Publications
Find all the scientific publications produced by HEDGE-IoT partners, presenting the latest scientific findings of the project.
Edge Offloading in Smart Grid
Deep Q-Learning-Based Smart Scheduling of EVs for Demand Response in Smart Grids
Whale Optimization for Cloud–Edge-Offloading Decision-Making for Smart Grid Services
Office Graph
Making the Dataspace Protocol an international standard
Market-based Congestion Management in Power Systems : With a focus on distribution grids
Databases in Edge and Fog Environments: A Survey
Market integration and TSO-DSO coordination for viable market-based congestion management in power systems
Knowledge Graph Model for Computing Continuum over Smart Grid
EVs Coordination to Maximize the Usage of Local Renewable Energy
Representation Learning on IoT Knowledge Graphs
Semantic Technologies for Flexible Energy Grids: the Arnhems Buiten demonstrator
Congestion management in distribution grids using local flexibility markets: Investigating influential factors
Reinforcement-Learning-Based Edge Offloading Orchestration in Computing Continuum
Heuristic based federated learning with adaptive hyperparameter tuning for households energy prediction
Data Spaces Standardization Landscape – Europe and International
Predictive and real-time congestion management to enhance grid hosting capacity
Analysis and comparison of congestion management solutions of distribution grids
Time and Frequency Domain-based Anomaly Detection in Smart Meter Data for Distribution Network Studies
The Effect of High-Resolution Wind Speed and Wind Direction Measurements on Dynamic Thermal Rating
Data-driven emission analysis of on-board chargers and large AC charging sites of electric vehicles
AI-Based Energy Forecasting at Different Distribution Grid Levels to Support Baseline Definition and DSO Participation in LFMs
Oracle MILP and Reinforcement Learning Bidding for PV-Battery Dispatch in an Incentive-Driven Local Flexibility Market
Decentralized IoT Data Marketplaces: Enabling Peer-to-Peer Exchange with Edge Computing
Lightweight Embedded IoT Gateway for Smart Homes Based on an ESP32 Microcontroller
Denoising Autoencoder for Appliance-Specific Energy Disaggregation in Residential Settings
Non-Intrusive Load Monitoring Using Cluster-Optimized Denoising Autoencoders