Please use this identifier to cite or link to this item: http://dspace2020.uniten.edu.my:8080/handle/123456789/8312
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dc.contributor.authorRazali, N.M.M.
dc.contributor.authorTeh, Y.Y.
dc.date.accessioned2018-02-15T02:45:53Z-
dc.date.available2018-02-15T02:45:53Z-
dc.date.issued2013
dc.identifier.urihttp://dspace.uniten.edu.my/jspui/handle/123456789/8312-
dc.description.abstractThe main objective to solve an emission constrained economic dispatch (ECED) problem is to simultaneously minimize the total cost of generation and the total emission level; whereby the latter is equated in terms of as emission cost. The conventional method (CM) by using the Lagrange Multiplier has some limitations such as lack of flexibility and accuracy due to the need of simplification of the problem before solving it and the solution generated may not be the best since it may be limited to local minima instead of global minima. The paper presents the solutions for ECED problem by using two stochastic optimisers; the Genetic Algorithm (GA) and Particle Swarm Optimizer (PSO). The results demonstrate the efficiency and effectiveness of using GA and PSO to solve the ECED problem compared to CM.
dc.titleEmission constrained economic dispatch by using stochastic optimisers
item.fulltextNo Fulltext-
item.grantfulltextnone-
Appears in Collections:COE Scholarly Publication
COGS Scholarly Publication
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