A differential evolution based memetic algorithm for workload optimization in power generation plants

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86092976" target="_blank" >RIV/61989100:27240/11:86092976 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/HIS.2011.6122117" target="_blank" >http://dx.doi.org/10.1109/HIS.2011.6122117</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/HIS.2011.6122117" target="_blank" >10.1109/HIS.2011.6122117</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A differential evolution based memetic algorithm for workload optimization in power generation plants

Popis výsledku v původním jazyce

Work load optimization in power generation plants is of practical importance in carbon constrained power industry. The main objective of the coal-fired power generation workload optimization is to minimize fuel consumption while maintaining the desired output and to maintain NO x emission within the environmental license limit. In this article, we represent an efficient Memetic Algorithm (MA) with a constraint handling method for the power generation loading optimization. This MA is developed by combining a competitive variant of Deferential Evolution (DE) and Simplex method. The proposed approach incorporates the constraint handling method to modify the selection rule which guides the search process in better direction. The simulation results based ona coal-fired power plant clearly indicate that our proposed method is very effective and it shows great computational efficiency in power generation workload optimization. 2011 IEEE.

Název v anglickém jazyce

A differential evolution based memetic algorithm for workload optimization in power generation plants

Popis výsledku anglicky

Work load optimization in power generation plants is of practical importance in carbon constrained power industry. The main objective of the coal-fired power generation workload optimization is to minimize fuel consumption while maintaining the desired output and to maintain NO x emission within the environmental license limit. In this article, we represent an efficient Memetic Algorithm (MA) with a constraint handling method for the power generation loading optimization. This MA is developed by combining a competitive variant of Deferential Evolution (DE) and Simplex method. The proposed approach incorporates the constraint handling method to modify the selection rule which guides the search process in better direction. The simulation results based ona coal-fired power plant clearly indicate that our proposed method is very effective and it shows great computational efficiency in power generation workload optimization. 2011 IEEE.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011

ISBN

978-1-4577-2150-2

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

271-276

Název nakladatele

IEEE

Místo vydání

New York

Místo konání akce

Malacca

Datum konání akce

5. 12. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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