RoCoF Restrictive Planning Framework and Wind Speed Forecast Informed Operation Strategy of Energy Storage System

Abstract

A planning framework and operation strategy for energy storage are developed to limit the rate of change of frequency (RoCoF) within the industry requirements in power systems with high renewable energy penetration. The planning framework utilizes a two-step algorithm for the capacity estimation of energy storage. In the first step, the size is calculated analytically based on the frequency dynamics. While in the second step, the estimated size is used as an initial guess in the region reduction iterative algorithm (RRIA) to calculate the accurate required capacity. Furthermore, an economical comparison is carried out among the available rapid responsive storage technologies to find out the most suitable technology for virtual inertia support (VIS). Next, a wind speed forecast informed coordinated control strategy is developed for the storage and wind turbine to provide VIS. An ensemble neural network technique is used for the wind speed forecasting. The coordinated control strategy utilizes the information of forecasted wind speed and the state of energy storage to improve the utilization of storage while limiting the RoCoF within desired window. Simulation results depict the accuracy of the estimated capacity and the effectiveness of the coordinated control strategy.