Computational intelligence based analysis of power distribution data

点击翻译按钮获取中文摘要

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