基于异常溯因推理的需求侧协同调度优化研究

Demand-side cooperative scheduling optimization based on abnormal abductive reasoning

中文关键词: 溯因推理  贝叶斯网络  分布式调度  日前优化调度  柔性负荷

英文关键词: abductive reasoning  Bayesian network  distributed scheduling  day-ahead optimization scheduling  flexible load

中文摘要:

      源网荷储的多样性特征导致当前电网异常的原因越来越复杂，为了充分利用需求侧宝贵的柔性资源，提出了一种基于异常溯因推理的需求侧协同调度优化方法。首先，提出了一种基于贝叶斯网络对异常指标进行溯因推理的方法。其次，基于极限场景法处理风力发电、负荷波动，构建考虑柔性负荷的电网日前分布式调度模型。最后，设置4种情景进行对比分析。算例结果表明，所提方法能够有效缓解区域潮流指标的异常趋势。

英文摘要:

      The diversity of source nectwork load and storage leads to increasingly complex causes of current grid anomalies. In order to make full use of the valuable flexible resources on the demand side, a demand- side cooperative scheduling optimization method based on abnormal abductive reasoning is proposed. Firstly, a method of abductive reasoning based on Bayesian network is proposed. Secondly, based on the limit scenario method to deal with fan and load fluctuations, the day-ahead distributed dispatching model of power grid considering flexible load is constructed. Finally, four scenarios are set for comparative analysis. The numerical results show that the proposed method can effectively alleviate the abnormal trend of regional tidal current index.