Large scale photovoltaic array fault diagnosis for optimized solar cell parameters extracted by heuristic evolutionary algorithm

This paper investigates the use of metaheuristic evolutionary algorithms to increase simulation accuracy of faulted large scale PV systems. The selected algorithm has been utilized innovatively to extract the internal parameters of the solar cell in fault conditions. PV power plants are subjected to faults and failures typically which requires fast and precise diagnosis. For large scale PV plant, fault diagnosis is expensive due shutdown periods and maintenance cost. Existing simulation based analysis in MATLAB/Simulink uses the predefined modules model without consideration of environmental factors such as aging effect and dust. This paper shows the added accuracy to the simulation results based on experimental extraction of PV modules. The developed model have been compared to experimental results and existing MATLAB model under normal and fault conditions.