preserving these optimum values until the termination. Since ChOA is a general optimizer, it lacks an operator to address the two issues mentioned above. In order to address the mentioned problems, this paper embeds the niching technique in ChOA that includes the personal best qualities of PSO and a local search technique. In addition, a novel constraint handling approach is utilized to ensure that the algorithm is robust in tackling PV Models’ parameters estimation constraints. The outcome of RN-ChOA is evaluated using seven well-known optimization algorithms, including the whippy Harris hawks optimization algorithm (WHHOA), performance-guided JAYA (PGJAYA), enriched Harris hawks optimization algorithm (EHHOA), improved JAYA (IJAYA), birds mating optimizer (BMO), flexible particle swarm optimization algorithm (FPSO), chaotic biogeography-based optimizer (CBBO), and generalized oppositional teaching-learning algorithm (GOTLA), as well as dynamic Levy flight ChOA (DLF-ChOA) and weighted ChOA (WChOA) as the most recent modified version of ChOA. Furthermore, the performance of the RN-ChOA method has been assessed in a practical application for parameter evaluation of three widely-used commercial modules, namely, multi-crystalline (KC200GT), polycrystalline (SW255), and mono-crystalline (SM55), under a variety of temperature and irradiance conditions that cause changes in the photovoltaic model’s parameters. The findings demonstrate the robustness and excellent performance of the suggested approach. Researchers are becoming increasingly interested in studying how to accurately estimate the parameters of solar PV models. In this regard, this paper proposes a newly proposed nature-inspired technique named chimp optimization algorithm (ChOA) to create accurate and dependable PV models, such as single diode, double diodes, three diodes, and PV module models. In the PV models' parameters estimation using optimization algorithms, two significant concerns need to be addressed: classifying various local/global optima and preserving these optimum values until the termination. Since ChOA is a general optimizer, it lacks an operator to address the two issues mentioned above. In order to address the mentioned problems, this paper embeds the niching technique in ChOA that includes the personal best qualities of PSO and a local search technique. In addition, a novel constraint handling approach is utilized to ensure that the algorithm is robust in tackling PV Models' parameters estimation constraints. The outcome of RN-ChOA is evaluated using seven well-known optimization algorithms, including the whippy Harris hawks optimization algorithm (WHHOA), performance-guided JAYA (PGJAYA), enriched Harris hawks optimization algorithm (EHHOA), improved JAYA (IJAYA), birds mating optimizer (BMO), flexible particle swarm optimization algorithm (FPSO), chaotic biogeography-based optimizer (CBBO), and generalized oppositional teaching-learning algorithm (GOTLA), as well as dynamic Levy flight ChOA (DLF-ChOA) and weighted ChOA (WChOA) as the most recent modified version of ChOA. Furthermore, the performance of the RN-ChOA method has been assessed in a practical application for parameter evaluation of three widely-used commercial modules, namely, multi-crystalline (KC200GT), polycrystalline (SW255), and mono-crystalline (SM55), under a variety of temperature and irradiance conditions that cause changes in the photovoltaic model's parameters. The findings demonstrate the robustness and excellent performance of the suggested approach. |
| Author | Cheng, Wuqun Khishe, Mohammad Bo, Qiuyu Mohammed, Adil Hussein Mohammadi, Mokhtar |
| Author_xml | – sequence: 1 givenname: Qiuyu surname: Bo fullname: Bo, Qiuyu organization: Institute of Urban and Rural Construction, Hebei Agricultural University, Hebei Province, China – sequence: 2 givenname: Wuqun surname: Cheng fullname: Cheng, Wuqun email: wuquncheng314@outlook.com organization: Institute of Urban and Rural Construction, Hebei Agricultural University, Hebei Province, China – sequence: 3 givenname: Mohammad surname: Khishe fullname: Khishe, Mohammad email: m_khishe@alumni.iust.ac.ir organization: Department of Electrical Engineering, Imam Khomeini Marine Science University, Nowshahr, Iran – sequence: 4 givenname: Mokhtar surname: Mohammadi fullname: Mohammadi, Mokhtar email: mukhtar@lfu.edu.krd organization: Department of Information Technology, College of Engineering and Computer Science, Lebanese French University, Kurdistan Region, Iraq – sequence: 5 givenname: Adil Hussein surname: Mohammed fullname: Mohammed, Adil Hussein email: adil.mohammed@cihanuniversity.edu.iq organization: Department of Communication and Computer Engineering, Faculty of Engineering, Cihan University-Erbil, Kurdistan Region, Iraq |
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| Keywords | Solar cell Niching concept Chimp optimization algorithm RN-ChOA Photovoltaic modules |
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| Snippet | •A niching concept is inspired to enhance the original ChOA.•RN-ChOA proposes a novel constraint handling technique.•The RN-ChOA is applied to estimate... Researchers are becoming increasingly interested in studying how to accurately estimate the parameters of solar PV models. In this regard, this paper proposes... |
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| SubjectTerms | Algorithms Biogeography Chimp optimization algorithm Constraint modelling Crystal structure Crystallinity Irradiance Machine learning Niching concept Optimization algorithms Parameter estimation Parameter identification Parameter robustness Particle swarm optimization Photovoltaic cells Photovoltaic modules Photovoltaics RN-ChOA Robustness Solar cell Solar energy |
| Title | Solar photovoltaic model parameter identification using robust niching chimp optimization |
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