Cost-Effective Energy Management of Battery Systems in AC Microgrids via Vortex Search

Abstract

Efficient dispatch of Battery Energy Storage Systems (BESS) is essential to reduce operational costs in Alternating Current (AC) microgrids, yet most Energy Management System (EMS) strategies reported in the literature are validated only under grid-connected conditions and lack a systematic tuning of their optimization parameters, limiting their reliability under islanded operation. This work presents a robust EMS methodology based on a tuned Parallel Vortex Search Algorithm (PVSA) combined with a Successive Approximation (SA) power flow method to optimize BESS dispatch in AC microgrids under both grid-connected and islanded modes, aiming to improve operational cost efficiency. The proposed strategy is validated on a 33-bus test feeder with real demand and generation profiles from Medellín, Colombia, and benchmarked against the Chu & Beasley Genetic Algorithm (CBGA) and the Memory-Based Gravitational Search Algorithm (MBGSA). Results show that PVSA achieves the lowest operational costs, reducing expenses by up to 1.44% in grid-connected mode and 0.132% in islanded mode relative to the base case, while maintaining voltage and current within technical limits. PVSA also demonstrates superior robustness, with minimal cost variability across 100 independent runs. Although computationally more intensive than CBGA and MBGSA, the proposed approach is well suited for offline planning scenarios where consistent and reliable operation is essential.