A Hybrid Maximum Power Point Tracking Method without Oscillations in Steady-State for Photovoltaic Energy Systems
This paper proposes a hybrid maximum power point tracking (MPPT) method with zero oscillation in steady-state by combining genetic algorithm (GA) and perturbation and observation (P&O) method. The proposed MPPT can track the global maximum power point (GMPP) fast for a photovoltaic (PV) system e...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/14/18/5590 |
| _version_ | 1797519485401300992 |
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| author | Chih-Chiang Hua Yu-Jun Zhan |
| author_facet | Chih-Chiang Hua Yu-Jun Zhan |
| author_sort | Chih-Chiang Hua |
| collection | DOAJ |
| description | This paper proposes a hybrid maximum power point tracking (MPPT) method with zero oscillation in steady-state by combining genetic algorithm (GA) and perturbation and observation (P&O) method. The proposed MPPT can track the global maximum power point (GMPP) fast for a photovoltaic (PV) system even under partial shaded conditions (PSC). The oscillations around the GMPP are eliminated and the power loss can be reduced significantly. In addition, the proposed MPPT can make the PV system operate at the highest efficiencies under various atmospheric conditions. During the MPP tracking, the system will oscillate around the MPPs, resulting in unnecessary power loss. To solve the problem, the artificial intelligence (AI) algorithms, such as PSO, Bee Colony optimization, GA, etc., were developed to deal with this issue. However, the problem with the AI algorithm is that the time for convergence may be too long if the range of the MPP search space is large. In addition, if the atmospheric conditions change fast, the PV system may operate at or close to the local maximum power points (LMPPs) for a long time. In this paper, a method combining the P&O’s fast tracking and GA’s GMPP tracking ability is proposed. The proposed system can stop the oscillations as soon as the GMPP is found, thus minimizing the power loss due to oscillations. The proposed MPPT can achieve superior performance while maintaining the simplicity of implementation. Finally, the simulation and experimental results are presented to demonstrate the feasibility of the proposed system. |
| first_indexed | 2024-03-10T07:43:27Z |
| format | Article |
| id | doaj.art-5c7add165680497fb5bcf7c0adb45c31 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T07:43:27Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-5c7add165680497fb5bcf7c0adb45c312023-11-22T12:49:57ZengMDPI AGEnergies1996-10732021-09-011418559010.3390/en14185590A Hybrid Maximum Power Point Tracking Method without Oscillations in Steady-State for Photovoltaic Energy SystemsChih-Chiang Hua0Yu-Jun Zhan1Department of Electrical Engineering, National Yunlin University of Science and Technology, Douliou 640, TaiwanDepartment of Electrical Engineering, National Yunlin University of Science and Technology, Douliou 640, TaiwanThis paper proposes a hybrid maximum power point tracking (MPPT) method with zero oscillation in steady-state by combining genetic algorithm (GA) and perturbation and observation (P&O) method. The proposed MPPT can track the global maximum power point (GMPP) fast for a photovoltaic (PV) system even under partial shaded conditions (PSC). The oscillations around the GMPP are eliminated and the power loss can be reduced significantly. In addition, the proposed MPPT can make the PV system operate at the highest efficiencies under various atmospheric conditions. During the MPP tracking, the system will oscillate around the MPPs, resulting in unnecessary power loss. To solve the problem, the artificial intelligence (AI) algorithms, such as PSO, Bee Colony optimization, GA, etc., were developed to deal with this issue. However, the problem with the AI algorithm is that the time for convergence may be too long if the range of the MPP search space is large. In addition, if the atmospheric conditions change fast, the PV system may operate at or close to the local maximum power points (LMPPs) for a long time. In this paper, a method combining the P&O’s fast tracking and GA’s GMPP tracking ability is proposed. The proposed system can stop the oscillations as soon as the GMPP is found, thus minimizing the power loss due to oscillations. The proposed MPPT can achieve superior performance while maintaining the simplicity of implementation. Finally, the simulation and experimental results are presented to demonstrate the feasibility of the proposed system.https://www.mdpi.com/1996-1073/14/18/5590PV systemmaximum power point tracking (MPPT)genetic algorithm (GA)partial shaded conditions (PSC) |
| spellingShingle | Chih-Chiang Hua Yu-Jun Zhan A Hybrid Maximum Power Point Tracking Method without Oscillations in Steady-State for Photovoltaic Energy Systems Energies PV system maximum power point tracking (MPPT) genetic algorithm (GA) partial shaded conditions (PSC) |
| title | A Hybrid Maximum Power Point Tracking Method without Oscillations in Steady-State for Photovoltaic Energy Systems |
| title_full | A Hybrid Maximum Power Point Tracking Method without Oscillations in Steady-State for Photovoltaic Energy Systems |
| title_fullStr | A Hybrid Maximum Power Point Tracking Method without Oscillations in Steady-State for Photovoltaic Energy Systems |
| title_full_unstemmed | A Hybrid Maximum Power Point Tracking Method without Oscillations in Steady-State for Photovoltaic Energy Systems |
| title_short | A Hybrid Maximum Power Point Tracking Method without Oscillations in Steady-State for Photovoltaic Energy Systems |
| title_sort | hybrid maximum power point tracking method without oscillations in steady state for photovoltaic energy systems |
| topic | PV system maximum power point tracking (MPPT) genetic algorithm (GA) partial shaded conditions (PSC) |
| url | https://www.mdpi.com/1996-1073/14/18/5590 |
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