Application of the PSO algorithm in BESS operation scheduling for industrial park power grids

Abstract

This study proposes an advanced methodological framework to optimize the operational strategy of Battery Energy Storage Systems (BESSs). The primary focus is to comprehensively address the multi-objective techno-economic operational problem in distribution networks, with particular attention to the characteristics of high-intensity industrial park loads subject to a time-of-use (TOU) electricity pricing mechanism. To optimize within the complex solution space of the 24-hour charging and discharging cycle, the Particle Swarm Optimization (PSO) algorithm is deployed as a black-box optimizer via a co-simulation mechanism that is deeply integrated with the PSS® SINCAL power system computing platform. The mathematical structure of the model strictly complies with boundary conditions regarding equipment physical constraints, notably the state of charge (SOC) limits, and the BESS rated power limits. The central contribution of this research is the quantification of the inherent trade-off between minimizing electricity transaction costs and managing active power losses across the system. The simulation results confirm that the proposed model constitutes a strategic and highly reliable computational tool. It not only meets the technical requirements for peak shaving during high-demand hours but also maximizes economic benefits through energy arbitrage under the TOU pricing mechanism.