Multi-objective optimization of accommodating distributed generation considering power loss, power quality, and system stability

This paper attempts to investigate the multi-objective optimization (MOO) of accommodating distributed generation (DG) based on a modified multi-objective particle swarm optimization algorithm (MMPSO). In view of the significance of economic operation, power quality and system stability, MOO model w...

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Bibliographic Details
Published in:Journal of industrial and production engineering Vol. 31; no. 3; pp. 146 - 154
Main Authors: Cheng, Shan, Qin, Tian-Ya, Jing, Li-Bing
Format: Journal Article
Language:English
Published: Abingdon Taylor & Francis 03.04.2014
Taylor & Francis Ltd
Subjects:
Algorithms
Buses (vehicles)
Deviation
Distributed generation
Economics
Electricity distribution
multi-objective particle swarm optimization
Optimization
Power loss
power quality
Systems stability
voltage stability
ISSN:2168-1015, 2168-1023
Online Access:Get full text
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Summary:This paper attempts to investigate the multi-objective optimization (MOO) of accommodating distributed generation (DG) based on a modified multi-objective particle swarm optimization algorithm (MMPSO). In view of the significance of economic operation, power quality and system stability, MOO model with physical, technical, and operational constraints for optimally accommodating DG has been established to minimize the total active power loss, the total voltage deviation, and the voltage stability index of the system. Due to the incompatibility between the objectives and the need for flexibility of solutions, instead of converting the multiple objectives into a single one, a MMPSO algorithm has been presented and testified, and then applied to MOO of accommodating DG in an IEEE-33 bus system. Simulation results reveal the advantage of the proposed MOO model and the effectiveness of applying MMPSO to MOO of accommodating DG in the distribution system.
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ISSN:2168-1015
2168-1023
DOI:10.1080/21681015.2014.917127