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REACTIVE POWER CONTROL OF THREE-PHASE GRID-CONNECTED PV
SYSTEM DURING GRID FAULTS USING TAKAGI-SUGENO-KANG
PROBABILISTIC FUZZY NEURAL NETWORK CONTROL
ABSTRACT
An intelligent controller based on Takagi Sugeno-Kang type probabilistic fuzzy neural
network with asymmetric membership function (TSKPFNN-AMF) is developed in this study for
the reactive and active power control of a three-phase grid-connected photovoltaic (PV) system
during grid faults. The inverter of the three-phase grid-connected PV system should provide a
proper ratio of reactive power to meet the low voltage ride through (LVRT) regulations and
control the output current without exceeding the maximum current limit simultaneously during
grid faults. Therefore, the proposed intelligent controller regulates the value of reactive power to
a new reference value which complies with the regulations of LVRT under grid faults. Moreover,
a dual mode operation control method of the converter and inverter of the three-phase grid-
connected PV system is designed to eliminate the fluctuation of DC-link bus voltage under grid
faults. Furthermore, the network structure, online learning algorithm, and convergence analysis
of the TSKPFNN-AMF are described in detail. Finally, some experimental results are illustrated
to show the effectiveness of the proposed control for the three phase grid-connected PV system.

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Reactive power control of three phase grid-connected pv system during grid faults using takagi-sugeno-kang probabilistic fuzzy neural network control

  • 1. REACTIVE POWER CONTROL OF THREE-PHASE GRID-CONNECTED PV SYSTEM DURING GRID FAULTS USING TAKAGI-SUGENO-KANG PROBABILISTIC FUZZY NEURAL NETWORK CONTROL ABSTRACT An intelligent controller based on Takagi Sugeno-Kang type probabilistic fuzzy neural network with asymmetric membership function (TSKPFNN-AMF) is developed in this study for the reactive and active power control of a three-phase grid-connected photovoltaic (PV) system during grid faults. The inverter of the three-phase grid-connected PV system should provide a proper ratio of reactive power to meet the low voltage ride through (LVRT) regulations and control the output current without exceeding the maximum current limit simultaneously during grid faults. Therefore, the proposed intelligent controller regulates the value of reactive power to a new reference value which complies with the regulations of LVRT under grid faults. Moreover, a dual mode operation control method of the converter and inverter of the three-phase grid- connected PV system is designed to eliminate the fluctuation of DC-link bus voltage under grid faults. Furthermore, the network structure, online learning algorithm, and convergence analysis of the TSKPFNN-AMF are described in detail. Finally, some experimental results are illustrated to show the effectiveness of the proposed control for the three phase grid-connected PV system.