A Metaheuristic Approach for the Optimal Allocation of Distributed Energy Resources in a Distribution System

In this paper, a variant of the Chimp optimisation algorithm, namely, Chimp Particle Swarm Optimisation Algorithm (ChPSO), a metaheuristic optimisation technique, is recommended to optimise the placement of Distributed Energy Resources (DER) in electric power distribution systems. By integrating the Chimp Optimization Algorithm with Particle Swarm Optimization, ChPSO enhances the efficiency and reliability of power distribution networks. The algorithm's effectiveness is evaluated using the IEEE-33 bus distribution system, a well-established benchmark in power system research. The primary goal is to strategically position DERs to minimize real power losses, and reduce voltage deviations across all nodes. Results indicate significant improvements in these performance metrics, showcasing ChPSO's capability to tackle complex optimization challenges. Specifically, the implementation of three optimally placed DERs achieved a remarkable 92.20% reduction in real power loss, while positioning four DERs resulted in an even greater reduction of 92.90%. Additionally, reactive power losses decreased by 90.55% and 91.59% for three and four DERs, respectively. These findings highlight the potential of the ChPSO algorithm as a decent solution for optimized DER placement, significantly enhancing the operational efficiency and reliability of modern distribution systems and emphasizing the need for innovative optimization strategies in sustainable energy solutions.