Optimal Operation of Energy Storage to Minimize Wind Spillage and Mitigate Wind Power Forecast Errors

Wind spill occurs due to the non-correlation between load and wind profiles, and also wind power forecast errors. Scheduling energy storage units to reduce wind spillage gets complicated considering the difference between day-ahead wind power forecast range, hour-ahead wind power forecast, and actual wind power. This paper presents an algorithm that optimally schedules energy storage to address both applications minimizing wind spillage and mitigating wind power forecast errors. First, energy storage is scheduled to minimize wind spillage by a mixed integer linear programming, given day-ahead wind power forecast range. Then, day-ahead energy storage operation is updated to mitigate the error between day-ahead wind power forecast and hour-ahead wind power forecast, using Discrete Wavelet Transform (DWT). Finally, energy storage operation is updated by DWT to mitigate the error between actual wind power and hour-ahead wind power forecast. Wind spillage and required back-up generation is calculated for different scenarios of day-ahead wind power forecast, energy storage technologies (e.g. compressed air energy storage, and sodium sulfur battery), and state of charge values. To showcase the applicability of the proposed approach, a case study based on the real world wind and load data obtained from the Bonneville Power Administration in 2013 is presented.