A novel hybrid algorithm based on optimal size and location of photovoltaic with battery energy storage systems for voltage stability enhancement

The article introduces a novel hybrid algorithm for optimizing the size and location of photovoltaic (PV) systems with battery energy storage systems (BESS) in radial distribution systems (RDSs). The primary challenge addressed is the enhancement of voltage stability during stressed conditions. The study reviews existing methods for optimizing distributed generator (DG) allocation, including both analytical and metaheuristic techniques. The proposed hybrid quasi-oppositional artificial rabbits’ optimization (Hybrid QOARO) metaheuristic algorithm combines quasi-oppositional-based learning (QOBL) with a novel line stability index (NLSI) to improve the search area and enhance the performance of the original artificial rabbits’ optimization (ARO) algorithm. The algorithm aims to minimize real power losses and total voltage deviation while maximizing voltage stability. The evaluation and comparison of the algorithm using the IEEE 33-node RDS demonstrate its effectiveness in optimizing DG size and placement. The study also examines the impact of different power factor values and the integration of PV-only and PV+BESS systems on energy losses and voltage stability over four seasons. The integration of PV and BESS units at various power factors results in reduced total energy losses and improved voltage profiles. The paper concludes by summarizing the contributions and discussing future research directions in the field of DG allocation and voltage stability enhancement.