An adaptive wind power smoothing method with energy storage system

Abstract

The random and intermittent nature of wind power (WP) makes the integration of large-scale wind farms into power system problematic. The energy storage system (ESS) is an effective means to smooth the WP. This paper presents a novel Kalman filter (KF) based adaptive wind power smoothing method to determine the power output of an ESS. ESS capacity can be significantly reduced by adjusting the parameters of KF adaptively according to the WP fluctuation. Meanwhile, a fuzzy logic controller is introduced to manage the remained energy level (REL) of the ESS. By considering the current WP fluctuation, the REL and the power output of the ESS together in the controller, the REL can be successfully managed to a reasonable range without deteriorating the WP fluctuation. A test case based on data from an actual wind farm validated the effectiveness of the proposed method.