PROJECT TITLE :

Coordinated Predictive Control of DFIG-Based Wind-Battery Hybrid Systems: Using Non-Gaussian Wind Power Predictive Distributions

ABSTRACT:

To enhance the wind energy dispatchability in the presence of non-Gaussian wind power uncertainties, this paper presents a stochastic coordinated control theme for the doubly-fed-induction-generator–based mostly wind-battery hybrid systems (WBHS). The proposed management scheme features a two-layer structure. Based mostly on the non-Gaussian distributional wind power forecasts, an upper layer stochastic predictive controller coordinates the operation of wind and battery subsystems. The computed power references are passed to the lower layer wind and battery controllers for execution. This manner, the combined power output of WBHS is delivered to the specified dispatch levels. The salient feature of the proposed scheme is that it optimizes the management actions over the non-Gaussian wind power predictive distributions, therefore handling the non-Gaussian uncertainties in wind power. The simulation results on actual wind information demonstrate the effectiveness of the proposed scheme.