DocumentCode :
14064
Title :
Switch and Tap-Changer Reconfiguration of Distribution Networks Using Evolutionary Algorithms
Author :
Mendes, Antonio ; Boland, Natashia ; Guiney, P. ; Riveros, Cristian
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Univ. of Newcastle, Callaghan, NSW, Australia
Volume :
28
Issue :
1
fYear :
2013
fDate :
Feb. 2013
Firstpage :
85
Lastpage :
92
Abstract :
The reconfiguration of distribution networks is an important combinatorial problem. This work addresses the particular case of reconfiguration after an outage caused by the loss of a single branch of the network. The reconfiguration is carried out over two domains simultaneously: re-switching strategies and transformer tap-changer adjustments. The approach was tested using a real large-scale network within the concession area of Energy Australia. The model considers four operational elements: an AC power flow model, the network´s radial topology when operating, voltage limits and load limits. Two evolutionary algorithms were implemented and tested. The first was a genetic algorithm, applied over the space of possible re-switching strategies, and for both re-switching and tap-changer adjustments, simultaneously. The second was a memetic algorithm, applied over the same two variations of the reconfiguration problem. Computational tests consider the evaluation of the loss of every branch, reporting the number of buses affected, and the number of overloaded branches after the reconfiguration.
Keywords :
combinatorial mathematics; distribution networks; evolutionary computation; genetic algorithms; on load tap changers; switchgear; AC power flow model; combinatorial problem; computational tests; distribution networks; energy Australia concession area; evolutionary algorithms; genetic algorithm; large-scale network; load limits; memetic algorithm; network radial topology; reswitching strategies; switch reconfiguration; tap-changer reconfiguration; transformer tap-changer adjustments; voltage limits; Australia; Genetic algorithms; Genetics; Memetics; Network topology; Search problems; Switches; Electricity distribution; genetic algorithms; metaheuristics; network reconfiguration; optimization;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2012.2194516
Filename :
6203628
Link To Document :
بازگشت