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1.电力传输与功率变换控制教育部重点实验室(上海交通大学),上海市 200240
2.国网宁夏电力有限公司,宁夏回族自治区银川市 750010
3.南瑞集团有限公司(国网电力科学研究院有限公司),江苏省南京市 211106
佘东(1997—),女,硕士研究生,主要研究方向:电力系统时域仿真不确定性分析。E-mail:shedong@sjtu.edu.cn
严正(1964—),男,通信作者,教授,博士生导师,主要研究方向:电力系统优化运行、电力系统稳定分析及智能电网。E-mail:yanz@sjtu.edu.cn
王晗(1993—),男,博士,主要研究方向:电力系统不确定性分析、微电网潮流计算。E-mail:wanghan9894@sjtu.edu.cn
收稿日期:2021-05-16,
修回日期:2021-11-04,
网络出版日期:2022-03-04,
纸质出版日期:2022-10-25
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佘东,严正,王晗等.基于含时序项代理模型的电力系统时域仿真不确定性分析[J].电力系统自动化,2022,46(20):119-128.
SHE Dong,YAN Zheng,WANG Han,et al.Uncertainty Analysis of Time-domain Simulation for Power System Based on Surrogate Model Containing Time Series Terms[J].Automation of Electric Power Systems,2022,46(20):119-128.
佘东,严正,王晗等.基于含时序项代理模型的电力系统时域仿真不确定性分析[J].电力系统自动化,2022,46(20):119-128. DOI: 10.7500/AEPS20210516005.
SHE Dong,YAN Zheng,WANG Han,et al.Uncertainty Analysis of Time-domain Simulation for Power System Based on Surrogate Model Containing Time Series Terms[J].Automation of Electric Power Systems,2022,46(20):119-128. DOI: 10.7500/AEPS20210516005.
随着电力系统中不确定性因素的不断增加,传统确定性的时域仿真分析已难以满足不确定性环境下系统暂态分析的需要。为此,提出了一种基于含时序项代理模型的时域仿真不确定性分析方法。该方法采用非线性有源自回归(NARX)模型表征系统动态特性,利用多项式混沌展开(PCE)方法刻画系统内随机因素的影响,在保证计算精度的同时,提高了时域仿真不确定性分析过程的效率。同时,引入了最小角回归(LAR)策略以选取代理模型的基函数,克服了高维随机变量所引起的维数灾问题。采用标准IEEE 9节点和118节点系统进行仿真,并与传统方法对比,验证了所提方法的准确性和高效性。
With the continuous increase of uncertain factors in power systems
the traditional deterministic time-domain simulation analysis has difficulty in meeting the system transient analysis needs of the power system under uncertain situations. To this end
an uncertainty analysis method of time-domain simulation based on a surrogate model containing time series terms is proposed. This method uses the nonlinear autoregressive with exogenous input (NARX) model to characterize the dynamic characteristics of the power system
as well as using the polynomial chaos expansion (PCE) method to describe the influence of random variables in the power system. While ensuring the calculation accuracy
the efficiency of the uncertainty analysis process of the time domain simulation is increased. At the same time
the least angle regression (LAR) strategy is introduced to select the basis function of the surrogate model
which overcomes the dimensionality disaster problem caused by high-dimensional random variables. The standard IEEE 9-bus system and IEEE 118-bus system are used for simulation
and the accuracy and efficiency of the proposed method are verified compared with the traditional methods.
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