Probability-Based Power Dispatch in Wind-Integrated Electrical Grid for Energy Storage Capacity Determination

Abstract

Implementing microgrids has become a current trend in the electric utility industry to either improve system reliability or energy access for energy sustainability. This study proposes a probability-based strategy for both long- and short-term power dispatch with wind and load uncertainty. The long-term power dispatch is used to determine a suitable capacity of energy storage, and the short-term power dispatch is used for real-time operation. For both short- and long-term power dispatch, the trends of wind energy and electricity demand are extracted using the wavelet packet analysis method and the moving average technique. The uncertainties from wind speed and power generation data are modeled with log-normal and extreme value distributions, respectively. From the obtained power dispatch and model forecasting, the capacity of energy storage is determined. To validate the proposed approach, a real-time operating simulation is used as a case study to observe the behavior of the wind-integrated electrical system. Results show that the proposed method can estimate the uncertainty variation range of wind energy and the state of charge of energy storage effectively.