引用本文:周玮,彭昱,孙辉,等.一种用于含风电场电力系统电压稳定概率分析的混合方法[J].电力系统保护与控制,2008,36(2):26-30,53.
ZHOU Wei,PENG Yu,SUN Hui,et al.A mixed method for voltage stability probabilistic analysis of power systems containing wind energy[J].Power System Protection and Control,2008,36(2):26-30,53
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一种用于含风电场电力系统电压稳定概率分析的混合方法
周玮1, 彭昱, 孙辉, 吴敬坤2, 樊飞
1.大连理工大学电气工程系,辽宁 大连 116024;2.东北电力设计院系统规划室,吉林 长春 130021
摘要:
为了进行风电并网后电力系统电压稳定性的评估,利用具有概率特征的负荷裕度指标,提出了一种含风电场电力系统电压稳定概率分析的混合方法。当系统随机参数扰动量很小时将系统简化为线性化模型,根据线性方程的叠加性原理,在计算负荷裕度关于随机参数的灵敏度矩阵的基础上运用叠加性原理并结合正态分布的特性,将系统负荷裕度在期望值附近的随机扰动分解为单独考虑负荷随机变化和风速随机变化两种情况下求得的负荷裕度扰动量之和。该方法与Monte Carlo法和半不变量法同时在IEEE-30节点系统上进行仿真计算,通过对比分析表明了本文方法在保证准确性的基础上节省了计算时间。
关键词:  风电  电压稳定  负荷裕度  叠加原理  灵敏度  半不变量
DOI:10.7667/j.issn.1674-3415.2008.02.007
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A mixed method for voltage stability probabilistic analysis of power systems containing wind energy
ZHOU Wei1, PENG Yu, SUN Hui, WU Jing-kun2, FAN Fei
1.Department of Electrical and Electronic Engineering, Dalian University of Technology, Dalian 116024, China;2.Northeast Electric Power Design Institute, Changchun 130021, China
Abstract:
In order to assess the voltage stability as wind power is integrated into the power system, a method is proposed to analyze probability characteristics of voltage stability based on probabilistic loading margin index. The deviations of these random parameters are small such that linear approximation of loading margin with respect to these parameters is valid. After calculating the sensitivity matrix of loading margin with respect to random parameters, superposition principle is applied to separate the loading margin deviation which varies around the expectation into two parts: load random parameters and wind random parameters respectively. The simulation results of the proposed method compared with those obtained from Monte Carlo method and moment and cumulate method for IEEE-30 test system show that the proposed method is not only precise but also simple and fast.
Key words:  wind power  voltage stability  loading margin  superposition principle  sensitivity  semi-invariant
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