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Particle Swarm Optimization for the Minimization of Power Losses in Distribution Networks

Authors: Joseph B. Abugri; Marc Karam;

Particle Swarm Optimization for the Minimization of Power Losses in Distribution Networks

Abstract

This research utilizes particle swarm optimization (PSO) to minimize the total active power losses in an IEEE 6-bus transmission system. The complexity of the problem lies in integrating Newton-Raphson load flow algorithm, which is used in computing power losses, with PSO algorithm, which is used to minimize these losses. The considered PSO control variables are: the reactive power output of generators, the tap ratios of transformers, and the reactive power output of shunt compensators. PSO was chosen as optimization method due to its popularity as a successful algorithm in solving non-smooth global optimization problems. The proposed PSO algorithm gave very satisfactory simulation results. Power losses were reduced by 13.9% for an initial set of PSO parameters. These parameters were thereafter varied in order to improve PSO performance by further minimizing the power losses. Effectively, we were able to obtain a set of parameters that resulted in a 19.31% reduction in power losses. These successful simulation results confirm the effectiveness of PSO in minimizing distribution networks power losses.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Top 10%
Average
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