Multi objective multi area hydrothermal environmental economic dispatch using bat algorithm

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dc.contributor.author Olang’o, Seline. A.
dc.contributor.author Musau, Peter M.
dc.contributor.author Odero, Nicodemus.A.
dc.date.accessioned 2022-11-17T07:26:24Z
dc.date.available 2022-11-17T07:26:24Z
dc.date.issued 2018
dc.identifier.citation 2018 International Conference on Power System Technology (POWERCON) en_US
dc.identifier.isbn 978-1-5386-6461-2
dc.identifier.uri https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8601543
dc.identifier.uri http://repository.seku.ac.ke/handle/123456789/6961
dc.description DOI: 10.1109/POWERCON.2018.8601543 en_US
dc.description.abstract This paper presents a Multi Objective, Multi Area Hydrothermal Environmental Economic Dispatch (MOMAHEED) problem which determines the optimal generating level of all the hydro and thermal generating units to adequately supply the demand, such that the total fuel cost of thermal plants in all areas and emissions are simultaneously curtailed while satisfying all physical and operational constraints. MOMAHEED is solved using Bat Algorithm (BA) which is inspired by echolocation behavior of micro bats. The multi objective function is converted to a single objective one using weighted sum method and cardinal priority ranking used to select the optimal solutions. The algorithm is tested on a four-area system considering three test cases and results in lower fuel costs as compared to Particle Swarm optimization (PSO). en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Bat Algorithm (BA) en_US
dc.subject Multi Objective Multi Area Hydrothermal Environmental Economic Dispatch (MOMAHEED), en_US
dc.subject Particle Swarm Optimization (PSO) en_US
dc.title Multi objective multi area hydrothermal environmental economic dispatch using bat algorithm en_US
dc.type Article en_US


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