| 引用本文: | 颜全椿,卫志农,徐泰山,王胜明,孙国强.基于Gauss-Markov模型的电力系统t型抗差状态估计[J].电力自动化设备,2014,34(6): |
| YAN Quanchun,WEI Zhinong,XU Taishan,WANG Shengming,SUN Guoqiang.Robust t-type state estimation based on Gauss-Markov model for power system[J].Electric Power Automation Equipment,2014,34(6): |
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| 摘要: |
| 将t型估计引入状态估计中，提出自适应Gauss-Markov模型的t型抗差状态估计。该方法能够克服传统不良数据辨识程序不能很好地辨识多个强相关不良数据的不足，且与传统状态估计程序具有很好的兼容性，利用t分布的自由度动态调节估计的效率和抗差性。该方法目标函数连续可微，可利用与加权最小二乘（WLS）法类似的牛顿法进行求解。IEEE标准系统和某实际输电网测试验证了所提方法的有效性，与含不良数据辨识功能的WLS估计和二次-常数（QC）估计相比，所提方法的抗差性具有明显的优势。 |
| 关键词: 电力系统 t型估计 自由度 不良数据 局部最优解 状态估计 |
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| 基金项目:国家高技术研究发展计划（863计划）项目（2011AA05A104）；国家自然科学基金资助项目（51107032，51277052，61104045）；国家电网公司科技项目 |
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| Robust t-type state estimation based on Gauss-Markov model for power system |
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YAN Quanchun1, WEI Zhinong1, XU Taishan2, WANG Shengming2, SUN Guoqiang1
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1.Research Center for Renewable Energy Generation Engineering，Ministry of Education，Hohai University，Nanjing 210098，China;2.State Grid Electric Power Research Institute／Nari Group Corporation，Nanjing 210003，China
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| Abstract: |
| The t-type estimation is introduced into the state estimation to form the robust t-type state estimation based on the adaptive Gauss-Markov model，which，compatible with the traditional state estimation program，uses the freedom degree of t-type estimation to dynamically adjust its efficiency and robustness. Its objective function is continuously differentiable and can be solved by the Newton method，similar to the WLS（Weighted Least Square） method. It avoids the shortage of traditional bad data identification program，which cannot identify the strongly correlative bad data effectively. Its effectiveness is verified with IEEE standard system and a practical transmission network，which demonstrates that it has obviously better robustness than WLS estimation and Quadratic-Constant estimation. |
| Key words: electric power systems t-type estimation freedom degree bad data local optimum state estimation |
