Bacterial Foraging Optimization Approach to Parameter Extraction of a Photovoltaic Module

This paper presents a new parameter extraction method for photovoltaic (PV) modules exploiting Bacterial Foraging Optimization (BFO) technique. In a PV system, validation of the model of a PV module with correctly chosen parameters is essential. An efficient parameter extraction method is required to estimate the parameters of PV module. Although, a number of parameter extraction methods are available in literature but there is a need to explore parameter extraction methods that could extract globally optimized parameters in changing weather conditions. One of the recent evolutionary computing approaches called BFO exhibits global optimization performance. Therefore, we employ BFO for extraction of parameters of a PV module. The proposed BFO-based parameter extraction method has been tested for different types of PV modules at different test conditions. Analyzing both the simulation and experimental results obtained using BFO; it is found that the module parameters are more accurate compared to that of Newton-Raphson, particle swarm optimization, and enhanced simulated annealing methods.