Improvement of Loadability in Distribution System Using Genetic Algorithm

TL;DR

This paper proposes a genetic algorithm-based method to optimize the placement of distributed generation sources in distribution systems, significantly improving loadability and system performance.

Contribution

It introduces a novel genetic algorithm approach for optimal DG placement to enhance loadability in distribution networks, considering renewable energy integration.

Findings

Genetic algorithm effectively maximizes loadability.

Optimal DG placement reduces system losses.

Improves reliability and stability of distribution systems.

Abstract

Generally during recent decades due to development of power systems, the methods for delivering electrical energy to consumers, and because of voltage variations is a very important problem, the power plants follow this criteria. The good solution for improving transfer and distribution of electrical power the majority of consumers prefer to use energy near the loads .So small units that are connected to distribution system named "Decentralized Generation" or "Dispersed Generation". Deregulated in power industry and development of renewable energies are the most important factors in developing this type of electricity generation. Today DG has a key role in electrical distribution systems. For example we can refer to improving reliability indices, improvement of stability and reduction of losses in power system. One of the key problems in using DG's, is allocation of these sources in distribution networks. Load ability in distribution systems and its improvement has an effective role in the operation of power systems. However, placement of distributed generation sources in order to improve the distribution system load ability index was not considered, we show DG placement and allocation with genetic algorithm optimization method maximize load ability of power systems .This method implemented on the IEEE Standard bench marks. The results show the effectiveness of the proposed algorithm .Another benefits of DG in selected positions are also studied and compared.