Voltage Restoration Control for Microgrid With Recurrent Wavelet Petri Fuzzy Neural Network
This study presents a voltage restoration control (VRC) based on battery energy storage system (BESS), which can be used for both supporting power source and voltage compensation. Voltage restoration is an important task for the power control of microgrid during utility disturbances. One of the dist...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9695454/ |
| _version_ | 1798031184864739328 |
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| author | Faa-Jeng Lin Jen-Chung Liao Cheng-I Chen Pin-Rong Chen Yu-Ming Zhang |
| author_facet | Faa-Jeng Lin Jen-Chung Liao Cheng-I Chen Pin-Rong Chen Yu-Ming Zhang |
| author_sort | Faa-Jeng Lin |
| collection | DOAJ |
| description | This study presents a voltage restoration control (VRC) based on battery energy storage system (BESS), which can be used for both supporting power source and voltage compensation. Voltage restoration is an important task for the power control of microgrid during utility disturbances. One of the disturbances is caused by short circuit on power line of the microgrid, which may lead to voltage sag and even blackout of the microgrid system. To tackle this problem, the recurrent wavelet petri fuzzy neural network (RWPFNN) controller is proposed in this study for the VRC of BESS to provide fast control response to mitigate the transient impact. Moreover, to examine the compliance with the requirements of low voltage ride through (LVRT) of the photovoltaic (PV) plant and investigate the performance of the proposed VRC, the microgrid built in Cimei Island in Penghu Archipelago, Taiwan, is investigated. Furthermore, the PV system, the wind turbine generator (WTG) system and the BESS are connected to the same point of common coupling (PCC) with separated step-up transformers in the microgrid. In addition, the diesel generators provide the main power sources and form the isolated microgrid system. Through the hardware in the loop (HIL) mechanism, which is built using OPAL-RT real-time simulator, with two floating-point digital signal processors (DSPs), the effectiveness of proposed intelligent controllers can be verified and demonstrated. |
| first_indexed | 2024-04-11T19:52:18Z |
| format | Article |
| id | doaj.art-232f7f11c7de4844986d98326162f92a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-11T19:52:18Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-232f7f11c7de4844986d98326162f92a2022-12-22T04:06:15ZengIEEEIEEE Access2169-35362022-01-0110125101252910.1109/ACCESS.2022.31473579695454Voltage Restoration Control for Microgrid With Recurrent Wavelet Petri Fuzzy Neural NetworkFaa-Jeng Lin0https://orcid.org/0000-0003-4717-1993Jen-Chung Liao1https://orcid.org/0000-0002-4740-4358Cheng-I Chen2https://orcid.org/0000-0002-2968-2362Pin-Rong Chen3Yu-Ming Zhang4Department of Electrical Engineering, National Central University, Chungli, TaiwanDepartment of Electrical Engineering, National Central University, Chungli, TaiwanDepartment of Electrical Engineering, National Central University, Chungli, TaiwanDepartment of Electrical Engineering, National Central University, Chungli, TaiwanDepartment of Electrical Engineering, National Central University, Chungli, TaiwanThis study presents a voltage restoration control (VRC) based on battery energy storage system (BESS), which can be used for both supporting power source and voltage compensation. Voltage restoration is an important task for the power control of microgrid during utility disturbances. One of the disturbances is caused by short circuit on power line of the microgrid, which may lead to voltage sag and even blackout of the microgrid system. To tackle this problem, the recurrent wavelet petri fuzzy neural network (RWPFNN) controller is proposed in this study for the VRC of BESS to provide fast control response to mitigate the transient impact. Moreover, to examine the compliance with the requirements of low voltage ride through (LVRT) of the photovoltaic (PV) plant and investigate the performance of the proposed VRC, the microgrid built in Cimei Island in Penghu Archipelago, Taiwan, is investigated. Furthermore, the PV system, the wind turbine generator (WTG) system and the BESS are connected to the same point of common coupling (PCC) with separated step-up transformers in the microgrid. In addition, the diesel generators provide the main power sources and form the isolated microgrid system. Through the hardware in the loop (HIL) mechanism, which is built using OPAL-RT real-time simulator, with two floating-point digital signal processors (DSPs), the effectiveness of proposed intelligent controllers can be verified and demonstrated.https://ieeexplore.ieee.org/document/9695454/Battery energy storage systemlow voltage ride throughmicrogridrecurrent wavelet petri fuzzy neural networkvoltage restoration control |
| spellingShingle | Faa-Jeng Lin Jen-Chung Liao Cheng-I Chen Pin-Rong Chen Yu-Ming Zhang Voltage Restoration Control for Microgrid With Recurrent Wavelet Petri Fuzzy Neural Network IEEE Access Battery energy storage system low voltage ride through microgrid recurrent wavelet petri fuzzy neural network voltage restoration control |
| title | Voltage Restoration Control for Microgrid With Recurrent Wavelet Petri Fuzzy Neural Network |
| title_full | Voltage Restoration Control for Microgrid With Recurrent Wavelet Petri Fuzzy Neural Network |
| title_fullStr | Voltage Restoration Control for Microgrid With Recurrent Wavelet Petri Fuzzy Neural Network |
| title_full_unstemmed | Voltage Restoration Control for Microgrid With Recurrent Wavelet Petri Fuzzy Neural Network |
| title_short | Voltage Restoration Control for Microgrid With Recurrent Wavelet Petri Fuzzy Neural Network |
| title_sort | voltage restoration control for microgrid with recurrent wavelet petri fuzzy neural network |
| topic | Battery energy storage system low voltage ride through microgrid recurrent wavelet petri fuzzy neural network voltage restoration control |
| url | https://ieeexplore.ieee.org/document/9695454/ |
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