NDLI: Improved PSO for the best compromise of power systems

Content Provider	IEEE Xplore Digital Library
Author	Chao-Lung Chiang
Copyright Year	2012
Description	Author affiliation: Dept. of Electronic Engineering, Nan Kai University of Technology, Taiwan (Chao-Lung Chiang)
Abstract	This paper develops an improved particle swarm optimization (IPSO) based multi-objective approach for the optimal economic emission dispatch (EED) of the hydrothermal power system (HPS), considering non-smooth fuel cost and emission level functions. The IPSO equipped with an accelerated operation and a migration operation can efficiently search and actively explore solutions. The multiplier updating (MU) is introduced to handle the equality and inequality constraints of the HPS, and the e-constraint technique is employed to manage the multi-objective problem. To show the advantages of the proposed algorithm, one example addressing the best compromise is applied to test EED problem of the HPS. The proposed approach integrates the IPSO, the MU and the e-constraint technique, revealing that the proposed approach has the following merits - 1) ease of implementation; 2) applicability to non-smooth fuel cost and emission level functions; 3) better effectiveness than the previous method; 4) better efficiency than Particle Swarm Optimization with the MU (PSO-MU), and 5) the requirement for only a small population in applying the optimal EED problem of the HPS.
Starting Page	1191
Ending Page	1196
File Size	295666
Page Count	6
File Format	PDF
ISBN	9781457721304
ISSN	21579563
e-ISBN	9781457721335
DOI	10.1109/ICNC.2012.6234657
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Economics Availability economic emission dispatch Nickel Generators Power systems particle swarm optimization Fuels Optimization
Content Type	Text
Resource Type	Article

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