Publisher: 2016 IEEE Power and Energy Society General Meeting (PESGM)
Published on: 11/14/2016
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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.
Wind spillage , wind power forecast errors , compressed air energy storage , sodium sulfur battery , energy storage operation , mixed integer linear programming , Discrete Wavelet Transform