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| 一种电力系统量测噪声自适应抗差状态估计方法 | |
| 引用本文： | 陈艳波,马进,文一宇. 一种电力系统量测噪声自适应抗差状态估计方法[J]. 电力系统自动化, 2015, 39(8): 66-73 |
| 作者姓名： | 陈艳波 马进 文一宇 |
| 作者单位： | 1. 新能源电力系统国家重点实验室，华北电力大学，北京市 102206 2. School of Electrical and Information Engineering，University of Sydney，NSW 2006，澳大利亚 3. 国网重庆市电力公司电力科学研究院,重庆市,400015 |
| 基金项目： | 国家高技术研究发展计划(863计划)资助项目(2012AA050208);国家自然科学基金资助项目(51407069);中央高校基本科研业务费专项资金资助项目(2014QN02) |
| 摘 要： | 为克服传统状态估计方法在处理量测噪声方面的局限性,文中首先提出一种基于最大相关熵准则的抗差状态估计一般模型,该模型可从理论上统一已有的几种抗差状态估计方法,并可导出新的抗差状态估计方法。在此基础上提出一种量测噪声自适应抗差状态估计方法(ARSE),ARSE能够通过统计学习获得量测噪声的分布规律,并与所提出的抗差状态估计一般模型进行在线匹配,从而实现对量测噪声类型的自适应,即在常见的量测噪声分布类型下,ARSE可得到更接近于状态变量真值的估计结果。最后通过仿真算例验证了所述方法的有效性。 |
| 关 键 词： | 抗差状态估计 自适应估计 状态估计 最大相关熵准则 电力系统 |
| 收稿时间： | 2014-04-02 |
| 修稿时间： | 2014-10-29 |
An Adaptive Robust State Estimation Approach for Measurement Noise |
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| CHEN Yanbo,MA Jin and WEN Yiyu. An Adaptive Robust State Estimation Approach for Measurement Noise[J]. Automation of Electric Power Systems, 2015, 39(8): 66-73 | |
| Authors: | CHEN Yanbo MA Jin WEN Yiyu |
| Affiliation: | State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China,School of Electrical and Information Engineering, University of Sydney, NSW 2006, Australia and State Grid Chongqing Electric Power Research Institute, Chongqing 400015, China |
| Abstract: | To overcome the limitations of traditional state estimation in dealing with noise measurement, a general model of robust state estimation (RSE) is proposed based on maximum correntropy criterion (MCC), which is able to unify several existing RSE models in theory and derive new RSE models. An adaptive robust state estimator (ARSE) for measuring noise is proposed, which makes it possible to obtain the distribution type of noise measurement through statistical learning. Then the corresponding optimal RSE model is selected online to adapt to the variation of noise measuring distribution type. ARSE is able to yield optimal estimation results closer to the true values of the state variables for common noise measuring distribution types. Simulation results show the effectiveness of the proposed ARSE. This work is supported by National High Technology Research and Development Program of China (863 Program) (No. 2012AA050208), National Natural Science Foundation of China (No. 51407069) and the Fundamental Research Funds for the Central Universities (No. 2014QN02). |
| Keywords: | robust state estimation adaptive estimation state estimation maximum correntropy criterion power systems |
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