Learning the optimal joint operation of the energy systems of Uruguay, Brazil, Paraguay and Argentina
- Autor(es):
- Chaer, Ruben ; Ramírez Paulino, Ignacio ; Camacho, Vanina ; Caporale, Ximena ; Casaravilla, Gonzalo
- Tipo:
- Preprint
- Versión:
- Enviado
- 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
- 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
- Año:
- 2022
- Idioma:
- Inglés
- Temas:
- 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
- Institución:
- Universidad de la República
- Repositorio:
- COLIBRI
- Nivel de acceso:
- Acceso abierto
