Privacy-Preserving Probabilistic Voltage Forecasting in Local Energy Communities

Electricity Consumer Characteristics Identification: A Federated Learning Approach

(2021) Yi Wang et al.   IEEE Transactions on Smart Grid

Privacy-Preserving Distributed Learning for Renewable Energy Forecasting

(2021) Carla Goncalves et al.   IEEE Transactions on Sustainable Energy

Short-term nodal voltage forecasting for power distribution grids: An ensemble learning approach

(2021) Yi Wang et al.   APPLIED ENERGY

SecureBoost: A Lossless Federated Learning Framework

(2021) Kewei Cheng et al.   IEEE INTELLIGENT SYSTEMS

Enabling Homomorphically Encrypted Inference for Large DNN Models

(2021) Guillermo Lloret-Talavera et al.   IEEE TRANSACTIONS ON COMPUTERS

Interpretable Probabilistic Forecasting of Imbalances in Renewable-Dominated Electricity Systems

(2021) Jean-Francois Toubeau et al.   IEEE Transactions on Sustainable Energy

Integrating P2P Energy Trading With Probabilistic Distribution Locational Marginal Pricing

(2020) Thomas Morstyn et al.   IEEE Transactions on Smart Grid

Machine Learning Techniques for Improving Self-Consumption in Renewable Energy Communities

(2020) Zacharie De Grève et al.   Energies

Recalibration of recurrent neural networks for short-term wind power forecasting

(2020) Jean-François Toubeau et al.   ELECTRIC POWER SYSTEMS RESEARCH

A New Cooperative Framework for a Fair and Cost-Optimal Allocation of Resources Within a Low Voltage Electricity Community

(2020) Martin Hupez et al.   IEEE Transactions on Smart Grid

Very-Short-Term Probabilistic Forecasting for a Risk-Aware Participation in the Single Price Imbalance Settlement

(2019) Jeremie Bottieau et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Privacy-preserving big data analytics a comprehensive survey

(2019) Hong-Yen Tran et al.   JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING

Linear Single- and Three-Phase Voltage Forecasting and Bayesian State Estimation With Limited Sensing

(2019) Roel Dobbe et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

A Distributed Approach for Wind Power Probabilistic Forecasting Considering Spatio-Temporal Correlation Without Direct Access to Off-Site Information

(2018) Yao Zhang et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Energy Collectives: a Community and Fairness based Approach to Future Electricity Markets

(2018) Fabio Moret et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Robust Forecasting Aided Power System State Estimation Considering State Correlations

(2018) Junbo Zhao et al.   IEEE Transactions on Smart Grid

Deep Learning-based Multivariate Probabilistic Forecasting for Short-Term Scheduling in Power Markets

(2018) Jean-Francois Toubeau et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

The Composition Theorem for Differential Privacy

(2017) Peter Kairouz et al.   IEEE TRANSACTIONS ON INFORMATION THEORY

A Short-Term Nodal Voltage Phasor Forecasting Method Using Temporal and Spatial Correlation

(2016) Mohammad Hassanzadeh et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

State Forecasting and Operational Planning for Distribution Network Energy Management Systems

(2016) Barry Patrick Hayes et al.   IEEE Transactions on Smart Grid

A new approach based on the experimental design method for the improvement of the operational efficiency in Medium Voltage distribution networks

(2015) Jean-François Toubeau et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

A Bayesian-Based Approach for a Short-Term Steady-State Forecast of a Smart Grid

(2013) Antonio Bracale et al.   IEEE Transactions on Smart Grid

What Can We Learn Privately?

(2011) Shiva Prasad Kasiviswanathan et al.   SIAM JOURNAL ON COMPUTING