6 papers
Knowledge- and Data-driven Services for Energy Systems using Graph Neural Networks
Francesco Fusco, Bradley Eck, Robert Gormally +2
The transition away from carbon-based energy sources poses several challenges for the operation of electricity distribution systems. Increasing shares of distributed energy resourc…
Scalable Deployment of AI Time-series Models for IoT
Bradley Eck, Francesco Fusco, Robert Gormally +2
IBM Research Castor, a cloud-native system for managing and deploying large numbers of AI time-series models in IoT applications, is described. Modelling code templates, in Python…
AI Modelling and Time-series Forecasting Systems for Trading Energy Flexibility in Distribution Grids
Bradley Eck, Francesco Fusco, Robert Gormally +2
We demonstrate progress on the deployment of two sets of technologies to support distribution grid operators integrating high shares of renewable energy sources, based on a market…
Probabilistic Graphs for Sensor Data-driven Modelling of Power Systems at Scale
Francesco Fusco
The growing complexity of the power grid, driven by increasing share of distributed energy resources and by massive deployment of intelligent internet-connected devices, requires n…
Castor: Contextual IoT Time Series Data and Model Management at Scale
Bei Chen, Bradley Eck, Francesco Fusco +4
We demonstrate Castor, a cloud-based system for contextual IoT time series data and model management at scale. Castor is designed to assist Data Scientists in (a) exploring and ret…
Learning Correlation Space for Time Series
Han Qiu, Hoang Thanh Lam, Francesco Fusco +1
We propose an approximation algorithm for efficient correlation search in time series data. In our method, we use Fourier transform and neural network to embed time series into a l…