Battery ESS Planning for Wind Smoothing via Variable-Interval Reference Modulation and Self-Adaptive SOC Control Strategy

Abstract

The variability of wind power generation increases the uncertainties in modern power system, affecting its physical operation. Owning to the fast response capability, battery energy storage system (BESS) has offered an answer to this problem. In this paper, a novel sizing methodology is proposed for BESS planning, which strikes a balance between economic cost and wind smoothing performance. First, a novel variable-interval reference signal optimization approach and a fuzzy control-based charging/discharging scheme are presented to smooth wind power, maintaining the state-of-health of BESS in the meanwhile. And then, power and energy capacities are determined according to a statistical model of charge/discharge power and the economic cost model, respectively. Finally, case studies are carried out to demonstrate the performance of the proposed method. The impact from wind power forecasting error during real-time operation is also analyzed.