| 引用本文: | 徐伟,刘建坤,胡昊明,赵静波.基于集群计算的特大型电网特征值搜索策略[J].电力系统保护与控制,2017,45(2):42-47.[点击复制] |
| XU Wei,LIU Jiankun,HU Haoming,ZHAO Jingbo.Eigenvalue searching strategy for ultra large scale power grid based on cluster computing[J].Power System Protection and Control,2017,45(2):42-47[点击复制] |
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| 摘要: |
| 针对隐式重启动Arnoldi算法无法自动搜索指定区域所有特征值的问题，设计了一种基于集群计算的特征值搜索策略，满足特大型电网小干扰稳定在线分析对计算结论准确性和实时性的要求。将待搜索区域划分为多个面积相同的区域，通过对搜索圆盘无法完全覆盖的区域设置更多的位移点来提高计算速度。采用正方形来划分待搜索区域，通过比较搜索圆盘内切正方形和待搜索正方形区域的大小实现待搜索区域是否被完全覆盖的自动判别。对华东电网的在线数据进行了分析计算，验证了搜索策略的正确性和有效性。 |
| 关键词: 小干扰稳定分析 隐式重启动Arnoldi算法 位移求逆变换 集群计算 |
| DOI：10.7667/PSPC160141 |
| 投稿时间：2016-01-25修订日期：2016-03-22 |
| 基金项目:中国博士后科学基金项目(2016M591738);江苏省博士后科研资助计划项目(1601160C) |
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| Eigenvalue searching strategy for ultra large scale power grid based on cluster computing |
| XU Wei,LIU Jiankun,HU Haoming,ZHAO Jingbo |
| (State Grid Jiangsu Electric Power Company Research Institute, Nanjing 211103, China) |
| Abstract: |
| Since implicit restarted Arnoldi algorithm cannot obtain all eigenvalues in a designated area automatically, an eigenvalue searching strategy based on cluster computing is proposed to satisfy the requirements of accuracy and speed of online small signal stability analysis for ultra large scale power grid. Searching area is divided into several areas with same size and shift is appointed in each area to determine areas consisting more eigenvalues. Such area will be designated multi shifts to improve calculating speed. Square will be chosen to divide the searching area. Uncovered square can be identified automatically by comparing with the inscribed square of the circle area formed by the eigenvalues of a shift. The analysis results of East China Power Grid online data validate the correctness and efficiency of the proposed strategy. This work is supported by China Postdoctoral Science Foundation (No. 2016M591738) and Postdoctoral Science and Technology Program of Jiangsu Province (No. 1601160C). |
| Key words: small signal stability analysis implicit restarted Arnoldi algorithm shift-invert transformation cluster computing |
