A Multiobjective Particle Swarm Optimization for Sizing and Placement of DGs from DG Owner's and Distribution Company's Viewpoints

Distributed generations (DGs) have significant benefits in the electric power industry, such as a reduction in CO2 and NOX emissions in electricity generation, improvement of voltage profile in distribution feeders, amending voltage stability in heavy load levels, enhancement of reliability and powe...

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Bibliographic Details
Published in:IEEE transactions on power delivery 2014-08, Vol.29 (4), p.1831-1840
Main Authors: Ameli, Amir, Bahrami, Shahab, Khazaeli, Farid, Haghifam, Mahmood-Reza
Format: Article
Language:English
Subjects:
Applied sciences
Contracts
DG placement and sizing
distributed generation
Economics
electric distribution system
Electric potential
Electric power distribution
Electric power generation
Electric power plants
Electric utilities
Electrical engineering. Electrical power engineering
Electrical power engineering
Electricity distribution
Electricity generation
Exact sciences and technology
Indexes
Investment
Linear programming
Mathematical model
Miscellaneous
multiobjective optimization method
multiobjective particle swarm optimization (MOPSO)
Operation. Load control. Reliability
Placement
Power electronics, power supplies
Power networks and lines
Power system stability
Reduction
Sizing
Swarm intelligence
Voltage
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Summary:Distributed generations (DGs) have significant benefits in the electric power industry, such as a reduction in CO2 and NOX emissions in electricity generation, improvement of voltage profile in distribution feeders, amending voltage stability in heavy load levels, enhancement of reliability and power quality, as well as securing the power market. Despite the numerous advantages of DG technologies, weak capability in dispatching and management of DGs is a major challenge for distribution system operators. Hence, during recent years, several studies about various aspects of control, operation, placement, and sizing of DGs have been conducted. This paper presents a novel application of multiobjective particle swarm optimization with the aim of determining the optimal DGs places, sizes, and their generated power contract price. In the proposed multiobjective optimization, not only are the operational aspects, such as improving voltage profile and stability, power-loss reduction, and reliability enhancement taken into account, but also an economic analysis is performed based on the distribution company's and DG owner's viewpoints. The simulation study is performed on the IEEE 33-bus distribution test system and the consequent discussions prove the effectiveness of the proposed approach.
ISSN:0885-8977
1937-4208
DOI:10.1109/TPWRD.2014.2300845