A Review and Comparative Study on Different Algorithms in Efficient DG Allocation in Power Distribution Networks

The integration of Distributed Generation (DG) into the Distribution infrastructure has become a pivotal approach for enhancing system reliability, reducing power losses, and improving voltage profiles. However, efficient DG Allocation units is essential to fully realize these benefits and avoid potential drawbacks such as voltage instability, power quality issues, and increased operational complexity. This study proposes a comparative analysis of various Refinement techniques employed to identify the best locations and sizes of DG units. Algorithms like Grey Wolf Algorithm (GWO), Particle Swarm optimization algorithm (PSO), the Dragonfly algorithm (DA), and Genetic algorithm can be used in multiple scenarios to determine the efficient number, size, and location of DG. It highlights recent advancements in the field and outlines core focus areas for future exploration. The problem of efficient DG placement is formulated as a multi-objective optimization task aimed at minimizing power losses, enhancing voltage stability, improving system reliability, and reducing operational costs. This is achieved while adhering to essential network constraints, including power balance, voltage limit, and DG capacity limits.