Improving energy autonomy of positive energy districts using multi-agent deep reinforcement learning

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Detalles Bibliográficos
Publicado en:	Scientific Reports (Nature Publisher Group) vol. 15, no. 1 (2025), p. 27798-27813
Autor principal:	Hribar, Jernej
Otros Autores:	Mohorčič, Mihael, Čampa, Andrej
Publicado:	Nature Publishing Group
Materias:	User behavior Deep learning Energy storage Optimization techniques Autonomy Electricity Heuristic Energy consumption Reinforcement Efficiency Vehicles Renewable energy Electric vehicles Renewable resources Cost reduction Energy management Solar energy Learning Linear programming Alternative energy sources Collaborative learning Households Self sufficiency Economic
Acceso en línea:	Citation/Abstract Full Text Full Text - PDF
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