A Novel Maximum Power Point Tracking Algorithm Based on Glowworm Swarm Optimization for Photovoltaic Systems
In order to extract the maximum power from PV system, the maximum power point tracking (MPPT) technology has always been applied in PV system. At present, various MPPT control methods have been presented. The perturb and observe (P&O) and conductance increment methods are the most popular and wi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | International Journal of Photoenergy |
| Online Access: | http://dx.doi.org/10.1155/2016/4910862 |
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| _version_ | 1832558654373494784 |
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| author | Wenhui Hou Yi Jin Changan Zhu Guiqiang Li |
| author_facet | Wenhui Hou Yi Jin Changan Zhu Guiqiang Li |
| author_sort | Wenhui Hou |
| collection | DOAJ |
| description | In order to extract the maximum power from PV system, the maximum power point tracking (MPPT) technology has always been applied in PV system. At present, various MPPT control methods have been presented. The perturb and observe (P&O) and conductance increment methods are the most popular and widely used under the constant irradiance. However, these methods exhibit fluctuations among the maximum power point (MPP). In addition, the changes of the environmental parameters, such as cloud cover, plant shelter, and the building block, will lead to the radiation change and then have a direct effect on the location of MPP. In this paper, a feasible MPPT method is proposed to adapt to the variation of the irradiance. This work applies the glowworm swarm optimization (GSO) algorithm to determine the optimal value of a reference voltage in the PV system. The performance of the proposed GSO algorithm is evaluated by comparing it with the conventional P&O method in terms of tracking speed and accuracy by utilizing MATLAB/SIMULINK. The simulation results demonstrate that the tracking capability of the GSO algorithm is superior to that of the traditional P&O algorithm, particularly under low radiance and sudden mutation irradiance conditions. |
| format | Article |
| id | doaj-art-5548ef6785874bb98921340cbca5c425 |
| institution | Kabale University |
| issn | 1110-662X 1687-529X |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Photoenergy |
| spelling | doaj-art-5548ef6785874bb98921340cbca5c4252025-02-03T01:31:50ZengWileyInternational Journal of Photoenergy1110-662X1687-529X2016-01-01201610.1155/2016/49108624910862A Novel Maximum Power Point Tracking Algorithm Based on Glowworm Swarm Optimization for Photovoltaic SystemsWenhui Hou0Yi Jin1Changan Zhu2Guiqiang Li3School of Engineering Science, University of Science and Technology of China, Hefei 230026, ChinaSchool of Engineering Science, University of Science and Technology of China, Hefei 230026, ChinaSchool of Engineering Science, University of Science and Technology of China, Hefei 230026, ChinaSchool of Engineering Science, University of Science and Technology of China, Hefei 230026, ChinaIn order to extract the maximum power from PV system, the maximum power point tracking (MPPT) technology has always been applied in PV system. At present, various MPPT control methods have been presented. The perturb and observe (P&O) and conductance increment methods are the most popular and widely used under the constant irradiance. However, these methods exhibit fluctuations among the maximum power point (MPP). In addition, the changes of the environmental parameters, such as cloud cover, plant shelter, and the building block, will lead to the radiation change and then have a direct effect on the location of MPP. In this paper, a feasible MPPT method is proposed to adapt to the variation of the irradiance. This work applies the glowworm swarm optimization (GSO) algorithm to determine the optimal value of a reference voltage in the PV system. The performance of the proposed GSO algorithm is evaluated by comparing it with the conventional P&O method in terms of tracking speed and accuracy by utilizing MATLAB/SIMULINK. The simulation results demonstrate that the tracking capability of the GSO algorithm is superior to that of the traditional P&O algorithm, particularly under low radiance and sudden mutation irradiance conditions.http://dx.doi.org/10.1155/2016/4910862 |
| spellingShingle | Wenhui Hou Yi Jin Changan Zhu Guiqiang Li A Novel Maximum Power Point Tracking Algorithm Based on Glowworm Swarm Optimization for Photovoltaic Systems International Journal of Photoenergy |
| title | A Novel Maximum Power Point Tracking Algorithm Based on Glowworm Swarm Optimization for Photovoltaic Systems |
| title_full | A Novel Maximum Power Point Tracking Algorithm Based on Glowworm Swarm Optimization for Photovoltaic Systems |
| title_fullStr | A Novel Maximum Power Point Tracking Algorithm Based on Glowworm Swarm Optimization for Photovoltaic Systems |
| title_full_unstemmed | A Novel Maximum Power Point Tracking Algorithm Based on Glowworm Swarm Optimization for Photovoltaic Systems |
| title_short | A Novel Maximum Power Point Tracking Algorithm Based on Glowworm Swarm Optimization for Photovoltaic Systems |
| title_sort | novel maximum power point tracking algorithm based on glowworm swarm optimization for photovoltaic systems |
| url | http://dx.doi.org/10.1155/2016/4910862 |
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