An Improved Partial Shading Detection Strategy Based on Chimp Optimization Algorithm to Find Global Maximum Power Point of Solar Array System
A PV system’s operation highly depends on weather conditions. In case of varying irradiances or load changes, there is a power mismatch between various modules of the PV array. This power mismatch causes instability in the output of the PV system and deteriorates the overall system efficiency. To ov...
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| Format: | Article |
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MDPI AG
2022-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/4/1549 |
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| author | Muqaddas Elahi Hafiz Muhammad Ashraf Chul-Hwan Kim |
| author_facet | Muqaddas Elahi Hafiz Muhammad Ashraf Chul-Hwan Kim |
| author_sort | Muqaddas Elahi |
| collection | DOAJ |
| description | A PV system’s operation highly depends on weather conditions. In case of varying irradiances or load changes, there is a power mismatch between various modules of the PV array. This power mismatch causes instability in the output of the PV system and deteriorates the overall system efficiency. To overcome instability and lower efficiency problems, and to extract maximum power from the PV system, various maximum power point tracking (MPPT) techniques are employed. The success of these techniques depends on the identification of the actual operating conditions of the system. This article proposes a hybrid maximum power point tracking (MPPT) technique that is capable of efficiently differentiating between uniform irradiance, non-uniform irradiance, and load variations on the PV system. Based on the identified operating conditions, the proposed method uses modified perturb and observe (Modified P&O) to cope with uniform irradiance variations and chimp optimization algorithms (ChOA) for non-uniform conditions to track the oscillation free maximum power-point. The proposed method is implemented and verified using a 4 × 3 PV array model in MATLAB Simulink software. Different cases of uniformly changing irradiance and non-uniformly changing irradiance are applied to test the performance of the proposed hybrid technique. The load varying conditions are performed by applying a variable load resistor. The authenticity of the proposed hybrid technique is critically evaluated against the well-known and most widely used optimization techniques of modified perturb and observe (Modified P&O), particle swarm optimization (PSO), flower pollination algorithm (FPA), and grey wolf optimization (GWO). The results demonstrate the superiority of the proposed technique in oscillation-free tracking of global maximum power point (GMPP) in a minimum tracking time of 0.4 s and 0.15 s, and steady-state MPPT efficiency of 96.92% and 99.54% under uniform and non-uniform irradiance conditions, respectively. |
| first_indexed | 2024-03-09T22:03:16Z |
| format | Article |
| id | doaj.art-274488cbdee5421c92b31bc7cf6c42da |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T22:03:16Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-274488cbdee5421c92b31bc7cf6c42da2023-11-23T19:45:57ZengMDPI AGEnergies1996-10732022-02-01154154910.3390/en15041549An Improved Partial Shading Detection Strategy Based on Chimp Optimization Algorithm to Find Global Maximum Power Point of Solar Array SystemMuqaddas Elahi0Hafiz Muhammad Ashraf1Chul-Hwan Kim2Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, KoreaDepartment of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, KoreaDepartment of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, KoreaA PV system’s operation highly depends on weather conditions. In case of varying irradiances or load changes, there is a power mismatch between various modules of the PV array. This power mismatch causes instability in the output of the PV system and deteriorates the overall system efficiency. To overcome instability and lower efficiency problems, and to extract maximum power from the PV system, various maximum power point tracking (MPPT) techniques are employed. The success of these techniques depends on the identification of the actual operating conditions of the system. This article proposes a hybrid maximum power point tracking (MPPT) technique that is capable of efficiently differentiating between uniform irradiance, non-uniform irradiance, and load variations on the PV system. Based on the identified operating conditions, the proposed method uses modified perturb and observe (Modified P&O) to cope with uniform irradiance variations and chimp optimization algorithms (ChOA) for non-uniform conditions to track the oscillation free maximum power-point. The proposed method is implemented and verified using a 4 × 3 PV array model in MATLAB Simulink software. Different cases of uniformly changing irradiance and non-uniformly changing irradiance are applied to test the performance of the proposed hybrid technique. The load varying conditions are performed by applying a variable load resistor. The authenticity of the proposed hybrid technique is critically evaluated against the well-known and most widely used optimization techniques of modified perturb and observe (Modified P&O), particle swarm optimization (PSO), flower pollination algorithm (FPA), and grey wolf optimization (GWO). The results demonstrate the superiority of the proposed technique in oscillation-free tracking of global maximum power point (GMPP) in a minimum tracking time of 0.4 s and 0.15 s, and steady-state MPPT efficiency of 96.92% and 99.54% under uniform and non-uniform irradiance conditions, respectively.https://www.mdpi.com/1996-1073/15/4/1549chimp optimization algorithm (ChOA)global maximum power point tracking (GMPPT)load variationsmodified perturb and observepartial shading conditionsphotovoltaic system |
| spellingShingle | Muqaddas Elahi Hafiz Muhammad Ashraf Chul-Hwan Kim An Improved Partial Shading Detection Strategy Based on Chimp Optimization Algorithm to Find Global Maximum Power Point of Solar Array System Energies chimp optimization algorithm (ChOA) global maximum power point tracking (GMPPT) load variations modified perturb and observe partial shading conditions photovoltaic system |
| title | An Improved Partial Shading Detection Strategy Based on Chimp Optimization Algorithm to Find Global Maximum Power Point of Solar Array System |
| title_full | An Improved Partial Shading Detection Strategy Based on Chimp Optimization Algorithm to Find Global Maximum Power Point of Solar Array System |
| title_fullStr | An Improved Partial Shading Detection Strategy Based on Chimp Optimization Algorithm to Find Global Maximum Power Point of Solar Array System |
| title_full_unstemmed | An Improved Partial Shading Detection Strategy Based on Chimp Optimization Algorithm to Find Global Maximum Power Point of Solar Array System |
| title_short | An Improved Partial Shading Detection Strategy Based on Chimp Optimization Algorithm to Find Global Maximum Power Point of Solar Array System |
| title_sort | improved partial shading detection strategy based on chimp optimization algorithm to find global maximum power point of solar array system |
| topic | chimp optimization algorithm (ChOA) global maximum power point tracking (GMPPT) load variations modified perturb and observe partial shading conditions photovoltaic system |
| url | https://www.mdpi.com/1996-1073/15/4/1549 |
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