Cost of Energy Losses Analysis Using a Hybrid Evolutionary Programming-Firefly Algorithm for Distributed Generation Installation

Abstract

This paper presents the Hybrid Evolutionary Programming-Firefly Algorithm (EPFA) technique for the cost of energy losses analysis of distributed generation (DG). In this study, EPFA is developed to determine the optimal size of DG while considering the system’s energy losses. EPFA is developed based on embedded Firefly Algorithm (FA) properties into the classical EP technique. The objective of this study was to reduce the cost of energy losses while increasing the voltage profile and minimizing distribution system losses between the different operational strategies and types of DG. In this study, the analysis was done by considering DG type 1 and DG type 2. The proposed technique was tested using the IEEE 69- bus test system. In terms of economic concerns, power system planners can use the information acquired for utility planning to determine the right location and capacity of DG. Finally, the proposed method can determine the appropriate DG sizing while reducing the cost of energy losses and total losses in the system, based on the simulation results.