An Improved Particle Swarm Optimization Algorithm for Optimal Allocation of Distributed Generation Units in Radial Power Systems
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Original research
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In this paper, an improved particle swarm optimization method (PSO) is proposed to optimally size and place a DG unit in an
electrical power system so as to improve voltage profile and reduce active power losses in the system. An IEEE 34 distribution bus
system is used as a case study for this research. A new equation of weight inertia is proposed so as to improve the performance of
the PSO conventional algorithm. -is development is done by controlling the inertia weight which affects the updating velocity of
particles in the algorithm. Matlab codes are developed for the adapted electrical power system and the improved PSO algorithm.
Results show that the proposed PSO algorithm successfully finds the optimal size and location of the desired DG unit with a
capacity of 1.6722MW at bus number 10. -is makes the voltage magnitude of the selected bus equal to 1.0055 pu and improves
the status of the electrical power system in general. -e minimum value of fitness losses using the applied algorithm is found to be
0.0.0406 while the average elapsed time is 62.2325 s. In addition to that, the proposed PSO algorithm reduces the active power
losses by 31.6%. -is means that the average elapsed time is reduced by 21% by using the proposed PSO algorithm as compared to
the conventional PSO algorithm that is based on the liner inertia weight equation.
 

Journal
Title
Hindawi Applied Computational Intelligence and So Computing
Publisher
Hindawi Applied Computational Intelligence and So Computing
Publisher Country
United Kingdom
Publication Type
Both (Printed and Online)
Volume
2020
Year
2020
Pages
8