Abstract
As the output from wind power generation is intermittent in nature, making the wind power output “dependable” is critical for seamless integration of wind generation. One of the most favorable solutions is incorporating energy storage system (ESS) with wind farms to establish a wind-energy storage hybrid system. Since it requires capital investment for ESS installation, it is important to estimate appropriate storage capacity and charging/discharging rate of ESS for desired applications. In this paper, the fluctuation feature of wind power output is analyzed both in time domain and frequency domain. The degree of fluctuation is extracted and illustrated as quantization index (QI). Based on QI clustering, the wind scenario with largest power fluctuation is selected as “worst performance,” according to which, scheduling time horizon, along with the capacity and charging/discharging power of ESS, can be determined. After the case study, the proposed model is proved to improve the generation scheduling process.
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