DocumentCode :
2739568
Title :
A Novel Method for Online Nodal Load Estimation of Middle Voltage Distribution Networks
Author :
Wu, Jianzhong ; Yu, Yixin
Author_Institution :
Sch. of Electr. Eng. & Autom., Tianjin Univ.
Volume :
2
fYear :
0
fDate :
0-0 0
Firstpage :
7622
Lastpage :
7626
Abstract :
A novel method is proposed for solving online nodal load estimation of middle voltage distribution networks systematically. Firstly the solution strategies are introduced, and then the algorithm is presented. The proposed method consists of three phases that are crude load estimation, load forecasting and robust load estimation. Three load allocation methods are offered in crude load estimation phase which can provide crude load values. A case-based fuzzy-neural network is utilized in load forecasting phase for supplying nodal load forecasting values. Robust load estimation has been robustified synthetically in both structure space and measurement space, which can effectively withstand the influence of gross errors and many small errors. The three phases of load estimation cooperate closely and form a closed-cycle information flow. The proposed method can run online and can provide reliable and consistent load data set for control and management of distribution networks
Keywords :
fuzzy neural nets; load forecasting; power distribution control; power system management; closed-cycle information flow; crude load estimation; fuzzy neural network; load forecasting; middle voltage distribution networks; online nodal load estimation; power systems; robust load estimation; Automation; Electronic mail; Extraterrestrial measurements; Intelligent control; Load forecasting; Phase estimation; Robustness; Voltage; distribution networks; load estimation; load forecasting; power systems; robust estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1713449
Filename :
1713449
Link To Document :
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