4.6 Article

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

Journal

IEEE TRANSACTIONS ON ENERGY CONVERSION
Volume 30, Issue 2, Pages 681-695

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEC.2015.2390912

Keywords

Battery energy storage; doubly-fed induction generator (DFIG); predictive control; probabilistic forecast; stochastic optimization; wind energy

Funding

  1. National Natural Science Foundation of China [61403303, 51177125]
  2. China Post-Doctoral Science Foundation [2014M560776]
  3. State Key Laboratory of Electrical Insulation and Power Equipment [EIPE15306]

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To improve the wind energy dispatchability in the presence of non-Gaussian wind power uncertainties, this paper presents a stochastic coordinated control scheme for the doubly-fed-induction-generator-based wind-battery hybrid systems (WBHS). The proposed control scheme has a two-layer structure. Based 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 way, the combined power output of WBHS is brought to the desired dispatch levels. The salient feature of the proposed scheme is that it optimizes the control actions over the non-Gaussian wind power predictive distributions, thus handling the non-Gaussian uncertainties in wind power. The simulation results on actual wind data demonstrate the effectiveness of the proposed scheme.

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