dc.creator | Troncoso Lora, Alicia | es |
dc.creator | Riquelme Santos, José Cristóbal | es |
dc.creator | Aguilar Ruiz, Jesús Salvador | es |
dc.creator | Riquelme Santos, Jesús Manuel | es |
dc.date.accessioned | 2016-07-07T10:14:07Z | |
dc.date.available | 2016-07-07T10:14:07Z | |
dc.date.issued | 2008 | |
dc.identifier.citation | Troncoso, A., Riquelme Santos, J.C., Aguilar Ruiz, J.S. y Riquelme Santos, J.M. (2008). Evolutionary techniques applied to the optimal short-term scheduling of the electrical energy production. European Journal of Operational Research, 185 (3), 1114-1127. | |
dc.identifier.issn | 0377-221 | es |
dc.identifier.uri | http://hdl.handle.net/11441/43323 | |
dc.description.abstract | This paper presents an evolutionary technique applied to the optimal short-term scheduling (24 h) of the electric energy
production. The equations that define the problem lead to a non-convex non-linear programming problem with a high
number of continuous and discrete variables. Consequently, the resolution of the problem based on combinatorial methods
is rather hard. The required heuristics, introduced to assure the feasibility of the constraints, are analyzed, along with a
brief description of the proposed genetic algorithm (GA). The GA is used to compute the optimal on/off status of thermal
units and the fitness function is obtained by solving a quadratic programming problem by means of a standard non-linear
Interior Point (IP) method. The results from real-world cases based on the Spanish power system are reported, which show
the good performance of the proposed algorithm, taking into account the complexity and dimensionality of the problem.
Finally, an IP algorithm is adapted to deal with discrete variables that appear in this problem and the obtained results are
compared with that of the proposed GA. | es |
dc.description.sponsorship | Ministerio de Ciencia y Tecnología TIN2004-00159 | es |
dc.description.sponsorship | Junta de Andalucia ACPAI-2003/032 | es |
dc.description.sponsorship | Junta de Andalucia P05-TIC-00531 | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.ispartof | European Journal of Operational Research, 185 (3), 1114-1127. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | genetic algorithms | es |
dc.subject | Scheduling | es |
dc.subject | Optimization | es |
dc.subject | Feasibility | es |
dc.subject | Interior point algorithms | es |
dc.title | Evolutionary techniques applied to the optimal short-term scheduling of the electrical energy production | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería Eléctrica | es |
dc.relation.projectID | TIN2004-00159 | es |
dc.relation.projectID | ACPAI-2003/032 | es |
dc.relation.projectID | P05-TIC-00531 | es |
dc.relation.publisherversion | http://dx.doi.org/10.1016/j.ejor.2006.06.044 | |
dc.identifier.doi | 10.1016/j.ejor.2006.06.044 | es |
idus.format.extent | 14 | es |
dc.journaltitle | European Journal of Operational Research | es |
dc.publication.volumen | 185 | es |
dc.publication.issue | 3 | es |
dc.publication.initialPage | 1114 | es |
dc.publication.endPage | 1127 | es |
dc.identifier.idus | https://idus.us.es/xmlui/handle/11441/43323 | |