Application of Intelligent Techniques for Renewable Energy Management

In this chapter, an approach for distributed generation (DG) placement in distribution systems is presented. It utilizes a hybrid algorithmic framework that combines k-nearest neighbors (KNN) and PSO. By using similarity and proximity criteria, the KNN algorithm finds possible places for DG and then reduces the size of the search field. Next, taking into account a variety of limitations and goals, the PSO algorithm optimizes the capacities and types of DG units. Enhancing the effectiveness of DG deployment while balancing system reliability, financial considerations, and environmental impact is the goal of this synergistic strategy. The suggested methodology is validated by simulations conducted on benchmark distribution systems, which show gains in voltage profiles, line losses, and overall system efficiency. KNN and PSO integration provides a strong and practical approach to DG placement optimization, offering insightful information to practitioners, academics, and stakeholders in the power distribution and renewable energy industries. The importance of this strategy in promoting resilient and sustainable distribution networks is shown by the chapter’s discussions on prospective uses, benefits, and directions for further study.