文章摘要
邹金,朱继忠,赖旭,等.基于时空自回归移动平均模型的风电出力序列模拟[J].电力系统自动化,2019,43(3):101-107. DOI: 10.7500/AEPS20180328002.
ZOU Jin,ZHU Jizhong,LAI Xu, et al.Simulation of Wind Power Output Series Based on Space-time Auto-regressive Moving Average Model[J].Automation of Electric Power Systems,2019,43(3):101-107. DOI: 10.7500/AEPS20180328002.
基于时空自回归移动平均模型的风电出力序列模拟
Simulation of Wind Power Output Series Based on Space-time Auto-regressive Moving Average Model
DOI:10.7500/AEPS20180328002
关键词: 风电出力  时空序列  时空自回归移动平均模型  时空相关性  多维时间序列
KeyWords: wind power output  space-time series  space-time auto regressive moving average (ST-ARMA) model  space-time correlation  multi-dimensional time series
上网日期:2018-12-14
基金项目:国家自然科学基金资助项目(51379159);南方电网公司总部技术研究服务专项项目(ZBKJXM20180064);广东省珠江人才计划资助项目(SEPRI-K172001)
作者单位E-mail
邹金 南方电网科学研究院有限责任公司, 广东省广州市 510080 zoujin@csg.cn 
朱继忠 南方电网科学研究院有限责任公司, 广东省广州市 510080  
赖旭 水资源与水电工程科学国家重点实验室(武汉大学), 湖北省武汉市 430072  
谢平平 南方电网科学研究院有限责任公司, 广东省广州市 510080  
禤培正 南方电网科学研究院有限责任公司, 广东省广州市 510080  
摘要:
      多风电场出力序列间的时空耦合相关性对风电并网下的电力系统运行具有重要影响。时空自回归移动平均(ST-ARMA)模型以较为简洁的形式对多维序列时空耦合相关性进行统计建模。针对多风电场出力时空序列的模拟问题,首先从时空序列的角度对风电场实测功率数据进行了统计分析,着重探讨了多风电场出力的时空耦合相关性。在此基础上,采用空间关系矩阵对风电场位置进行描述,并将其嵌入ST-ARMA模型的自回归过程建立多风电场出力序列的时空耦合相关性模型。该模型有效地模拟了实测风电场出力序列的时间相关性、空间相关性以及二者之间的耦合特性,可用于产生大量与实际风电出力统计特性相同的模拟数据,为风电并网下的电力系统运行与规划研究提供数据基础。
Abstract:
      The coupled space-time correlation among output series in multiple wind farms has great effects on the operation of power systems. Space-time auto regressive moving average (ST-ARMA) model can restore statistical model of coupled space-time correlation of multi-dimensional sequences in a relatively simple form. In order to build an effective model for multi-dimensional wind power series, the measured wind power data from the perspective of space-time series are statistically analyzed, especially for the coupled space-time correlation. Then, a spatial relation matrix is used to describe the location of each wind farm, and embedded into the auto regression process of ST-ARMA model in order to simulate the coupled space-time correlation of wind power series. The ST-ARMA model has restored not only the temporal and spatial correlation of original wind power series, but also the coupled characteristic between the two kinds of correlation. This model can be used to produce huge amount of simulation data with the same characteristics of actual wind power output, which is able to provide data basics for the planning and operation research of wind power integration.
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