A Method for Optimizing the Energy Storage Configuration on The Renewable Energy Side Based-on Improved HS-IMOPSO

The integration of renewable energy (RE) has a significant impact on the reliability and stability of power systems. Therefore, the introduction of ES systems is necessary to mitigate potential issues. ES systems can effectively reduce voltage fluctuations, enhance the efficient utilization of RE resources, and significantly decrease energy losses in the power network. This paper aims to develop a comprehensive model that considers system voltage fluctuations, network losses, and accumulated ES capacity for ES siting and sizing. To address the multi-objective optimization problem, we introduce an innovative multi-objective particle swarm optimization algorithm based on Harmony Search (HS-IMOPSO). This algorithm cleverly incorporates the principles of harmony and tone modulation from the Harmony Search method into the multi-objective particle swarm optimization framework, substantially reducing the risk of falling into local optima. We utilize data from the entire year of 2022 from a specific location, segmenting it into quarterly intervals and extracting representative daily data. The algorithm's validation is conducted using an IEEE33-node distribution system. Simulation results highlight the outstanding performance of the HS-IMOPSO algorithm in global search capabilities and the generation of a superior Pareto solution set.