采用混合高斯模型及边缘变换技术的蒙特卡洛随机潮流方法
发布时间：2018-10-31 10:44
【摘要】：提出一种计及输入变量相关性的改进蒙特卡洛随机潮流方法。该方法针对系统输入变量多样性和随机性的特点,建立其混合高斯模型并根据测量数据进行参数估计。在蒙特卡洛仿真基础上,引入均匀设计抽样技术提高采样效率,并通过边缘变换和Cholesky分解产生具有相关性的输入变量样本。采用多重线性化手段在加快计算速度的同时减小潮流方程线性化引起的截断误差。对IEEE 30和IEEE 118节点系统的测试分析,验证了所提方法的准确性、快速性和有效性。
[Abstract]:An improved Monte Carlo stochastic power flow method considering the correlation of input variables is proposed. According to the diversity and randomness of input variables, the mixed Gao Si model is established and the parameters are estimated according to the measured data. On the basis of Monte Carlo simulation, uniform design sampling technique is introduced to improve sampling efficiency, and correlation input variable samples are generated by edge transform and Cholesky decomposition. The method of multiple linearization is used to speed up the calculation and reduce the truncation error caused by linearization of power flow equation. The accuracy, rapidity and validity of the proposed method are verified by testing and analyzing the IEEE 30 and IEEE 118 bus systems.
【作者单位】： 东南大学电气工程学院;国网江苏省电力公司电力科学研究院;
【基金】：国家自然科学基金资助项目(51377021) 中央高校基本科研业务费专项资金资助项目(2242016K41064) 国家电网公司科技项目“新能源发电预测误差对电网安全运行影响评价方法研究”~~
【分类号】：TM712;TM744
，
本文编号：2301882
[Abstract]:An improved Monte Carlo stochastic power flow method considering the correlation of input variables is proposed. According to the diversity and randomness of input variables, the mixed Gao Si model is established and the parameters are estimated according to the measured data. On the basis of Monte Carlo simulation, uniform design sampling technique is introduced to improve sampling efficiency, and correlation input variable samples are generated by edge transform and Cholesky decomposition. The method of multiple linearization is used to speed up the calculation and reduce the truncation error caused by linearization of power flow equation. The accuracy, rapidity and validity of the proposed method are verified by testing and analyzing the IEEE 30 and IEEE 118 bus systems.
【作者单位】： 东南大学电气工程学院;国网江苏省电力公司电力科学研究院;
【基金】：国家自然科学基金资助项目(51377021) 中央高校基本科研业务费专项资金资助项目(2242016K41064) 国家电网公司科技项目“新能源发电预测误差对电网安全运行影响评价方法研究”~~
【分类号】：TM712;TM744
，
本文编号：2301882
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