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| Título: | Learning the optimal joint operation of the energy systems of Uruguay, Brazil, Paraguay and Argentina |
| Autor: | Chaer, Ruben Ramírez Paulino, Ignacio Camacho, Vanina Caporale, Ximena Casaravilla, Gonzalo |
| Tipo: | Preprint |
| Palabras clave: | Wind energy generation, Training, Sea surface, Renewable energy sources, Neural networks, Hydroelectric power generation, Reinforcement learning, Approximate Stochastic Dynamic Programming, Machine Learning, Optimal operation of hydrothermal systems |
| Fecha de publicación: | 2022 |
| Resumen: | In the continuous fight against Bellman's Curse of Dimensionality, this work presents the first steps towards learning the Optimal Operation Policy of the electricity generation system of Uruguay, Brazil, Paraguay and Argentina with the infrastructures projected for the year 2030. The Operation Policy under consideration involves 76 state variables: one associated to the surface temperature anomaly of the Pacific Ocean in the N34 area, and 75 related to the hydroelectric reservoirs. The proposed methodology includes the design and training of two alternate neural network architectures combined with modern techniques devised for variance reduction and exploration, which were key to the success achieved |
| Descripción: | Presentado y publicado en 2022 IEEE PES Generation, Transmission and Distribution Conference and Exposition – Latin America (IEEE PES GTD Latin America), La Paz, Bolivia, 20-22 oct. 2022, pp. 1-6. |
| Financiadores: | Proyecto ANII-FSE_1_2017_1_144926 - "Planificación de inversiones con energías variables, restricciones de red y gestión de demanda" (2018-2020) Fondo Sectorial de Energía ANII |
| Citación: | Chaer, R., Ramírez Paulino, I., Camacho, V. y otros. Learning the optimal joint operation of the energy systems of Uruguay, Brazil, Paraguay and Argentina [Preprint]. Publicado en: 2022 IEEE PES Generation, Transmission and Distribution Conference and Exposition – Latin America (IEEE PES GTD Latin America), La Paz, Bolivia, 20-22 oct 2022, 6 p. DOI 10.1109/IEEEPESGTDLatinAmeri53482.2022.10037786 |
| Cobertura geográfica: | Argentina Brasil Paraguay Uruguay |
| Departamento académico: | Potencia Potencia Procesamiento de Señales Procesamiento de Señales |
| Grupo de investigación: | Energía Eléctrica Tratamiento de Imágenes Energía Eléctrica Tratamiento de Imágenes |
| Aparece en las colecciones: | Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica |
Ficheros en este ítem:
| Fichero | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| CRCCC22.pdf | Preprint | 240 kB | Adobe PDF | Visualizar/Abrir |
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