A New Controller to Enhance PV System Performance Based on Neural Network
In recent years, a radical increase of photovoltaic (PV) power generators installation took place because of increased efficiency of solar cells, as well as the growth of manufacturing technology of solar panels. This paper shows the operation and modeling of photovoltaic systems, particularly desig...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Academy Publishing Center
2017-06-01
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| Series: | Renewable Energy and Sustainable Development |
| Subjects: | |
| Online Access: | http://apc.aast.edu/ojs/index.php/RESD/article/view/190 |
| _version_ | 1797258819364978688 |
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| author | Roshdy A AbdelRassoul Yosra Ali Mohamed Saad Zaghloul |
| author_facet | Roshdy A AbdelRassoul Yosra Ali Mohamed Saad Zaghloul |
| author_sort | Roshdy A AbdelRassoul |
| collection | DOAJ |
| description | In recent years, a radical increase of photovoltaic (PV) power generators installation took place because of increased efficiency of solar cells, as well as the growth of manufacturing technology of solar panels. This paper shows the operation and modeling of photovoltaic systems, particularly designing neural controller to control the system. Neural controller is optimized using particle swarm optimization (PSO) leads to getting the best performance of the designed PV system. Using neural network the maximum overshoot and rise time obtained become 0.00001% and 0.1798 seconds, respectively also this paper introduce a comparison between some kind of controller for PV system.<span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: Calibri; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-EG;">In recent years, a radical increase of photovoltaic (PV) power generators installation took place because of increased efficiency of solar cells, as well as the growth of manufacturing technology of solar panels. This paper shows the operation and modeling of photovoltaic systems, particularly designing neural controller to control the system.</span><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: Calibri; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;"> Neural controller is optimized using particle swarm optimization (PSO) leads to getting the best performance of the designed PV system. Using neural network the maximum overshoot and rise time obtained become <span style="color: #1d2129; background-image: initial; background-attachment: initial; background-size: initial; background-origin: initial; background-clip: initial; background-position: initial; background-repeat: initial;">0.00001</span>% and <span style="color: #1d2129; background-image: initial; background-attachment: initial; background-size: initial; background-origin: initial; background-clip: initial; background-position: initial; background-repeat: initial;">0.1798 </span>seconds, respectively also this paper introduce a comparison between some kind of controller for PV system.</span> |
| first_indexed | 2024-03-12T01:39:57Z |
| format | Article |
| id | doaj.art-26a780ef2e264dd68f73345e1a50b9e2 |
| institution | Directory Open Access Journal |
| issn | 2356-8518 2356-8569 |
| language | English |
| last_indexed | 2024-04-24T22:59:35Z |
| publishDate | 2017-06-01 |
| publisher | Academy Publishing Center |
| record_format | Article |
| series | Renewable Energy and Sustainable Development |
| spelling | doaj.art-26a780ef2e264dd68f73345e1a50b9e22024-03-17T15:35:47ZengAcademy Publishing CenterRenewable Energy and Sustainable Development2356-85182356-85692017-06-013222423310.21622/resd.2017.03.2.224116A New Controller to Enhance PV System Performance Based on Neural NetworkRoshdy A AbdelRassoul0Yosra Ali1Mohamed Saad Zaghloul2AASTAASTAASTIn recent years, a radical increase of photovoltaic (PV) power generators installation took place because of increased efficiency of solar cells, as well as the growth of manufacturing technology of solar panels. This paper shows the operation and modeling of photovoltaic systems, particularly designing neural controller to control the system. Neural controller is optimized using particle swarm optimization (PSO) leads to getting the best performance of the designed PV system. Using neural network the maximum overshoot and rise time obtained become 0.00001% and 0.1798 seconds, respectively also this paper introduce a comparison between some kind of controller for PV system.<span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: Calibri; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-EG;">In recent years, a radical increase of photovoltaic (PV) power generators installation took place because of increased efficiency of solar cells, as well as the growth of manufacturing technology of solar panels. This paper shows the operation and modeling of photovoltaic systems, particularly designing neural controller to control the system.</span><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: Calibri; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;"> Neural controller is optimized using particle swarm optimization (PSO) leads to getting the best performance of the designed PV system. Using neural network the maximum overshoot and rise time obtained become <span style="color: #1d2129; background-image: initial; background-attachment: initial; background-size: initial; background-origin: initial; background-clip: initial; background-position: initial; background-repeat: initial;">0.00001</span>% and <span style="color: #1d2129; background-image: initial; background-attachment: initial; background-size: initial; background-origin: initial; background-clip: initial; background-position: initial; background-repeat: initial;">0.1798 </span>seconds, respectively also this paper introduce a comparison between some kind of controller for PV system.</span>http://apc.aast.edu/ojs/index.php/RESD/article/view/190particle swarm optimization, neural network and photovoltaic |
| spellingShingle | Roshdy A AbdelRassoul Yosra Ali Mohamed Saad Zaghloul A New Controller to Enhance PV System Performance Based on Neural Network Renewable Energy and Sustainable Development particle swarm optimization, neural network and photovoltaic |
| title | A New Controller to Enhance PV System Performance Based on Neural Network |
| title_full | A New Controller to Enhance PV System Performance Based on Neural Network |
| title_fullStr | A New Controller to Enhance PV System Performance Based on Neural Network |
| title_full_unstemmed | A New Controller to Enhance PV System Performance Based on Neural Network |
| title_short | A New Controller to Enhance PV System Performance Based on Neural Network |
| title_sort | new controller to enhance pv system performance based on neural network |
| topic | particle swarm optimization, neural network and photovoltaic |
| url | http://apc.aast.edu/ojs/index.php/RESD/article/view/190 |
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