Optimal assessment of smart grid based photovoltaic cell operational parameters using simulated annealing

Abstract

With the ever-increasing load demand throughout the globe, natural renewable resources integrated into the existing network architecture for sustainable energy production are gaining considerable significance. Photovoltaic (PV) generation systems is one such technique to deal with the worldwide challenge for achieving green energy and low carbon footprint while simultaneously providing emission free electrical power from solar radiations. In this paper, we consider smart grid architecture connecting the end-users and the utility power plant with solar energy sources through an effective power optimization system. Multiple performance criteria associated with solar cell operation are evaluated and analyzed using the simulated annealing algorithm. These objectives considered for optimization include the cell saturation current, photo-generated current, material band gap, cell temperature, annualized life cycle cost, fill factor and cell efficiency. The formulated optimization conditions are specified in terms of two independent variables of cell ambient temperature and cell illumination. Moreover, the adaption of distinct values of short circuit current coefficients on the light originated current is measured. Through extensive simulation experiments, two disparate annealing procedures of fast annealing and Boltzmann annealing are applied coupled with three categories of temperature update schemes, viz. exponential, logarithmic and linear.