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Stochastic PSO-based heat and power dispatch under environmental constraints incorporating CHP and wind power units

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dc.contributor.author Piperagkas, GS en
dc.contributor.author Anastasiadis, AG en
dc.contributor.author Hatziargyriou, ND en
dc.date.accessioned 2014-03-01T01:37:08Z
dc.date.available 2014-03-01T01:37:08Z
dc.date.issued 2011 en
dc.identifier.issn 0378-7796 en
dc.identifier.uri http://hdl.handle.net/123456789/21457
dc.subject Cogeneration en
dc.subject Economic dispatch en
dc.subject Environmental dispatch en
dc.subject Multi-objective particle swarm optimization en
dc.subject Wind power estimation en
dc.subject.classification Engineering, Electrical & Electronic en
dc.subject.other Cogeneration en
dc.subject.other Economic dispatch en
dc.subject.other Environmental dispatch en
dc.subject.other Multi objective particle swarm optimization en
dc.subject.other Wind power estimation en
dc.subject.other Cogeneration plants en
dc.subject.other Computer simulation en
dc.subject.other Constraint theory en
dc.subject.other Emission control en
dc.subject.other Particle swarm optimization (PSO) en
dc.subject.other Random variables en
dc.subject.other Scheduling en
dc.subject.other Stochastic models en
dc.subject.other Stochastic systems en
dc.subject.other Wind power en
dc.subject.other Multiobjective optimization en
dc.title Stochastic PSO-based heat and power dispatch under environmental constraints incorporating CHP and wind power units en
heal.type journalArticle en
heal.identifier.primary 10.1016/j.epsr.2010.08.009 en
heal.identifier.secondary http://dx.doi.org/10.1016/j.epsr.2010.08.009 en
heal.language English en
heal.publicationDate 2011 en
heal.abstract In this paper an extended stochastic multi-objective model for economic dispatch (ED) is proposed, that incorporates in the optimization process heat and power from CHP units and expected wind power. Stochastic restrictions for the CO2, SO2 and NO emissions are used as inequality constraints. The ED problem is solved using a multi-objective particle swarm optimization technique. The available wind power is estimated from a transformation of the wind speed considered as a random variable to wind power. Simulations are performed on the modified IEEE 30 bus network with 2 cogeneration units and actual wind data. Results concerning minimum cost and emissions reduction options are finally drawn. (c) 2010 Elsevier B.V. All rights reserved. en
heal.publisher ELSEVIER SCIENCE SA en
heal.journalName Electric Power Systems Research en
dc.identifier.doi 10.1016/j.epsr.2010.08.009 en
dc.identifier.isi ISI:000284523800026 en
dc.identifier.volume 81 en
dc.identifier.issue 1 en
dc.identifier.spage 209 en
dc.identifier.epage 218 en


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