Optimizing Distributed Generation Placement for Voltage Stability Using Genetic Algorithms

The growing complexity of modern energy systems has led to the increasing penetration of Distributed Generation (DG) into the distribution network as an effective method of improving grid efficiency, resilience, and stability. However, the current techniques for optimal DG allocation are still hampered by the high cost, slow implementation, and unfulfilled promises. In a bid to improve voltage stability as the major goal of the optimal location for DG units, a method based on Genetic Algorithm (GA) is proposed in this study. The methodology requires the simulation of the real-life 11 kV primary feeder system in Ado-Ekiti, Nigeria, for optimisation on MATLAB. In endemic conditions, the voltage deviation serves as the criterion performance to evaluate the stability of the distribution systems under varying DG penetration capacity before and after the implementation of the GA method. The results prove that the random location of the DG unit is capable enough to marginally improve the voltage profile. However, the impact of the proposed GA-based method considerably improves the system voltage profile above the stability limit of 0.95 p.u. at the maximum loading condition due to the increase in capacity. The findings concluded that GA is an excellent tool for optimal DG location, thus providing a good ground for the utilities to exploit for improving voltage stability, loss reduction, and economic operation of energy systems. GA applications could serve as a pivotal organising force in the power distribution improvement strategies that make great contributions to smart distribution and decentralised grids.