Binary Particle Swarm Optimization for Optimization of Photovoltaic Generators in Radial Distribution Systems Using Probabilistic Load Flow

Abstract

This article shows that technical constraints must be considered in radial distribution networks, where voltage regulation is one of the primary problems in distributed generation photovoltaic systems. Loads and distributed generation production are modeled as random variables. Results prove that the proposed method can be applied for keeping voltages within desired limits at all load buses of a photovoltaic grid-connected system. To evaluate the performance of a photovoltaic system, this article has developed a probabilistic model that takes into account the random nature of solar irradiance and load. This work introduces a new method utilizing discrete particle swarm optimization and probabilistic radial load flow. Computer simulation reduction demonstrates better performance of the new probabilistic load flow in comparison to the Monte Carlo simulation. Acceptable solutions are reached in a smaller number of iterations. Therefore, convergence is rapidly attained, and computational cost is low enough for that required for Monte Carlo simulation.