We consider Data Centers (DCs) as flexible loads that can alter their power consumption to a .....
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- Adaptive federated learning framework for predicting EV charging stations occupancy
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- Forecasting the occupancy of electric vehicle (EV) charging stations is crucial for addressing key c .....
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Conference papers
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- COGNAC: Cooperative Graph-based Networked Agent Challenges for Multi-Agent Reinforcement Learning
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- Many controlled complex systems have an inherent network structure, such as power grids, traffic lig .....
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- Benchmarking Catastrophic Forgetting Mitigation Methods in Federated Time Series Forecasting
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- Catastrophic forgetting (CF) poses a persistent challenge in continual learning (CL), especially wit .....
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- Moment Constrained Optimal Transport for Energy Demand Management of Heterogeneous Loads
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- This paper addresses the problem of coordinating a large population of heterogeneous electrical load .....
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- Mean-Field Control of Heterogeneous Piecewise Deterministic Markov Processes under Grid Constraints
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- This paper investigates mean-field control problems for large populations of agents modeled by piece .....
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- Federated Learning with Mixed Encryption for Distributed Energy Resources: Forecasting Electricity Charging Demand at Multiple Electrical Vehicle Charging Stations
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- Sharing information or data between actors is crucial for forecasting distributed energy resources. .....
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- Unlock Data Sharing in Wind Power Forecasting through Privacy-preserving Federated-Learning: Benchmarking of Mixed and Fully Encrypted Frameworks
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- Federated learning is a technology enabling the privacy-preserving sharing of spatio-temporal data. .....
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- Assessment of Kolmogorov-Arnold Networks for Spatio-Temporal Renewable Energy Forecasting
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- Multi-Market Bidding of Virtual Power Plants with Machine Learning-Assisted Asynchronous Distributed Optimization
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- Virtual power plants aggregate distributed energy resources, such as renewables, flexible loads, and .....
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- Moment Constrained Optimal Transport for Thermostatically Controlled Loads
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- Controlling large populations of thermostatically controlled loads (TCLs), such as water heaters, po .....
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- Multi-agent reinforcement learning for locally observable cooperative systems with acyclic dependence structure
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- Single-agent reinforcement learning algorithms can be directly applied to multi-agent systems in an .....
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2024
Journal articles
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- Multivariate Federated Tree-based Forecasting Combining Resilience and Privacy: Application to Distributed Energy Resources
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- Using spatiotemporal data can increase forecasting accuracy for distributed energy resources such as .....
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- Towards fine tuning wake steering policies in the field: an imitation-based approach
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- Yaw misalignment strategies can increase the power output of wind farms by mitigating wake effects, .....
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Conference papers
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- WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control
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- The wind farm control problem is challenging, since conventional model-based control strategies requ .....
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- Extending Privacy-preserving Regression Trees to a Value-oriented Forecasting Approach for Trading DER Resources
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- In the state of the art, it has been shown that in several applications like spatiotemporal forecast .....
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- Multivariate Federated Tree-based Forecasting Combining Resilience and Privacy: Application to Distributed Energy Resources
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- Using spatiotemporal data can increase forecasting accuracy for distributed energy resources such as .....
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2023
Journal articles
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- Kullback–Leibler-Quadratic Optimal Control
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- This paper presents approaches to mean-field control, motivated by distributed control of multiagent .....
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Reports
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- Mapping of distributed AI services on IoT fog architecture under QoS constraints
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- Rapport de Master 2
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