Gravitational search algorithm with linearly decreasing gravitational constant for parameter estimation of photovoltaic cells

Due to undeniable environmental, economical and technical reasons, renewable energy-based power generation in electric power systems is continually increasing. Among renewables, photovoltaic (PV) power generation is a viable and attractive choice. For modeling photovoltaic systems, accurate modeling of PV cells is a must. PV cells are often modeled as single diode or double diode models. The process of estimating circuit model parameters of PV cells based on datasheet information or experimental I–V measurements is called PV cell parameter estimation problem and is being frequently researched in the last three decades. The research effort is being put to achieve more accurate circuit model parameters. In this paper, gravitational search algorithm (GSA) with linearly decreasing gravitational constant is proposed for solving PV cell parameter estimation problem. The results of application of the proposed GSA to PV cell parameter estimation problem vividly show its outperformance over GSA with constant gravitational constant, GSA with exponentially decreasing gravitational constant, genetic algorithm, evolutionary programming and Newton algorithm.