Integrating small and large-scale photovoltaic(PV)solar systems into electrical distribution systems has become mandatory due to increased electricity bills and the concern for limiting greenhouse gases.However,the re...Integrating small and large-scale photovoltaic(PV)solar systems into electrical distribution systems has become mandatory due to increased electricity bills and the concern for limiting greenhouse gases.However,the reliable and efficient operation of PV-based distribution systems can be confronted by the intermittence and high variability of solar sources and their consequential faults.In this regard,this article suggests a moderated fault-clearing strategy based on the incremental conductance–maximum power point tracking(IC–MPPT)technique and artificial neural networks(ANNs)to enhance fault detection,localization,and restoration pro-cesses in PV-based distribution systems.The proposed strategy leverages IC–MPPT to ensure optimal power generation from the PV solar system,even in the presence of faults.By tracking the maximum power point,the algorithm maintains the performance of the system and mitigates against the impact of faults on the output power.Furthermore,an ANN is employed to improve fault detec-tion and localization accuracy.The developed ANN-based moderated fault-clearing strategy is trained using historical data and fault scenarios,enabling it to recognize fault patterns and make informed decisions through extensive simulations and comparisons with traditional fault-clearing methods.To accomplish this study,benchmarks in PV-based distribution systems are constructed and em-ployed using the MATLAB®/Simulink®software package.Moreover,to validate the efficacy of the developed ANN-based moderated fault-clearing strategy,a real case study of a 1-MW PV-based distribution system in an industrial field located in Giza governorate,Egypt,is tested and investigated.The obtained results demonstrate the effectiveness of the IC–MPPT and ANN-based moderated fault-clearing strategy in achieving faster fault detection,precise fault localization,and efficient restoration in PV solar-based dis-tribution systems while preserving maximum power extraction under small and large system disturbances.Furthermore,IC–MPPT based on an ANN achieves an average power of 98.556 kW and 299.632 kWh energy availability,whereas the IC–MPPT based on a pro-portional–integral controller achieves 95.7996 kW and 283.4036 kWh,and the classic perturb-and-observe MPPT algorithm achieves 92.2657 kW and 276.8014 kWh.展开更多
文摘Integrating small and large-scale photovoltaic(PV)solar systems into electrical distribution systems has become mandatory due to increased electricity bills and the concern for limiting greenhouse gases.However,the reliable and efficient operation of PV-based distribution systems can be confronted by the intermittence and high variability of solar sources and their consequential faults.In this regard,this article suggests a moderated fault-clearing strategy based on the incremental conductance–maximum power point tracking(IC–MPPT)technique and artificial neural networks(ANNs)to enhance fault detection,localization,and restoration pro-cesses in PV-based distribution systems.The proposed strategy leverages IC–MPPT to ensure optimal power generation from the PV solar system,even in the presence of faults.By tracking the maximum power point,the algorithm maintains the performance of the system and mitigates against the impact of faults on the output power.Furthermore,an ANN is employed to improve fault detec-tion and localization accuracy.The developed ANN-based moderated fault-clearing strategy is trained using historical data and fault scenarios,enabling it to recognize fault patterns and make informed decisions through extensive simulations and comparisons with traditional fault-clearing methods.To accomplish this study,benchmarks in PV-based distribution systems are constructed and em-ployed using the MATLAB®/Simulink®software package.Moreover,to validate the efficacy of the developed ANN-based moderated fault-clearing strategy,a real case study of a 1-MW PV-based distribution system in an industrial field located in Giza governorate,Egypt,is tested and investigated.The obtained results demonstrate the effectiveness of the IC–MPPT and ANN-based moderated fault-clearing strategy in achieving faster fault detection,precise fault localization,and efficient restoration in PV solar-based dis-tribution systems while preserving maximum power extraction under small and large system disturbances.Furthermore,IC–MPPT based on an ANN achieves an average power of 98.556 kW and 299.632 kWh energy availability,whereas the IC–MPPT based on a pro-portional–integral controller achieves 95.7996 kW and 283.4036 kWh,and the classic perturb-and-observe MPPT algorithm achieves 92.2657 kW and 276.8014 kWh.
