Please use this identifier to cite or link to this item: http://hdl.handle.net/10266/4482
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dc.contributor.supervisorNarang, Nitin-
dc.contributor.supervisorKaur, Manbir-
dc.contributor.authorKumar, Nitish-
dc.date.accessioned2017-07-21T08:30:55Z-
dc.date.available2017-07-21T08:30:55Z-
dc.date.issued2017-07-21-
dc.identifier.urihttp://hdl.handle.net/10266/4482-
dc.descriptionMaster of Engineering-Power Systemsen_US
dc.description.abstractAn integration of civilized swarm optimization (CSO) and shuffle frog leap algorithm (SFLA) is presented to solve practical economic load dispatch (ELD) problem. In the formulation of practical ELD problem, multiple fuel, valve point effect, transmission losses, ramp rate limits and prohibited operating zone are also considered. In CSO, societies are formed by the group of individual with better performing individual of each society consider as society leaders. The best performing society leader consider as civilization leader. In this proposed integrated search technique, initially the particles are updated by applying CSO algorithm thereafter SFLA update the worst particles and make the worst particles to better particles. This integrated search technique provides the fast convergence speed and best global solution. In this dissertation work, multi- fuel options have been considered due to depletion and ever increase in cost of quality. Due to these problems, multi- fuel options provide to the power plant and effect of the multi-fuel should be considered in ELD problem. To evaluate the efficiency and feasibility of proposed technique, it is applied to small, medium and large test systems. The better results are obtained by the proposed technique as compared to other optimization technique described in literature.en_US
dc.language.isoenen_US
dc.subjectEconomic load dispatchen_US
dc.subjectCivilized swarm optimizationen_US
dc.subjectshuffle algorithmen_US
dc.titleEconomic Dispatch Problem with Multiple Fuel by using Integrated Search Techniqueen_US
dc.typeThesisen_US
Appears in Collections:Masters Theses@EIED

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