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同调机群
相关语句
  coherent generator groups
    Improved Fuzzy ISODATA Method for Identification of Coherent Generator Groups
    改进模糊ISODATA法识别电力系统同调机群
短句来源
    Coherent Generator Groups Recognizing Study Based on Fuzzy Clustering Theory
    基于模糊聚类理论的电力系统同调机群识别研究
短句来源
    Research of recognizing coherent generator groups in power system is important to dynamic equivalence, transient stability calculation and provides essential data for improving system's behavior.
    发电机同调机群识别的研究对动态等值、暂态稳定分析计算、为改进系统行为的控制设备的设计、操作和整定提供必要数据等方面有极其重要的意义。
短句来源
    Secondly, two math models based on the fuzzy clustering in recognizing coherent generator groups has been deduced.
    其次,本文推导了基于模糊聚类分析识别同调机群的两种数学模型。
短句来源
    In this paper,the fuzzy clustering method is introduced to identify coherent generator groups in power system.
    引入模糊聚类方法识别电力系统同调机群
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  “同调机群”译为未确定词的双语例句
    Distinguishing Method of Coherency Set Group in Electric Power System
    电力系统同调机群的识别方法
短句来源
    Under study of the distinguishing method of the coherency set group inelectric power system,all the former distinguishing methods of the coherency setgroups were summed up and directed against the problems of the methods,a newpractical distinguishing method of the coherency set group was given out.
    在对电力系统中同调机群的识别方法进行研究的同时,并对以往的各种同调机群的识别方法也进行了归纳总结,针对这些方法所存在的问题,给出了一种新的较为实用的同调机群识别方法。
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Under study of the distinguishing method of the coherency set group inelectric power system,all the former distinguishing methods of the coherency setgroups were summed up and directed against the problems of the methods,a newpractical distinguishing method of the coherency set group was given out.

在对电力系统中同调机群的识别方法进行研究的同时,并对以往的各种同调机群的识别方法也进行了归纳总结,针对这些方法所存在的问题,给出了一种新的较为实用的同调机群识别方法。

Through the simulation analysis of large-scale power system,it is found that the out-of-step generators may behave in two groups,the main out-of-step generator groups and the minor out-of-step generator groups.The main out-of-step generator groups can determine the out-of-step center interface tie-lines of large-scale power system,but the minor out-of-step generator groups cannot.This phenomenon facilitates a method of capturing the out-of-step center interface tie-lines,based on searching the lowest voltage...

Through the simulation analysis of large-scale power system,it is found that the out-of-step generators may behave in two groups,the main out-of-step generator groups and the minor out-of-step generator groups.The main out-of-step generator groups can determine the out-of-step center interface tie-lines of large-scale power system,but the minor out-of-step generator groups cannot.This phenomenon facilitates a method of capturing the out-of-step center interface tie-lines,based on searching the lowest voltage points (center of out-of-step) during the system out-of-step state.By doing so,the main out-of-step generator groups can be identified.But the method maybe fails to split the minor out-of-step generators into the correct coherent out-of-step generator groups.Hence,in engineering practice,the generators which are likely to be in the minor ou-of- step groups should be equipped with the out-of-step separation equipment based on the off-line system analysis.Thus with the backup of the separation devices,further accident will be avoided.

通过对大规模电网的失步仿真研究发现,当系统失步时失步机群可能会呈现为主要失步机群和次要失步机群2种失步模式。主要失步机群决定着整个大区电网的失步中心断面联络线,而次要失步机群不能决定整个大区电网的失步中心断面联络线。该现象将导致通过捕捉失步断面电压最低点(失步中心)寻找失步断面联络线的方法一般只能将主要失步机群分开,却未必能够将次要失步机群也合理分布到与之同调的机群之中。因此,工程中应结合系统离线仿真分析,尽可能对有可能成为次要失步模式的机组安装失步解列装置,以作为一种后备,防止次要失步模式机组扰动系统,造成事故扩大。

In this paper,the fuzzy clustering method is introduced to identify coherent generator groups in power system.A large number of simulations are performed to choose the control parameters of primary fuzzy ISODATA method,and some experienced values of the optimization parameters are given.The best categorizing number is determined by adopting fuzzy F statistical value.The algorithm is improved according to the features of coherent generator groups identification,which makes it much more adaptive to engineering...

In this paper,the fuzzy clustering method is introduced to identify coherent generator groups in power system.A large number of simulations are performed to choose the control parameters of primary fuzzy ISODATA method,and some experienced values of the optimization parameters are given.The best categorizing number is determined by adopting fuzzy F statistical value.The algorithm is improved according to the features of coherent generator groups identification,which makes it much more adaptive to engineering application.Finally,the simulation on EPRI 36-bus AC system shows the effectiveness of the proposed method.

引入模糊聚类方法识别电力系统同调机群。首先对原有的基于模糊相关自组织数据分析算法(iterativese lf-organ iz ing data ana lys is techn iques a lgorithm,ISODATA)的同调机群识别法的各个控制参数的选取问题进行了大量仿真实验,给出了优化参数取值的一些经验值。特别在如何确定最优分类数的问题上引入了模糊F统计量的方法,并根据电力系统同调识别的特点改进了模糊相关自组织数据分析算法的同调机群识别算法,使其更能适用于工程应用。最后用EPR I_36节点纯交流系统的仿真计算验证了该方法的有效性。

 
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