Optimal Integration of DGs in Distribution Networks using Realistic Load Models with Hybrid MC-GA Technique

Abstract

As per conventional demand pattern, there is a daily rise in the need for power consumption. Therefore, producing large amounts of power is important, or losses should be kept to a minimum. This paper presents optimal performance index-based size and location determination of Distributed Generations (DGs) with realistic load models (RLMs) such as RLM-1, RLM-2, RLM-3, RLM-4 and RLM-5 respectively in distribution networks from minimization of real and reactive power losses of the system viewpoint. In this analysis, enhancement of system power factor (SPF) taken as power system performances without and with various types of DGs for different RLMs. The proposed technique for simulation is based on hybrid Monte Carlo-Genetic Algorithm (MC-GA). 16-bus and 37-bus distribution system networks have been carried out to test the proposed methodology. Through comprehensive simulations on a test distribution network, the effectiveness of the proposed approach is demonstrated. Results highlight its potential to optimize the system's performance in terms of reliability, efficiency, and grid stability. This paper contributes to the advancement of optimal DG strategies, emphasizing the importance of addressing realistic load scenarios using a hybrid MC-GA technique.