Impact Analysis of Combining Distributed Generation With Charging Loads for Electric Vehicles Accounting Reliability

Abstract

This work is concerned with the penetration of renewable energy-based distributed generation along with electric vehicle (EV) charging loads into power distribution systems. This presents a new optimization procedure integrating Particle Swarm Optimization and the Andean Condor Algorithm (PSO-ACA) into a high-performing route for system design. It analyzes the performance of the system in terms of minimizing the loss of power and maximizing reliability. The study evaluates reliability indices and power loss reductions in detail by utilizing benchmark 33-bus and 69-bus test systems. The findings indicate that for the 33-bus system, the active power loss reduction obtained is 64.3 KW, with real power loss showing a 68% reduction, whereas for the 69-bus system, real power loss decrease is 72% (62.8 KW). This led to a substantial reduction in reliability indices thus enhancing the overall system performance as hybrid optimization techniques improved the reliability of the system remarkably. These results show the immense potential that advanced hybrid optimization approaches combined with reliability analyses have for delivering the economically viable, sustainable renewable energy systems of the future. This collaboration is in line with the larger objectives of promoting sustainable energy solutions and establishing a more resilient and efficient energy framework.