| 采用改进联合正态变换法的随机潮流计算 |
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| 引用本文： | 蔡霁霖,徐青山,丁茂生,王旭东. 采用改进联合正态变换法的随机潮流计算[J]. 电力系统自动化, 2015, 39(23): 104-110 |
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| 作者姓名： | 蔡霁霖 徐青山 丁茂生 王旭东 |
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| 作者单位： | 东南大学电气工程学院, 江苏省南京市 210096,东南大学电气工程学院, 江苏省南京市 210096,国网宁夏电力公司, 宁夏回族自治区银川市 750001,国网天津市电力公司, 天津市 300384 |
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| 基金项目： | 国家自然科学基金资助项目(51377021);国家科技支撑计划资助项目(2013BAA01B00);国家电网公司科技项目(SGTJ0000KXJS1400087) |
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| 摘 要： | 为了对随机潮流计算时电力系统中的相关性因素进行建模,提出了一种改进的联合正态变换(JNT)法。首先,介绍了传统JNT法的基本步骤,分析了JNT法建模时能够保持相关性结构不变的原因。然后,介于核心部分在于将正交变换引入到传统JNT法中,根据JNT法以正态分布为基础这一特性,提出了一种改进JNT法以提高采样效率,并将该采样法与蒙特卡洛法相结合计算系统随机潮流。最后,利用IEEE 30节点网络设计了算例,分别验证了所提出的改进JNT法和随机潮流算法的可行性。
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| 关 键 词： | 相关性建模 联合正态变换(JNT) 蒙特卡洛法 随机潮流 |
| 收稿时间： | 2015-02-12 |
| 修稿时间： | 2015-09-28 |
Stochastic Power Flow Computation Using Improved Joint Normal Transform Method |
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| CAI Jilin,XU Qingshan,DING Maosheng and WANG Xudong. Stochastic Power Flow Computation Using Improved Joint Normal Transform Method[J]. Automation of Electric Power Systems, 2015, 39(23): 104-110 |
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| Authors: | CAI Jilin XU Qingshan DING Maosheng WANG Xudong |
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| Affiliation: | School of Electrical Engineering, Southeast University, Nanjing 210096, China,School of Electrical Engineering, Southeast University, Nanjing 210096, China,State Grid Ningxia Electric Power Company, Yinchuan 750001, China and State Grid Tianjin Electric Power Company, Tianjin 300384, China |
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| Abstract: | An improved joint normal transform (JNT) method is proposed to model the dependence factors in power systems in stochastic power flow computation. First, the procedure for the traditional JNT method is described and the cause of correlation structure remaining unchanged is analyzed with reference to the properties of rank correlations when JNT method is utilized in dependence modelling. Then, the most important part is applying orthogonal transformation to the traditional JNT method according to the characteristic that the JNT method is based on normal distribution. This improved sampling method is combined with Monte Carlo method to calculate the stochastic power flow. Finally, a calculation example is designed to verify the feasibility of the proposed improved JNT method and stochastic power flow algorithm by adjusting the parameters of an IEEE 30-bus network. This work is supported by National Natural Science Foundation of China (No.51377021), National Key Technologies R&D Program (No. 2013BAA01B00) and State Grid Corporation of China (No. SGTJ0000KXJS1400087). |
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| Keywords: | dependence modeling joint normal transform (JNT) Monte Carlo method stochastic power flow |
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