Reactive Power Control of Single-Stage Three-Phase Photovoltaic System during Grid Faults Using Recurrent Fuzzy Cerebellar Model Articulation Neural Network
This study presents a new active and reactive power control scheme for a single-stage three-phase grid-connected photovoltaic (PV) system during grid faults. The presented PV system utilizes a single-stage three-phase current-controlled voltage-source inverter to achieve the maximum power point trac...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | International Journal of Photoenergy |
| Online Access: | http://dx.doi.org/10.1155/2014/760743 |
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| author | Faa-Jeng Lin Kuang-Chin Lu Hsuan-Yu Lee |
| author_facet | Faa-Jeng Lin Kuang-Chin Lu Hsuan-Yu Lee |
| author_sort | Faa-Jeng Lin |
| collection | DOAJ |
| description | This study presents a new active and reactive power control scheme for a single-stage three-phase grid-connected photovoltaic (PV) system during grid faults. The presented PV system utilizes a single-stage three-phase current-controlled voltage-source inverter to achieve the maximum power point tracking (MPPT) control of the PV panel with the function of low voltage ride through (LVRT). Moreover, a formula based on positive sequence voltage for evaluating the percentage of voltage sag is derived to determine the ratio of the injected reactive current to satisfy the LVRT regulations. To reduce the risk of overcurrent during LVRT operation, a current limit is predefined for the injection of reactive current. Furthermore, the control of active and reactive power is designed using a two-dimensional recurrent fuzzy cerebellar model articulation neural network (2D-RFCMANN). In addition, the online learning laws of 2D-RFCMANN are derived according to gradient descent method with varied learning-rate coefficients for network parameters to assure the convergence of the tracking error. Finally, some experimental tests are realized to validate the effectiveness of the proposed control scheme. |
| format | Article |
| id | doaj-art-b139942dc4194754a28742ff2cefb052 |
| institution | Kabale University |
| issn | 1110-662X 1687-529X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Photoenergy |
| spelling | doaj-art-b139942dc4194754a28742ff2cefb0522025-02-03T06:01:55ZengWileyInternational Journal of Photoenergy1110-662X1687-529X2014-01-01201410.1155/2014/760743760743Reactive Power Control of Single-Stage Three-Phase Photovoltaic System during Grid Faults Using Recurrent Fuzzy Cerebellar Model Articulation Neural NetworkFaa-Jeng Lin0Kuang-Chin Lu1Hsuan-Yu Lee2Department of Electrical Engineering, National Central University, Chungli 320, TaiwanDepartment of Electrical Engineering, National Central University, Chungli 320, TaiwanDepartment of Electrical Engineering, National Central University, Chungli 320, TaiwanThis study presents a new active and reactive power control scheme for a single-stage three-phase grid-connected photovoltaic (PV) system during grid faults. The presented PV system utilizes a single-stage three-phase current-controlled voltage-source inverter to achieve the maximum power point tracking (MPPT) control of the PV panel with the function of low voltage ride through (LVRT). Moreover, a formula based on positive sequence voltage for evaluating the percentage of voltage sag is derived to determine the ratio of the injected reactive current to satisfy the LVRT regulations. To reduce the risk of overcurrent during LVRT operation, a current limit is predefined for the injection of reactive current. Furthermore, the control of active and reactive power is designed using a two-dimensional recurrent fuzzy cerebellar model articulation neural network (2D-RFCMANN). In addition, the online learning laws of 2D-RFCMANN are derived according to gradient descent method with varied learning-rate coefficients for network parameters to assure the convergence of the tracking error. Finally, some experimental tests are realized to validate the effectiveness of the proposed control scheme.http://dx.doi.org/10.1155/2014/760743 |
| spellingShingle | Faa-Jeng Lin Kuang-Chin Lu Hsuan-Yu Lee Reactive Power Control of Single-Stage Three-Phase Photovoltaic System during Grid Faults Using Recurrent Fuzzy Cerebellar Model Articulation Neural Network International Journal of Photoenergy |
| title | Reactive Power Control of Single-Stage Three-Phase Photovoltaic System during Grid Faults Using Recurrent Fuzzy Cerebellar Model Articulation Neural Network |
| title_full | Reactive Power Control of Single-Stage Three-Phase Photovoltaic System during Grid Faults Using Recurrent Fuzzy Cerebellar Model Articulation Neural Network |
| title_fullStr | Reactive Power Control of Single-Stage Three-Phase Photovoltaic System during Grid Faults Using Recurrent Fuzzy Cerebellar Model Articulation Neural Network |
| title_full_unstemmed | Reactive Power Control of Single-Stage Three-Phase Photovoltaic System during Grid Faults Using Recurrent Fuzzy Cerebellar Model Articulation Neural Network |
| title_short | Reactive Power Control of Single-Stage Three-Phase Photovoltaic System during Grid Faults Using Recurrent Fuzzy Cerebellar Model Articulation Neural Network |
| title_sort | reactive power control of single stage three phase photovoltaic system during grid faults using recurrent fuzzy cerebellar model articulation neural network |
| url | http://dx.doi.org/10.1155/2014/760743 |
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