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Power generation loading optimization using a multi-objective constraint-handling method via PSO algorithm

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conference contribution
posted on 06.12.2017, 00:00 by Xinghuo Yu, Dujuan Li
Power generation loading optimization problem will be of practical importance in the coming carbon constrained power industry. A major objective for the coal-fired power generation loading optimization is to minimize fuel consumption to achieve output demand and to maintain NOx emissions within the environmental license limit. This paper presents a multi-objective constraint-handling method incorporating the Particle Swarm Optimization (PSO) algorithm for the power generation loading optimization application. The proposed approach adopts the concept of Pare to dominance from multi-objective optimization, and uses several selection rules to determine particles’ behaviors to guide the search direction. The simulation results of the power generation loading optimization based on a coal-fired power plant demonstrates the capability, effectiveness and efficiency of using a multi-objective constraint-handling method with PSO algorithm in solving significant industrial problems.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Start Page

1632

End Page

1637

Number of Pages

6

Start Date

01/01/2008

ISSN

1935-4576

ISBN-13

9781424421718

Location

Daejeon, Korea

Publisher

IEEE

Place of Publication

USA

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Faculty of Business and Informatics; RMIT University; TBA Research Institute;

Era Eligible

Yes

Name of Conference

IEEE International Conference on Industrial Informatics

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