基于MQ-WaveNet的风电集群发电功率多步概率预测  

Multi-step Probability Prediction of Power Generation for Wind Power Clusters Based on Multi-horizon Quantile-WaveNet

作　　者：李青 张新燕[1] 摆志俊 马磊 王衡 张正 LI Qing;ZHANG Xinyan;BAI Zhijun;MA Lei;WANG Heng;ZHANG Zheng(Department of Electrical Engineering,Xinjiang University,Urumchi 830000,China;Electric Power Research Institute of State Grid Xinjiang Electric Power Co.,Ltd.,Urumchi 830000,China;Aksu Power Supply Company of State Grid Xinjiang Electric Power Co.,Ltd.,Urumchi 830000,China;State Grid Xinjiang Electric Power Co.,Ltd.,Urumchi 830000,China)

机构地区：[1]新疆大学电气工程学院,新疆维吾尔自治区乌鲁木齐市830000 [2]国网新疆电力有限公司电力科学研究院,新疆维吾尔自治区乌鲁木齐市830000 [3]国网新疆电力有限公司阿克苏供电公司,新疆维吾尔自治区乌鲁木齐市830000 [4]国网新疆电力有限公司,新疆维吾尔自治区乌鲁木齐市830000

出　　处：《电力系统自动化》2023年第8期156-168,共13页Automation of Electric Power Systems

基　　金：国家自然科学基金资助项目(51667018);自治区自然科学基金联合基金项目(2021D01C044)。

摘　　要：风电渗透率的持续提高对电力平衡测算、电网运行调度和系统频率稳定带来了极大挑战。为量化区域风力发电的不确定性,提出一种风电集群直接多步概率预测模型。首先,为有效挖掘区域内各风电场数据与集群发电总出力间的时空相关性,采用最大互信息系数法选取基准场站和关键输入特征变量。然后,基于序列-序列网络架构,结合分位数回归概率预测特性及波网(WaveNet)可捕获大范围内时序依赖特性等优点,设计了适用于风电集群概率预测的多视界分位数(MQ)-WaveNet模型,实现对风电集群场站在多个时间跨步上的风电功率多分位点的预测。最后,选取中国新疆哈密东南部风区12个邻近的大型风电场运行数据进行算例分析。结果表明,所提模型仅利用相关基准场站的关键特征变量即可实现风电集群发电功率的有效预测,模型复杂度低、易于工程应用推广。The continuous increase of wind power penetration rate has brought great challenges to the calculation of power balance,grid operation scheduling and system frequency stability.In order to quantify the uncertainty of regional wind power generation,a direct multi-step probability prediction model for wind power clusters is proposed.First,in order to effectively exploit the spatialtemporal correlation between the data of every wind farm and the total power output of clusters,the maximum mutual information coefficient(MIC)method is used to select the reference station and key input characteristic variables.Then,based on the sequencesequence network architecture,combined with the probability prediction characteristics of quantile regression(QR)method and the advantages of WaveNet which can capture a wide range of time-dependent characteristics,a multi-horizon quantile(MQ)-WaveNet model is designed for probability prediction of wind power clusters,which can realize the MQ probability prediction of wind power in multiple steps for wind power clusters.Finally,the operation data of 12 adjacent large-scale wind farms in the southeast wind region of Hami,Xinjiang in China are selected for case study.The results show that the proposed model can effectively predict the power output of wind power clusters only by using the key feature variables of reference stations.The model has low complexity and is easy to be applied in engineering.

关 键 词：风电预测 发电功率 多分位数 多步概率预测 最大互信息系数 波网 

分 类 号：TM614[电气工程—电力系统及自动化]