TY - JOUR
T1 - An improved gravitational search algorithm for optimal placement and sizing of renewable distributed generation units in a distribution system for power quality enhancement
AU - Fazliana Abdul Kadir, Aida
AU - Mohamed, Azah
AU - Shareef, Hussain
AU - Asrul Ibrahim, Ahmad
AU - Khatib, Tamer
AU - Elmenreich, Wilfried
PY - 2014/5
Y1 - 2014/5
N2 - Distributed generation (DG) is an important element to be considered in distribution planning since it plays a major role in stability and power quality improvement. This paper presents a new method for determining optimal sizing and placement of DG in a distribution system. A multi-objective function is formed to minimize the total losses, average total voltage harmonic distortion, and voltage deviation in the distribution system. The improved gravitational search algorithm (IGSA) is proposed as an optimization techniques and its performance is compared with other optimization techniques such as particle swarm optimization (PSO) and GSA. The load flow algorithm from MATPOWER and harmonic load flow was integrated in MATLAB environment to solve the proposed multi-objective function. Finally, the proposed algorithm is tested on the radial 69-bus distribution system with three case studies. The results show that the IGSA performs better than PSO and GSA by giving the best fitness value and the fastest average elapsed time.
AB - Distributed generation (DG) is an important element to be considered in distribution planning since it plays a major role in stability and power quality improvement. This paper presents a new method for determining optimal sizing and placement of DG in a distribution system. A multi-objective function is formed to minimize the total losses, average total voltage harmonic distortion, and voltage deviation in the distribution system. The improved gravitational search algorithm (IGSA) is proposed as an optimization techniques and its performance is compared with other optimization techniques such as particle swarm optimization (PSO) and GSA. The load flow algorithm from MATPOWER and harmonic load flow was integrated in MATLAB environment to solve the proposed multi-objective function. Finally, the proposed algorithm is tested on the radial 69-bus distribution system with three case studies. The results show that the IGSA performs better than PSO and GSA by giving the best fitness value and the fastest average elapsed time.
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U2 - 10.1063/1.4878997
DO - 10.1063/1.4878997
M3 - Article
AN - SCOPUS:84901308966
SN - 1941-7012
VL - 6
JO - Journal of Renewable and Sustainable Energy
JF - Journal of Renewable and Sustainable Energy
IS - 3
M1 - 033112
ER -