Wind Power Smoothing With Energy Storage System: A Stochastic Model Predictive Control Approach

The utilization of energy storage system (ESS) is an effective method for dealing with the randomness and variability wind power. Therefore, improving coordination between ESS power a direction worthy research. This study develops two-layer stochastic model predictive control (SMPC) smoothing on different time-scales. proposed optimization framework smooths by adjusting charge discharge hybrid ESSs; moreover, it combines SMPC approach chance constraints to address uncertainties energy. Furthermore, previous states are taken into account, in addition within rolling time horizon, obtain optimal ESSs, capacity planning ESSs conducted simultaneously. numerical results obtained through amplitude-frequency simulation comparison prove that superior conventional terms minimizing frequency fluctuation size ESS.