DocumentCode :
2581163
Title :
Model Design for Transmission Congestion Management Based on Fuzzy Programming
Author :
Zhao, Yu ; Zhao, Bo ; Qi, Chunjie
Author_Institution :
Coll. of Econ. & Manage., Huazhong Agric. Univ., Wuhan
fYear :
2009
fDate :
23-25 Jan. 2009
Firstpage :
355
Lastpage :
358
Abstract :
Based on data collected previously on the electricity market of the East China, we use stepwise regression method to find the approximate expression of the active power flow of each power sets on East Chinapsilas certain electrical network. Then classified discussion is carried out according to the difference of the capacity in and out of merit in order to obtain a simple and reasonable rule for calculating the block cost. Based on this, the objective programming model for output distribution of each unit is achieved. Exclude conditions step by step, and adjust the output allocation plan. Introduce flexible factors defining membership function to change fuzzy programming into non-fuzzy programming, and use genetic algorithm to get solution. The model considers both safety and cost so that different network operators can get their preferred allocation plan.
Keywords :
distribution networks; fuzzy set theory; genetic algorithms; load flow; power markets; power transmission; regression analysis; East China certain electrical network; active power flow; data collection; electricity market; fuzzy programming; genetic algorithm; objective programming model; stepwise regression method; transmission congestion management; Costs; Economic forecasting; Educational institutions; Electricity supply industry; Energy management; Functional programming; Knowledge management; Power generation; Power generation economics; Safety; electrical network; fuzzy programming; model design; multiobjective optimization; transmission congestion management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge Discovery and Data Mining, 2009. WKDD 2009. Second International Workshop on
Conference_Location :
Moscow
Print_ISBN :
978-0-7695-3543-2
Type :
conf
DOI :
10.1109/WKDD.2009.8
Filename :
4771949
Link To Document :
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