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基于随机配置点法的概率潮流算法
引用本文:孙英云,毛瑞,董雷,蒲天骄,于汀.基于随机配置点法的概率潮流算法[J].电力系统自动化,2015,39(23):111-118.
作者姓名:孙英云  毛瑞  董雷  蒲天骄  于汀
作者单位:新能源电力系统国家重点实验室(华北电力大学), 北京市 102206,新能源电力系统国家重点实验室(华北电力大学), 北京市 102206,新能源电力系统国家重点实验室(华北电力大学), 北京市 102206,中国电力科学研究院, 北京市 100192,中国电力科学研究院, 北京市 100192
基金项目:国家重点基础研究发展计划(973计划)资助项目 (2012CB215203);国家自然科学基金资助项目(50907034)
摘    要:可再生能源的大量接入使得电力系统的不确定性增加,对电力系统的运行和控制提出了新的挑战。从不确定性量化理论出发,提出了一种基于随机配置点法的概率潮流算法。该算法将不确定性输入变量的概率分布表述为广义多项式混沌的谱系数,通过构建一个规模可控的确定性非线性方程组,将待求变量的概率分布函数求解转换为广义多项式混沌的谱系数求解问题,可较好地解决概率潮流计算中求解精度和计算复杂度之间的矛盾。在IEEE 14节点和IEEE 118节点系统的仿真计算中,该算法的有效性、实用性和准确性得到了验证,对于含新能源并网的概率潮流等不确定性问题具有较好的工程应用前景。

关 键 词:不确定性量化    正交多项式混沌    概率潮流    随机配置点法
收稿时间:3/6/2015 12:00:00 AM
修稿时间:2015/11/3 0:00:00

Probabilistic Load Flow Algorithm Based on Stochastic Collocation Method
SUN Yingyun,MAO Rui,DONG Lei,PU Tianjiao and YU Ting.Probabilistic Load Flow Algorithm Based on Stochastic Collocation Method[J].Automation of Electric Power Systems,2015,39(23):111-118.
Authors:SUN Yingyun  MAO Rui  DONG Lei  PU Tianjiao and YU Ting
Affiliation:State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Beijing 102206, China,State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Beijing 102206, China,State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Beijing 102206, China,China Electric Power Research Institute, Beijing 100192, China and China Electric Power Research Institute, Beijing 100192, China
Abstract:The development of intermittent energy significantly enhances the operation uncertainty of power systems,posing new challenges to power system operation and control. Based on the uncertainty quantification (UQ) theory, this paper proposes a stochastic collocation probabilistic load flow (PLF) algorithm, which utilizes the generalised polynomial chaos (gPC). By constructing affordable deterministic nonlinear equations, the solutions, or quantities of interest, are expressed as convergent series of gPC expansions in terms of random inputs, with their distribution functions solved by calculating the spectral coefficients of gPC expansions. This algorithm is capable of solving the contradiction between accuracy and computational complexity. The effectiveness, practicality and accuracy of the proposed algorithm is proved by the simulation of IEEE14-bus and IEEE118-bus systems, which shows that it has good engineering application prospects in PLF analysis for renewable energy connected power systems. This work is supported by National Basic Research Program of China (973 Program) (No. 2012CB215203) and National Natural Science Foundation of China (No. 50907034).
Keywords:uncertainty quantification  generalised polynomial chaos  probabilistic load flow  stochastic collocation method
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