基于切片反射采样的风电并网系统可用输电能力概率风险评估

Probabilistic risk assessment of ATC based on reflective slice sampling for power system with wind farm

如何全面地考虑风电功率的波动性和随机性,提高风电场出力概率分布采样的速度及精度,进而有效评估可用输电能力(ATC)成为亟待解决的问题。为此,提出基于切片反射采样(RSS)的改进方法对风电并网系统的ATC进行概率风险评估。对风电场出力进行优化建模,利用RSS对模型进行采样并构建样本空间,将样本值代入潮流方程进行最优潮流计算,并对ATC评估指标进行统计分析。含有风电场模型的IEEE 30节点系统仿真结果表明,与常规Gibbs采样算法相比,所提方法在确保计算效率的同时显著提高了采样方法的准确度。

In order to enhance the speed and precision of the probabilistic distribution sampling of windfarm power-output and further to effectively assess the ATC（Available Transfer Capability）,it is essential to comprehensively consider the fluctuation and randomness of wind power,for which,an improved method based on RSS（Reflective Slice Sampling） is proposed to assess the probabilistic risk of the ATC of power system with wind farm. An optimal model of wind-farm power-output is established and then sampled based on RSS to construct a sample space. Samples are then applied to the power flow equations for calculating the optimal power flow and the ATC assessment indexes are statistically analyzed. The simulative results of IEEE 30-bus system with a wind farm show that,compared with traditional Gibbs sampling,the proposed method improves the precision of sampling method while ensures the calculation efficiency.