计及预测误差相关性的风电出力不确定性集合建模与评估

先进的鲁棒调度技术是应对出力不确定性最经济、最有效的手段之一;而不确定性集合是刻画风电出力不确定性的基本形式,它不依赖于预测误差的具体分布形式,是制定风电鲁棒调度策略,进而保障系统安全经济运行的重要参考依据。首先,采用实际数据对现有不确定性集合建模方法进行了评估,指出在不确定性集合中若忽略风电预测误差的相关性将导致不合理的结果。在此基础上,基于广义椭球的一般表达式,提出了风电出力不确定性测度的概念,进而给出一种可以准确考虑风电预测误差相关性的不确定性集合建模方法。实际算例表明,在给定置信概率下,所提方法能够保证不确定性集合凸性,大幅压缩不确定性集合的测度,从而显著降低电力系统鲁棒优化决策的保守性。

Modeling and Evaluation of Uncertainty Set Considering Wind Power Prediction Error Correlation

Advanced robust scheduling technology is one of the most economical and effective means to deal with output uncertainty. Usually, uncertainty set is used for describing the prediction error of wind power generation. It does not require the probability distribution of prediction errors and can cover all realizations of wind generation prediction errors with given confidence level. In our work, existing models of uncertainty set are evaluated using real data in wind farm operations. The study shows that unreasonable uncertainty sets may occur if the correlation of prediction errors is neglected. Furthermore, a criterion of wind generation uncertainty is proposed, based on which a new ellipsoidal modeling method is derived to incorporate the correlation of prediction errors. Given a confidence level in the sense of probability, the proposed uncertainty set can greatly reduce the measure of prediction errors with convexity guarantee. This facilitates mitigating conservativeness of robust optimization decision making process in power systems.