基于有限差分运行域的风电场全风况超短期出力动态区间建模  

Dynamic Interval Modeling of Ultra-short-term Output of Wind Farm Based on Finite Difference Operating Domains

作　　者：胡阳[1,2] 李倩[1] 房方 郝雨辰[3] HU Yang;LI Qian;FANG Fang;HAO Yuchen(School of Control and Computer Engineering,North China Electric Power University,Changping District,Beijing 102206,China;Key Laboratory of Power Station Energy Transfer Conversion and System(North China Electric Power University),Ministry of Education,Changping District,Beijing 102206,China;State Grid Jiangsu Electric Power Company,Nanjing 210017,Jiangsu Province,China)

机构地区：[1]华北电力大学控制与计算机工程学院,北京市昌平区102206 [2]电站能量传递转化与系统教育部重点实验室(华北电力大学),北京市昌平区102206 [3]国网江苏省电力有限公司,江苏省南京市210017

出　　处：《电网技术》2022年第4期1346-1354,共9页Power System Technology

基　　金：国家电网有限公司总部科技项目“基于人工智能的新能源资源分析及预测技术”(NY71-20-039)。

摘　　要：风电功率具有波动大、不确定性强等特点,场级超短期出力在风电机组风况、出力方面的时延性及时空分散性尚未有效解决。首先,针对周期性风向数据,对机组进行风向聚类并划分风向扇区。其次,提出两步相关性分析法,确定对场级出力影响大且相对独立的多元特征风速。然后,基于有限差分运行域定义回归向量,采用长短期记忆神经网络进行超短期时序动态建模,并结合非参数条件核密度估计法和半参数Copula估计法构建区间模型。最后,通过算例仿真验证了动态区间模型的有效性与可靠性。该模型适用分钟级至秒级的风电场动态响应特性建模,对风电场快速一次调频、无功调压等研究具有指导意义。Wind power has the characteristics of large fluctuation and strong uncertainty.The time delay and timespace dispersion of the field level ultra short-term outputs on wind conditions and outputs of wind turbines have not been effectively solved.First,for periodic wind direction data,wind direction clustering is performed and wind direction sectors are divided.Secondly,a two-step correlation analysis method is proposed to determine the multivariate characteristic wind speed which is relatively independent and has a great influence on the field level outputs.Then the regression vector is defined based on the finite difference operating domain,and the long short-term memory neural network is used for ultra-short-term time series dynamic modeling.Combined with the non-parametric conditional kernel density estimation and the semi-parameter Copula method the interval model is constructed.Finally,the validity and reliability of the dynamic interval model is verified by a simulation example.This model is suitable for modeling the dynamic response characteristics of wind farms from minutes to seconds,which has guiding significance for the research of fast primary frequency regulation and reactive power voltage regulation of wind farms.

关 键 词：风力发电 高维风向聚类 扇区划分 多元特征风速 有限差分回归向量 深度学习神经网络 动态区间建模 

分 类 号：TM614[电气工程—电力系统及自动化]