Unit Commitment Considering the Correlation of Wind Power Prediction Errors

Due to the volatility and uncertainty of wind power, their increasing grid-connected capacity brings great challenges to the safe and economic operation of traditional power system. This paper proposes a unit commitment model based on chance-constrained considering multiple correlations of forecast errors. Firstly, by using chance-constrained programming, the multiple correlations of forecast errors and the unit commitment with wind power integrated are effectively connected. Secondly, the theory of conditional value at risk is introduced, and the capacity of reserve and risk are well balanced under multiple correlations. In addition, the impact of wind power uncertainty on scheduling is reduced, due to the refined expression of wind power forecast error characteristics. Finally, the calculation and analysis of the proposed model are conducted on a New England 10-unit system. Case study verified the effectiveness of the method.