基于场景集的含风电电力系统旋转备用优化

Optimizing the Spinning Reserve in Wind Power System Using Scenario Method

大规模风电并网对电力系统调度运行和旋转备用的决策带来了难题。将电量不足期望和弃风电量期望通过惩罚系数引入机组组合目标函数中,权衡系统经济性和可靠性,协调决策旋转备用。通过拉丁超立方采样建立基于机组强迫停运、风电出力预测误差和负荷预测误差离散化的场景集,基于所建立的场景集推导出电量不足期望和弃风电量期望跟旋转备用的关系式并作为机组组合模型的约束,进行含风电电力系统发电和旋转备用计划协调决策。仿真结果表明建立的模型能根据可靠性要求灵活安排机组出力和旋转备用计划。

Large-scale wind farm integration brings new challenges to decision of spinning reserve capacity.This paper proposes a method to balance system reliability and operation cost by using ＂expected energy not supplied（EENS）＂ and ＂expected wind curtailed（EWC） ＂ in form of an additional penalty term in objective function of unit commitment problem.Quantized relation between spinning reserve and EENS and EWC is derived by putting up scenario set using Latin hypercube sampling（LHS） technique,taking into account forced outage of generation units,discretized wind power prediction error and power load prediction error.Simulation results of comparison between different spinning reserve decision techniques show that the proposed method can consider both economy and reliability,and decide spinning reserve capacity more flexibly by setting different penalty coefficients.