Summary of Generalizing in Net-zero Microgrids: a Study with Federated Ppo and Trpo, by Nicolas M Cuadrado Avila et al.
Generalizing in Net-Zero Microgrids: A Study with Federated PPO and TRPO
by Nicolas M Cuadrado Avila, Samuel Horváth, Martin Takáč
First submitted to arxiv on: 30 Dec 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a collaborative and privacy-preserving framework called FedTRPO to optimize energy management in microgrids. It integrates Federated Learning (FL) with Trust Region Policy Optimization (TRPO) to manage distributed energy resources (DERs) efficiently. The authors simulate designed net-zero energy scenarios for microgrids composed of multiple buildings using a customized version of the CityLearn environment and synthetically generated data. Experimental results show that FedTRPO is comparable to state-of-the-art federated RL methodologies without hyperparameter tuning. This framework highlights the feasibility of collaborative learning for achieving optimal control policies in energy systems, advancing the goals of sustainable and efficient smart grids. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps make buildings more energy-efficient by sharing information between them. It creates a special algorithm called FedTRPO that combines two existing methods: Federated Learning (FL) and Trust Region Policy Optimization (TRPO). This allows different buildings to work together while keeping their own energy usage private. The authors tested this idea using a simulated city environment and found it worked just as well as more advanced approaches without needing special adjustments. This could help make smart grids more sustainable and efficient. |
Keywords
» Artificial intelligence » Federated learning » Hyperparameter » Optimization
