A Hybrid Metaheuristic Approach for Optimal PV Placement and Sizing in Distribution Networks

Faculty of Electrical Engineering, The University of Danang -University of Science and Technology, Danang, Vietnam

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

Integrating renewable energy sources into distribution networks can improve operational efficiency and reduce power losses. This study proposes a hybrid optimization method combining Archimedes Optimization Algorithm (AOA), Football Team Training Optimization Algorithm (FFTOA), Teaching-Learning Based Optimization Algorithm (TLBOA), and Starfish Optimization Algorithm (SFOA) to determine the optimal placement and sizing of photovoltaic units. The hybrid strategy enhances the original AOA by improving convergence speed and reducing the risk of local optima. FTTOA with Fitness Distance Balance helps select better guiding solutions, TLBOA supports information sharing and population diversity, and SFOA strengthens exploration and solution regeneration. A Beta distribution is used to model solar irradiance uncertainty. The proposed method is tested on the IEEE 33-bus distribution system for PV allocation. Results show that PV integration improves voltage profiles and reduces energy losses. Compared with other methods, the proposed approach achieves competitive performance and improved stability while maintaining reasonable computational cost.