Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019).

Advances in energy generation processes as well as in customers' needs and expectations lead to fast changesx000D
and modifications of a power grid. Variability and uncertainties in a power distribution grid are observed on thex000D
generation side due to growing involvement of clean energy sources and potential contributions of small,x000D
independent energy producers; and on the load side due to changes in profiles of energy consumption, nature ofx000D
devices connected to a grid, and increased presence of energy storages. Improvements in monitoring and datax000D
collection practices provide opportunities to more comprehensive modelling and managing operations of a grid.x000D
A power grid can be enhanced and become more efficient by integrating techniques of artificial intelligence inx000D
analysis and optimization of its operations. Advanced data analysis methods should be able to address a servicex000D
quality degradation due to outages, weather patterns and asset related performance.x000D
The proposed project aims at applying Machine Learning/Data Mining and Computational Intelligencex000D
methods for analysis of power distribution system data, and proposing a methodology for processing this datax000D
in order to foresee and identify potential problems in power distribution system leading to power outages.x000D
It is expected that developed methodology will lead to faster analysis time and discovery of new insightsx000D
aiming at augmenting and predicting reliability of a power distribution grid.