Dynamic State-of-Charge Modeling in Battery Energy Storage Systems With Power Ramp-Rate Control

Abstract

This paper presents a vectorized approach for modeling and tuning the state-of-charge (SOC) dynamics in Battery Energy Storage Systems (BESS) equipped with power ramp-rate control (PRRC). The SOC evolution is formulated in discrete time, and parameter estimation is performed using Differential Evolution (DE) integrated with Anatem, a dynamic simulation tool used for electromechanical transient studies. This study compares the traditional generic (WECC-based) SOC model, which employs a fixed-gain integrator, with a proposed variable-gain integrator that adapts to BESS active power through a piecewise-linear function. The methodology is validated using real SCADA data from a 1.1-MW photovoltaic plant coupled with a 0.95-MW/0.49-MWh BESS in Brazil. Measurements were sampled at 1-second intervals, while Anatem simulations employed a 50-ms integration step to ensure numerical accuracy and appropriate representation of converter-level dynamics. A reference day and multiple operational scenarios were used for calibration and cross-validation. Results show that the variable-gain formulation reduces the Root Mean Square Error (RMSE) by 57–91% compared with the standard generic model, providing an improved fidelity during rapid charge and discharge transitions. The method also enhances the alignment between simulated and measured active-power behavior, supporting robust ramp-rate compliance and improved representation of BESS operational limits. The proposed framework is suitable for both short-term dynamic simulations and long-term operational analyses and can be extended to hybrid configurations and other control functions that require parameter tuning from real operational data. The findings highlight the importance of dynamic gain adaptation for accurate SOC modeling in hybrid PV–BESS systems and support the applicability of this method in stability studies, operational planning, and hybrid system design.