Reliability Improvement by Optimal Placement and Sizing of Renewable Energy-Based Distributed Generation Employing Mean Oriented Particle Swarm Optimization

In recent years, the distribution system reliability analysis has become an integral part of power system analysis. The increase in the incorporation of renewable energy-based (RER) distributed generation (DG) has introduced uncertainties that affect the grid reliability, operation, and planning. Hence, it is crucial to maintain a stable and reliable power supply. This paper aims to improve reliability parameters, enhance the bus voltage profiles, and decrease the real power loss in radial distribution networks by finding the optimal allocations and capacity planning of RER DGs employing the proposed mean-oriented PSO algorithm. The limitation of PSO of premature and slow convergence is improved by adding a mean component to the velocity of the particle. It leads to faster convergence and avoids trapping in local minima, leading to a better global solution. The mean-oriented PSO algorithm performance is compared with that of PSO for the Algerian 114 bus test system. The problem takes into account a load that changes over time to achieve practical results. The obtained results showcase the efficacy of the proposed mean-oriented PSO algorithm in solving the multimodal and complex problem of optimal placement and sizing of RER DG for improving the reliability of the system and reducing the real power losses of the distribution network with different loading conditions.