This paper presents a novel approach that simultaneously enables photovoltaic(PV)inversion and flexible arc suppression during single-phase grounding faults.Inverters compensate for ground currents through an arc-elim...This paper presents a novel approach that simultaneously enables photovoltaic(PV)inversion and flexible arc suppression during single-phase grounding faults.Inverters compensate for ground currents through an arc-elimination function,while outputting a PV direct current(DC)power supply.This method effectively reduces the residual grounding current.To reduce the dependence of the arc-suppression performance on accurate compensation current-injection models,an adaptive fuzzy neural network imitating a sliding mode controller was designed.An online adaptive adjustment law for network parameters was developed,based on the Lyapunov stability theorem,to improve the robustness of the inverter to fault and connection locations.Furthermore,a new arc-suppression control exit strategy is proposed to allow a zerosequence voltage amplitude to quickly and smoothly track a target value by controlling the nonlinear decrease in current and reducing the regulation time.Simulation results showed that the proposed method can effectively achieve fast arc suppression and reduce the fault impact current in single-phase grounding faults.Compared to other methods,the proposed method can generate a lower residual grounding current and maintain good arc-suppression performance under different transition resistances and fault locations.展开更多
基金the Natural Science Foundation of Fujian,China(No.2021J01633).
文摘This paper presents a novel approach that simultaneously enables photovoltaic(PV)inversion and flexible arc suppression during single-phase grounding faults.Inverters compensate for ground currents through an arc-elimination function,while outputting a PV direct current(DC)power supply.This method effectively reduces the residual grounding current.To reduce the dependence of the arc-suppression performance on accurate compensation current-injection models,an adaptive fuzzy neural network imitating a sliding mode controller was designed.An online adaptive adjustment law for network parameters was developed,based on the Lyapunov stability theorem,to improve the robustness of the inverter to fault and connection locations.Furthermore,a new arc-suppression control exit strategy is proposed to allow a zerosequence voltage amplitude to quickly and smoothly track a target value by controlling the nonlinear decrease in current and reducing the regulation time.Simulation results showed that the proposed method can effectively achieve fast arc suppression and reduce the fault impact current in single-phase grounding faults.Compared to other methods,the proposed method can generate a lower residual grounding current and maintain good arc-suppression performance under different transition resistances and fault locations.
