Suchergebnisse

In this article a new procedure to optimize the design of a Multiple Receivers Solar Power Tower system is presented. The proposed procedure allows to optimize the different receivers (height, aperture tilt angle, azimuth angle and aperture size) as well as the heliostat field layout, seeking to minimize the levelized cost of thermal energy. The optimization problem is high dimensional, with a black-box nonconvex objective function that is hard to compute. Our method is based on an alternating greedy-based heuristic method, already used by the authors to design a system with a single receiver, which simultaneously optimizes the receivers and the heliostat field. The proposed procedure allows one to determine the overall number of heliostats, their locations and the aiming region of each field. ; Abengoa Solar New Technologies ; Instituto de Matemáticas de la Universidad de Sevilla ; Ministerio de Ciencia e Innovación ; Ministerio de Economía y Competitividad ; Junta de Andalucía ; European Union

La comunicación aborda el diseño de un modelo estadístico de predicción dinámica de la sequía en Andalucía y su persistencia en un horizonte temporal de 12 meses a partir de los datos históricos (1950-2012) del Índice Estandarizado de Sequía Pluviométrica (IESP) en 243 observatorios de Andalucía. Se emplea un algoritmo kNN (k-Nearest Neighbors), que busca las situaciones pasadas más similares a la actual y predice el futuro promediando lo que ocurrió a continuación en dichas situaciones. Los resultados producen porcentajes de error muy reducidos. El modelo se está aplicando en rutina en el Sistema de Información de Climatología Ambiental (CLIMA) de la Consejería de Medio Ambiente de la Junta de Andalucía (http://www.climasig.es). ; This paper presents a statistical model for the dynamical prediction of drought in Andalusia. The drought index used is the IESP, which stands for Índice Estandarizado de Sequía Pluviométrica in Spanish, and has been applied to historical observation series (1950-2012) for 243 observatories. A kNN (k-Nearest Neighbors) algorithm is used to predict the future situations by averaging the past instances that are most similar to the current one. The application of a validation procedure on the available data shows that this model leads to very small percentages of failed predictions. The model is being applied by the Environment Ministry of the Andalusian Government to monitor drought in the region.