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Stefan cel Mare
University of Suceava
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  4/2020 - 1
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Multi-objective Environmental-economic Load Dispatch Considering Generator Constraints and Wind Power Using Improved Multi-objective Particle Swarm Optimization

YALCINOZ, T. See more information about YALCINOZ, T. on SCOPUS See more information about YALCINOZ, T. on IEEExplore See more information about YALCINOZ, T. on Web of Science, RUDION, K. See more information about RUDION, K. on SCOPUS See more information about RUDION, K. on SCOPUS See more information about RUDION, K. on Web of Science
 
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Download PDF pdficon (1,254 KB) | Citation | Downloads: 494 | Views: 442

Author keywords
optimization, particle swarm optimization, power generation dispatch, power system economics, wind energy

References keywords
power(29), dispatch(29), economic(26), optimization(21), swarm(20), algorithm(13), energy(11), objective(9), multiobjective(8), multi(8)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2020-11-30
Volume 20, Issue 4, Year 2020, On page(s): 3 - 10
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2020.04001
Web of Science Accession Number: 000594393400001
SCOPUS ID: 85098149157

Abstract
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One of the vital optimization issues in energy systems is the problem of economic load dispatch (ED). On the other hand, solar, wind, and other renewable energies are important energy sources for reducing hazardous emissions. This paper suggests an improved multi-objective particle swarm optimization algorithm (IMOPSO) that uses a functional inertial weight and a functional constriction factor to solve the multi-objective environmental-economic load dispatch (MEED) problem. A mutation strategy is used in IMOPSO, and a mutation operator, which is implemented for each particle in the swarm, is used to find optimum Pareto fronts. In this paper, the proposed IMOPSO is applied to the MEED problem under consideration of emission pollution, wind energy, prohibited operating zone, ramp limits, valve point effects, and transmission losses. The proposed technique is tested on the IEEE 30-bus, the IEEE 118-bus test system, and the modified IEEE 118-bus test system with emission coefficients, ramp rate limits, wind power, and prohibited operating zone. The IMOPSOs are compared with the results of various multi-objective algorithms to solve the MEED problem. The simulation results indicate that the IMOPSO produces better results than the compared multi-objective optimization algorithms for various test systems.


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References Weight

Web of Science® Citations for all references: 40,219 TCR
SCOPUS® Citations for all references: 17,857 TCR

Web of Science® Average Citations per reference: 914 ACR
SCOPUS® Average Citations per reference: 406 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2021-03-01 12:27 in 282 seconds.




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