Optimal voltage support mechanism in distribution networks


Autoria(s): Ziari, Iman; Ledwich, Gerard; Ghosh, Arindam
Data(s)

2011

Resumo

Optimal scheduling of voltage regulators (VRs), fixed and switched capacitors and voltage on customer side of transformer (VCT) along with the optimal allocaton of VRs and capacitors are performed using a hybrid optimisation method based on discrete particle swarm optimisation and genetic algorithm. Direct optimisation of the tap position is not appropriate since in general the high voltage (HV) side voltage is not known. Therefore, the tap setting can be determined give the optimal VCT once the HV side voltage is known. The objective function is composed of the distribution line loss cost, the peak power loss cost and capacitors' and VRs' capital, operation and maintenance costs. The constraints are limits on bus voltage and feeder current along with VR taps. The bus voltage should be maintained within the standard level and the feeder current should not exceed the feeder-rated current. The taps are to adjust the output voltage of VRs between 90 and 110% of their input voltages. For validation of the proposed method, the 18-bus IEEE system is used. The results are compared with prior publications to illustrate the benefit of the employed technique. The results also show that the lowest cost planning for voltage profile will be achieved if a combination of capacitors, VRs and VCTs is considered.

Identificador

http://eprints.qut.edu.au/40768/

Publicador

The Institution of Engineering and Technology (IET)

Relação

DOI:10.1049/iet-gtd.2010.0277

Ziari, Iman, Ledwich, Gerard, & Ghosh, Arindam (2011) Optimal voltage support mechanism in distribution networks. IET Generation, Transmission & Distribution, 5(1), pp. 127-135.

Direitos

Copyright 2011 The Institution of Engineering and Technology (IET)

Fonte

Faculty of Built Environment and Engineering; School of Design; School of Engineering Systems

Palavras-Chave #090600 ELECTRICAL AND ELECTRONIC ENGINEERING #Capacitor Switching #Costing #Genetic Algorithms #Particle Swarm Optimisation #Power Distribution Economics #Power Distribution Planning
Tipo

Journal Article