Machine Learning Applied to the Operation of Fully Renewable Energy Systems

This work presents a novel learning algorithm for the operation policy of power systems trying to minimize the cost of fulfilling the energy demand. The algorithm improves upon the classical reinforcement learning methods by controlling the sampling variance in the estimation of the future cost spat...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	2023 IEEE PES GTD International Conference and Exposition (GTD) S. 139 - 143
Hauptverfasser:	Chaer, Ruben, Ramirez, Ignacio, Casaravilla, Gonzalo
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.05.2023
Schlagworte:	Approximate Stochastic Dynamic Programming Costs Heuristic algorithms Lakes Power system dynamics Reinforcement learning Reinforcement Machine Learning Renewable Energies Solar energy Stochastic processes
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!