Pragmatic Design and Tuning of a Hybrid Metaheuristic BESS Controller for LV Grid Stability

Abstract

The integration of Battery Energy Storage Systems (BESS) is critical for mitigating voltage instability in low-voltage (LV) networks with high photovoltaic (PV) penetration. While metaheuristic algorithms offer powerful tools for optimizing BESS dispatch, their successful transition from theoretical models to practical application hinges on a nuanced understanding of their operational parameters. This paper presents a case study on the pragmatic design and tuning of a hybrid Particle Swarm Optimization-Grey Wolf Optimizer (PSO-GWO) for a six-dimensional, multi-BESS control problem. We chronicle the evolution of the simulation framework, highlighting critical implementation challenges and their solutions. Key findings demonstrate that optimizer population size, not just iteration count, is a decisive factor in control stability, particularly for computationally inexpensive configurations. We introduce a control oscillation metric as a key performance indicator and discuss the indispensable role of smart warm-starts and rate-limiting in generating physically viable and asset-safe control actions. The paper concludes that a successful BESS control strategy is defined not only by its ability to meet primary objectives like voltage regulation but also by the stability and practicality of the control signals it produces, presenting a crucial trade-off between computational budget and real-world viability.