Evolutionary Computing Techniques for Distributed Generation: Survey

Abstract

Distributed Generation (DG) refers to the production of electricity from various small-scale energy sources situated near the consumer, rather than centralized power plants. In recent years, there has been a significant focus on integrating DG units into distribution systems. The primary goals of using DG are to enhance the voltage profile, improve voltage stability, and reduce power losses. DG aims to decrease system losses, optimize voltage levels, and increase voltage stability within a power network. Various optimization techniques based on evolutionary computing, such as Genetic Algorithms (GA), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), and Differential Evolution (DE), have been proposed to address the DG optimization problem. These methods are applied to solve the problem as both single-objective and multi objective optimization tasks. An overview of the studies and advancements in the subject of distributed generation is provided in this publication, reviewing studies that utilize evolutionary computing techniques. It  also discusses the types of DG; the technologies employed, and related concepts.