Search Results for author: Nicolas Mauricio Cuadrado

Found 2 papers, 0 papers with code

FRESCO: Federated Reinforcement Energy System for Cooperative Optimization

no code implementations27 Mar 2024 Nicolas Mauricio Cuadrado, Roberto Alejandro Gutierrez, Martin Takáč

The rise in renewable energy is creating new dynamics in the energy grid that promise to create a cleaner and more participative energy grid, where technology plays a crucial part in making the required flexibility to achieve the vision of the next-generation grid.

Federated Learning

Generalized Policy Learning for Smart Grids: FL TRPO Approach

no code implementations27 Mar 2024 Yunxiang Li, Nicolas Mauricio Cuadrado, Samuel Horváth, Martin Takáč

The smart grid domain requires bolstering the capabilities of existing energy management systems; Federated Learning (FL) aligns with this goal as it demonstrates a remarkable ability to train models on heterogeneous datasets while maintaining data privacy, making it suitable for smart grid applications, which often involve disparate data distributions and interdependencies among features that hinder the suitability of linear models.

energy management Federated Learning +1

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