DocumentCode :
3290721
Title :
Dynamic Reactive Power Planning of Oil Field Distribution Networks Based on Genetic Algorithm
Author :
Xiaomeng, Wu ; Haiyan, Hu
Author_Institution :
Sch. of Electr. Eng., Xi´´an Shiyou Univ., Xi´´an, China
fYear :
2009
fDate :
16-17 May 2009
Firstpage :
752
Lastpage :
754
Abstract :
An approach for low-voltage side reactive power compensators of oil field distribution networks is put forward. The highest investment benefit, which is discounted back to present, is taken as objective function. The restriction of total investment is considered in the form of punishment functions. On the basis of which, an augmented index is established. Every possible installing location of the automatic reactive compensation equipments is regarded as a gene. The value of each gene is the installing time of the corresponding compensation equipment while zero means no compensation equipment needing to install. A genetic algorithm is adopted to determine the optimal dynamic planning results of the compensation equipments on the low voltage side of distribution transformers. The load varying is also considered in the proposed method. Three cases are detailed, such as without limiting total investment, limiting total investment and limiting the investment of every phase showing that the proposed method is feasible.
Keywords :
power distribution planning; reactive power; automatic reactive compensation equipments; dynamic planning; dynamic reactive power planning; genetic algorithm; oil field distribution networks; Circuits; Genetic algorithms; Genetic engineering; Investments; Petroleum; Power engineering and energy; Power system planning; Reactive power; Transformers; Voltage; distribution network; dynamic planning; genetic algorithm; oil field; reactive power compensation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits, Communications and Systems, 2009. PACCS '09. Pacific-Asia Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3614-9
Type :
conf
DOI :
10.1109/PACCS.2009.197
Filename :
5232434
Link To Document :
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