dc.creator | Zuluaga, Jorge | |
dc.creator | Murillo Sánchez, Carlos E. | |
dc.creator | Moreno Chuquen, Ricardo | |
dc.creator | Chamorro, Harold R. | |
dc.creator | Sood, Vijay K. | |
dc.date.accessioned | 2023-05-16T19:50:24Z | |
dc.date.accessioned | 2023-06-06T15:26:41Z | |
dc.date.available | 2023-05-16T19:50:24Z | |
dc.date.available | 2023-06-06T15:26:41Z | |
dc.date.created | 2023-05-16T19:50:24Z | |
dc.date.issued | 2022 | |
dc.identifier | 17521424 | |
dc.identifier | https://hdl.handle.net/10614/14748 | |
dc.identifier | 25168401 | |
dc.identifier | Universidad Autónoma de Occidente | |
dc.identifier | Repositorio Educativo Digital UAO | |
dc.identifier | https://red.uao.edu.co/ | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/6649739 | |
dc.description.abstract | The variability and uncertainty of renewable resources impose new challenges in the
operational planning related to the unit commitment of generation units. The development
of day‐ahead multi‐period optimal power flow, under integration of wind power, requires
modelling of multiple scenarios in order to ensure an optimal power flow minimising the
generation cost. A progressive hedging approach has been proposed and developed to
solve efficiently the unit commitment problem as a two‐stage stochastic programming
problem to update each stage in parallel. The performance of progressive hedging is
compared with a standard mixed‐integer linear programming problem. The results indicate
that the computation time is 50 times faster than standard mixed‐integer linear program ming. The test case system is based on a reduced version of the interconnected Colombian
system. The comparative results indicate an important reduction in computational time | |
dc.language | eng | |
dc.publisher | Institution of Engineering and Technology (IET) | |
dc.publisher | Tianjin University | |
dc.relation | 9 | |
dc.relation | 1 | |
dc.relation | Zuluaga, J., Murillo Sánchez, C.E., Moreno Chuquen, R., Chamorro, H.R., Sood, V.K. (2022). Day-ahead unit commitment for hydro-thermal coordination with high participation of wind power. IET Renewable Power Generation, pp. 1-9 | |
dc.relation | IET Energy Systems Integration | |
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dc.relation | Haugen, K.K., Løkketangen, A., Woodruff, D.L.: Progressive hedging as a meta‐heuristic applied to stochastic lot‐sizing. Eur. J. Oper. Res. 132(1), 116–122 (2001). https://doi.org/10.1016/s0377-2217(00)00116-8 | |
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dc.relation | Zimmerman, R.D., Murillo‐Sánchez, C.E.: Matpower (version 7.1). (2020)[Online]. https://matpower.org | |
dc.rights | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.rights | Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) | |
dc.rights | Derechos reservados - Institution of Engineering and Technology (IET), 2022 | |
dc.title | Day-ahead unit commitment for hydro-thermal coordination with high participation of wind power | |
dc.type | Artículo de revista | |