Title: An efficient coupled GA and load flow algorithm for optimal placement and sizing of distributed generators

Authors: Nadim Makhol, Mohsen Mohammadi Alamuti, Hassan Nouri

Addresses: Faculty of Mechanical and Electrical Engineering, Department of Electrical Power Engineering, Damascus University, Damascus, Syria. ' Power Systems and Electronics Research Group, University of the West of England, Bristol, UK. ' Power Systems and Electronics Research Group, University of the West of England, Bristol, UK

Abstract: A genetic algorithm is used in conjunction with an efficient load flow programme to determine the optimal locations and sizing of the predefined DGs within MATLAB software. The best location for the DGs and the sizing of the DGs are determined using the genetic algorithm. The branch electrical loss is considered as the objective function and the system total loss represent the fitness evaluation function for driving the GA. The load flow equations are considered as equality constraints and the equations of nodal voltage and branch capacity are considered as inequality constraints. The approach is tested on a 15 bus IEEE distribution feeder.

Keywords: distribution networks; distributed generation; loss reduction; genetic algorithms; GAs; load flow; optimisation; generator placement; generator sizing; distributed generators; electrical loss.

DOI: 10.1504/IJPEC.2010.030861

International Journal of Power and Energy Conversion, 2010 Vol.2 No.1, pp.59 - 77

Published online: 10 Jan 2010 *

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