Reactive Power Optimization in Power System using Genetic Algorithm

Abstract

An increase in inductive loads is driving up energy consumption to the point where distribution system analysis is becoming too complicated to answer theoretically. Nigeria's electrical distribution system so regularly finds it difficult to keep up with the nation's high energy consumption. To maximise power losses and increase operating bus voltages, this research study analyses the Choba 11kV Distribution Network and applies a genetic algorithm to reactive power optimisation. A load flow analysis of the 76 buses in the network under inquiry showed that 41 of them were running at a critical level of undervoltage. Additionally, a genetic algorithm was used to position capacitors optimally to enhance system performance overall and guarantee the dependability of power supply. After inserting the capacitor banks, a load flow analysis was carried out to validate the proposed methodology for reactive power optimisation. The results showed that all buses were operating within permissible limits, that the active power losses had decreased by 30.9%, and that the reactive power losses had decreased by 31.5%, improving the distribution system's performance. The power system network was modelled and simulated using ETAP (Electrical Transient Analyzer Program) software, while load flow analysis was conducted using Newton Raphson's approach.