Optimization Techniques to Minimize the Power Loss and Maintain Voltage Stability for A Power System

An increasing number of developing nations across the globe have encountered an inevitable surge in the demand for electrical power. This surge, if left unaddressed, can lead to a deterioration of the voltage magnitude and a decrease in the overall stability of the power systems. Within this context, an approach to mitigate system losses explored in this study involves the strategic allocation of distributed generation (DG). The pivotal factors in this endeavor are the judicious determination of the optimal location and sizing of DG units. Failure to achieve the optimal distribution, sizing, and placement of grid-connected DG can result in either over-compensation or under-compensation in a loss mitigation strategy. This study has been done by a comprehensive comparative analysis of the efficacy of three optimization techniques which are Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Hybrid Swarm Evolutionary Programming (HSEP), for their capacity to minimize power losses while simultaneously upholding voltage magnitude in power system. The assessment was conducted on two distinct power systems which are the interconnected IEEE-30. The HSEP algorithm stands out by notably reducing total active power losses compared to others. The voltage profile graph highlights all optimization techniques consistently maintain values ranging from 0.95 to 1.05 p.u, complying with ANSI C84.1 standards. Multiple meta-heuristic algorithms to address intricate and multifaceted problems more effectively. Such an approach is particularly advantageous when dealing with complex challenges that can benefit from the identification of various optimization strategies.