Combined Heat and Power Economic Dispatch Using Civilized Swarm Optimization

dc.contributor.authorSharma, Era
dc.contributor.supervisorNarang, Nitin
dc.date.accessioned2014-08-14T07:12:17Z
dc.date.available2014-08-14T07:12:17Z
dc.date.issued2014-08-14T07:12:17Z
dc.descriptionME, EIEDen
dc.description.abstractA Civilized swarm optimization (CSO) technique, having attributes of particle swarm optimization (PSO) and society civilization algorithm (SCA) is presented in this dissertation work to solve combined heat and power economic dispatch (CHPED) problem taking into account the operational constraints of power system. CSO is a new integration based optimization technology in which the mutually interacting societies of SCA forming a civilization have been embedded in the population based self adaptive searching strategy of PSO. It is applied on CHPED problem to obtain optimum solution within feasible operating limits, satisfying the load demand at the same time. The main difficulty while dealing with a CHPED system is of multiple constraint satisfaction which is handled by following Euclidean distance approach in this work. In order to determine the efficacy of the proposed CSO based approach, it is applied on three standard test problems and the results obtained shows that the proposed CSO technique minimizes the cost at considerably smaller level of violation of constraints as compared to those obtained using other existing methods. The optimization strategy proposed in this dissertation work is easy to implement and it outperforms all the previous approaches in a respect of constraint satisfaction with cost minimizationen
dc.format.extent1489677 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10266/2905
dc.language.isoenen
dc.subjectSociety Civilization algorithmen
dc.subjectParticle Swarm Optimizationen
dc.subjectSwarm Society leaderen
dc.subjectCivilization leaderen
dc.subjectCombined heat and power economic dispatchen
dc.titleCombined Heat and Power Economic Dispatch Using Civilized Swarm Optimizationen
dc.typeThesisen

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