| 基于不确定测度的电力系统抗差状态估计：(三)算法对比 |
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| 引用本文： | 陈艳波,谢瀚阳,王鹏,王金丽,葛婷,王若兰. 基于不确定测度的电力系统抗差状态估计：(三)算法对比[J]. 电力系统自动化, 2018, 42(3): 8-13 |
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| 作者姓名： | 陈艳波 谢瀚阳 王鹏 王金丽 葛婷 王若兰 |
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| 作者单位： | 华北电力大学电气与电子工程学院, 北京市 102206,广东电网有限责任公司信息中心, 广东省广州市 510600,中国电力科学研究院有限公司, 北京市 100192,中国电力科学研究院有限公司, 北京市 100192,华北电力大学电气与电子工程学院, 北京市 102206,华北电力大学电气与电子工程学院, 北京市 102206 |
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| 基金项目： | 国家自然科学基金资助项目(51777067)；中央高校基本科研业务费专项资金资助项目(2016YQ02) |
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| 摘 要： | 针对所提出的基于兼顾测点正常率的偏离度最小准则的最大正常率最小偏差度估计方法,运用大量算例与已有的加权最小二乘、加权最小绝对值、非二次准则和基于测量不确定度的估计方法进行对比研究。结果表明,所述方法对强相关的多不良数据、杠杆点不良数据均具有较强的抑制能力,在计算效率上也能满足大系统的要求。
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| 关 键 词： | 抗差状态估计；不确定测度；强相关不良数据；杠杆点 |
| 收稿时间： | 2016-12-13 |
| 修稿时间： | 2017-11-29 |
Uncertain Measure Based Robust State Estimation of Power System Part Three Algorithm Comparison |
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| CHEN Yanbo,XIE Hanyang,WANG Peng,WANG Jinli,GE Ting and WANG Ruolan. Uncertain Measure Based Robust State Estimation of Power System Part Three Algorithm Comparison[J]. Automation of Electric Power Systems, 2018, 42(3): 8-13 |
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| Authors: | CHEN Yanbo XIE Hanyang WANG Peng WANG Jinli GE Ting WANG Ruolan |
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| Affiliation: | School of Electrical & Electronic Engineering, North China Electric Power University, Beijing 102206, China,Information Center of Guangdong Power Grid Co. Ltd., Guangzhou 510600, China,China Electric Power Research Institute, Beijing 100192, China,China Electric Power Research Institute, Beijing 100192, China,School of Electrical & Electronic Engineering, North China Electric Power University, Beijing 102206, China and School of Electrical & Electronic Engineering, North China Electric Power University, Beijing 102206, China |
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| Abstract: | The least deviation estimation method of maximum normal rate based on the minimum deviation criterion considering the normal rate of measuring point is proposed. A large number of examples are tested to make a comparison among the method proposed above and the existing methods of weighted least squares, weighted minimum absolute value, non-quadratic criterion and estimation method based on measurement uncertainty. The results show that the method proposed has a strong ability to suppress the bad data with strong correlation and bad data of leverage. The computational efficiency can also meet the requirements of large-scale systems. |
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| Keywords: | robust state estimation uncertain measure multi-objective bad data with strong correlation leverage point |
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