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 |