DocumentCode :
265215
Title :
Parameter error identification method for multi-doubtful parameters of power grid
Author :
Haoming Liu ; Yongxin Liang ; Kangle He ; Jianchao Wu
Author_Institution :
Coll. of Energy & Electr. Eng., Hohai Univ., Nanjing, China
fYear :
2014
fDate :
4-7 June 2014
Firstpage :
286
Lastpage :
289
Abstract :
Parameter error affects the quality of state estimation and the application of other senior software in energy management system (EMS). When there are multiple bad data of remote measurement and parameter errors, it is important to ensure the effectiveness of state estimation. This paper proposes an effective and practical parameter error identification method for essential data of power grid. Firstly, percentage residuals of all measuring data are calculated to obtain the set of suspicious measuring points and further the set of suspicious branches. Then, correlation indices of suspicious branches are calculated and sorted to get a descending sequence. The suspicious parameter corresponding to a suspicious branch is adjusted based on the Newton downhill method. Case study on a simple 5-node network and a practical power grid shows that the method purposed can identify the network parameter error and the measuring data error simultaneously, thus improving the accuracy of state estimation on essential data of power grid operation.
Keywords :
energy management systems; least squares approximations; power grids; power system state estimation; EMS; Newton downhill method; correlation index; energy management system; multidoubtful parameters; network parameter error identification method; power grid; power system state estimation; suspicious branches; Automation; Conferences; Control systems; Intelligent systems; correlation index; essential data; parameter identification; suspicious branch;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2014 IEEE 4th Annual International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4799-3668-7
Type :
conf
DOI :
10.1109/CYBER.2014.6917476
Filename :
6917476
Link To Document :
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