考虑多风电场出力预测误差分布特征的随机机组组合

Stochastic Unit Commitment Considering Output Forecast Error Distribution Characteristics of Multiple Wind Farms

随着风电大规模的并网发电,准确把握风电出力预测误差的特性和规律对于提升电网运行的安全性和经济性具有重要的现实意义。首先基于Pair-Copula理论,提出了一种考虑多风电场出力预测误差相关性和条件分布特性的不确定性模型,可有效提高风电出力不确定性建模的准确程度。然后,在此基础上建立了计及风电风险成本和系统安全约束的随机机组组合模型。通过引入考虑风电出力区间边界的系统备用和网络安全约束,使得系统能够在设定置信区间内有效应对风电的任意波动,确保日内调度方案的可行性;此外,通过将风电区间边界当作决策变量引入到模型的优化过程中,并设置风险机会约束以限制失负荷和弃风风险概率,可有效提升调度决策的灵活性。最后,在具体算例系统仿真测试中验证了所提模型的有效性。

With the increase of wind power penetration level,it is of a great practical significance to accurately grasp the characteristics and laws of wind power output forecast errors for improving the safety and economy of power grid operation.Based on the Pair-Copula theory,an uncertainty model considering the correlation and conditional distribution characteristics of output forecast errors of multiple wind farms is proposed in this paper,in order to effectively improve the accuracy of wind power output uncertainty modeling.Then,a stochastic unit commitment model incorporating the wind power risk cost and the system safety constraints is presented.By introducing the system reserve and network security constraints considering the boundary of wind power output interval,the system is able to safely accommodate arbitrary fluctuations of wind power within the set confidence interval,ensuring the feasibility of the intra-day scheduling scheme.In addition,the wind power interval boundaries are introduced as decision variables into the optimization process of the model,and the risk chance constraints are set to restrict the probability of load shedding risk and the wind curtailment risk to effectively improve the flexibility of scheduling decision.Finally,the effectiveness of the proposed model is verified in the simulation test of specific examples.