基于数据关联狄利克雷混合模型的电网净负荷不确定性表征研究  

Uncertainty Characterization of Power Grid Net Load of Dirichlet Process Mixture Model Based on Relevant Data

作　　者：李远征[1,2] 孙天乐 刘云 赵勇 曾志刚[1,2] LI Yuan-Zheng;SUN Tian-Le;LIU Yun;ZHAO Yong;ZENG Zhi-Gang(School of Artificial Intelligence and Automation,Key Laboratory on Image Information Processing and Intelligent Control of Ministry of Education,Huazhong University of Science and Technology,Wuhan 430074;China-Belt and Road Joint Laboratory on Measurement and Control Technology,Wuhan 430074;School of Electrical Power Engineering,South China University of Technology,Guangzhou 510641)

机构地区：[1]华中科技大学人工智能与自动化学院,图像信息处理与智能控制教育部重点实验室,武汉430074 [2]中国−测控技术“一带一路”联合实验室,武汉430074 [3]华南理工大学电力学院,广州510641

出　　处：《自动化学报》2022年第3期747-761,共15页Acta Automatica Sinica

基　　金：国家自然科学基金(62073148);腾讯—犀牛鸟基金(RAGR20210102)资助。

摘　　要：针对电网净负荷时序数据关联的特点,提出基于数据关联的狄利克雷混合模型(Data-relevance Dirichlet process mixture model,DDPMM)来表征净负荷的不确定性.首先,使用狄利克雷混合模型对净负荷的观测数据与预测数据进行拟合,得到其混合概率模型;然后,提出考虑数据关联的变分贝叶斯推断方法,改进后验分布对该混合概率模型进行求解,从而得到混合模型的最优参数;最后,根据净负荷预测值的大小得到其对应的预测误差边缘概率分布,实现不确定性表征.本文基于比利时电网的净负荷数据进行检验,算例结果表明:与传统的狄利克雷混合模型和高斯混合模型(Gaussian mixture model,GMM)等方法相比,所提出的基于数据关联狄利克雷混合模型可以更为有效地表征净负荷的不确定性.Considering the time sequence correlation of the net load in power grids,this paper proposes a non-parametric Bayesian framework based on the data-relevance Dirichlet process mixture model(DDPMM).First,the Dirichlet process mixture model is used to fit the observation data and the forecast data of net load,in order to obtain a joint mixed probability model.Then,we propose a modified variational Bayesian inference that considers the correlation of the time sequence to acquire optimal parameters of the mixture model.Afterwards,we obtain the corresponding net load forecast error probabilistic distribution according to different net load forecast values.Finally,this paper uses actual data from the Belgian power grid for verification.Compared with the traditional Dirichlet process mixture model and Gaussian mixture model(GMM),our proposed approach takes into account the correlation of time series.Therefore,it can better characterize the forecast error of the net load,and obtain the optimal number of component clusters that would capture the uncertainty of the net load with more efficiency.

关 键 词：狄利克雷混合模型 净负荷 不确定性表征 时序序列 预测误差 

分 类 号：TM714[电气工程—电力系统及自动化]