Reference number : GC-2017-Q2-00329, amendment number : , agreement type : G, recipient legal name : Reformat, Marek (University of Alberta), recipient country : CA, recipient province : nan, recipient city : Alberta, recipient postal code : nan, program name english : Engage Grants for Universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : Advances in energy generation processes as well as in customers' needs and expectations lead to fast changes_x000D_
and modifications of a power grid. Variability and uncertainties in a power distribution grid are observed on the_x000D_
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 of_x000D_
devices connected to a grid, and increased presence of energy storages. Improvements in monitoring and data_x000D_
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 in_x000D_
analysis and optimization of its operations. Advanced data analysis methods should be able to address a service_x000D_
quality degradation due to outages, weather patterns and asset related performance._x000D_
The proposed project aims at applying Machine Learning/Data Mining and Computational Intelligence_x000D_
methods for analysis of power distribution system data, and proposing a methodology for processing this data_x000D_
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 insights_x000D_
aiming at augmenting and predicting reliability of a power distribution grid., program purpose french : Advances in energy generation processes as well as in customers' needs and expectations lead to fast changes_x000D_
and modifications of a power grid. Variability and uncertainties in a power distribution grid are observed on the_x000D_
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 of_x000D_
devices connected to a grid, and increased presence of energy storages. Improvements in monitoring and data_x000D_
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 in_x000D_
analysis and optimization of its operations. Advanced data analysis methods should be able to address a service_x000D_
quality degradation due to outages, weather patterns and asset related performance._x000D_
The proposed project aims at applying Machine Learning/Data Mining and Computational Intelligence_x000D_
methods for analysis of power distribution system data, and proposing a methodology for processing this data_x000D_
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 insights_x000D_
aiming at augmenting and predicting reliability of a power distribution grid., agreement title english : Computational intelligence based analysis of power distribution data, agreement title french : Computational intelligence based analysis of power distribution data, agreement number : EGP, agreement value : 25000.0, agreement start date : 2017-08-23, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada