TY - JOUR
T1 - Voltage Restoration Control for Microgrid with Recurrent Wavelet Petri Fuzzy Neural Network
AU - Lin, Faa Jeng
AU - Liao, Jen Chung
AU - Chen, Cheng I.
AU - Chen, Pin Rong
AU - Zhang, Yu Ming
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Battery energy storage system
KW - low voltage ride through
KW - microgrid
KW - recurrent wavelet petri fuzzy neural network
KW - voltage restoration control
UR - http://www.scopus.com/inward/record.url?scp=85124098120&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2022.3147357
DO - 10.1109/ACCESS.2022.3147357
M3 - 期刊論文
AN - SCOPUS:85124098120
SN - 2169-3536
VL - 10
SP - 12510
EP - 12529
JO - IEEE Access
JF - IEEE Access
ER -