Artículo
Evolutionary techniques applied to the optimal short-term scheduling of the electrical energy production
Autor/es | Troncoso Lora, Alicia
Riquelme Santos, José Cristóbal Aguilar Ruiz, Jesús Salvador Riquelme Santos, Jesús Manuel |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos Universidad de Sevilla. Departamento de Ingeniería Eléctrica |
Fecha de publicación | 2008 |
Fecha de depósito | 2016-07-07 |
Publicado en |
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Resumen | 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 ... 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. |
Identificador del proyecto | TIN2004-00159
ACPAI-2003/032 P05-TIC-00531 |
Cita | 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. |
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