Hybrid optimization to enhance power system reliability using GA, GWO, and PSO

Author:

Sireesha Rachapalli1,Coppisetty Srinivasa Rao2,Vijay Kumar Mallapu1

Affiliation:

1. EEE Department, JNTUA , Ananthapuramu , India

2. G Pullaiah College of Engineering and Technology , Kurnool , India

Abstract

Abstract An optimization approach is described in the research study that deals with the issue of reconfiguration networks built with certain conditions of power loss reduction and reliability. Furthermore, the reconfigured networking system seeks optimization based on criteria affecting the limitations. This study optimises specific network faults subjecting resources with no supply during reconfiguration to avoid the effect and possess through active power losses. These goals were met using the mathematical method of the optimisation process. The mathematical formulation is generated first in the system development process. As a result, a comprehensive methodology using genetic algorithm, Grey Wolf optimization (GWO), and particle swarm optimization (PSO) was developed. Finally, intended methodologies were estimated. Based on the results, it is clear that the proposed hybrid GWO-PSO approach outperforms all other methods in terms of node voltage, reliability, line currents, and computational duration. Furthermore, when optimally sized distributed generations are placed in optimal locations, total loss is reduced by up to 63% and voltage profiles improve.

Publisher

Walter de Gruyter GmbH

Subject

Behavioral Neuroscience,Artificial Intelligence,Cognitive Neuroscience,Developmental Neuroscience,Human-Computer Interaction

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