Enhancing frequency control in wind-penetrated power system using ultrabattery energy storage: Tracking model predictive static programming approach

Wind power causes generation–load mismatch, which conventional load frequency control (LFC) cannot effectively handle. Energy storage systems (ESSs) can enhance LFC by absorbing (supplying) surplus (inadequate) power. However, power system is nonlinear and constrained. This study proposes a nonlinear predictive control framework—tracking model predictive static programming—to enhance LFC in a wind-integrated system using an Ultrabattery energy storage system (UESS). The objective is to improve power system frequency stability using a UESS. Therefore, the problem was formulated as a reference tracking one, wherein the objective is to minimize the power system frequency and UESS voltage deviations. State and input constraints were included. Two case studies validated the system’s performance, showing that UESS mitigates wind and load disturbances. When employing the proposed control with UESS, the integral squared error was reduced from a value of 7.058 to 1.019 in a case study involving both wind and load disturbances.