DocumentCode :
647815
Title :
Optimal distribution network reinforcement considering load growth, line loss and reliability
Author :
Ziari, Iman ; Ledwich, Gerard ; Ghosh, A.
Author_Institution :
Sch. of Eng. Syst., Queensland Univ. of Technol., Brisbane, QLD, Australia
fYear :
2013
fDate :
21-25 July 2013
Firstpage :
1
Lastpage :
1
Abstract :
Summary form only given. In this paper, a new comprehensive planning methodology is proposed for implementing distribution network reinforcement. The load growth, voltage profile, distribution line loss, and reliability are considered in this procedure. A time-segmentation technique is employed to reduce the computational load. Options considered range from supporting the load growth using the traditional approach of upgrading the conventional equipment in the distribution network, through to the use of Distributed Generators (DG). The objective function is composed of the construction cost, loss cost and reliability cost. As constraints, the bus voltages and the feeder currents should be maintained within the standard level. The DG output power should not be less than a ratio of its rated power because of efficiency. A hybrid optimization method, called Modified Discrete Particle Swarm Optimization, is employed to solve this nonlinear and discrete optimization problem. A comparison is performed between the optimized solution based on planning of capacitors along with tap-changing transformer and line upgrading and when DGs are included in the optimization.
Keywords :
distributed power generation; particle swarm optimisation; power capacitors; power distribution planning; power distribution reliability; DG output power; computational load; construction cost; discrete optimization problem; distributed generators; distribution line loss; hybrid optimization method; load growth; loss cost; modified discrete particle swarm optimization; nonlinear optimization problem; objective function; optimal distribution network reinforcement; reliability cost; tap-changing transformer; time-segmentation technique; voltage profile; Educational institutions; Generators; Linear programming; Optimization; Planning; Reliability engineering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting (PES), 2013 IEEE
Conference_Location :
Vancouver, BC
ISSN :
1944-9925
Type :
conf
DOI :
10.1109/PESMG.2013.6672358
Filename :
6672358
Link To Document :
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