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Monday, May 9 • 2:00pm - 2:50pm
Data Science Applied: A Utilities Sector Case Study - Bram Steurtewagen

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Automated Metering Infrastructure (AMI) is gaining traction within the utilities sector and has brought with it numerous improvements in all related fields. Specifically in tariff setting and demand response models, classification of smart meter readings into load profiles helps find the right segments to target. The methodology explained in this tutorial combines commercial, government and open data with the internal company data to accurately predict the load profile of a new customer using high performing classification models in both R and PySpark. Load profiles are generated using a clustering algorithm and are subsequently used as the dependent variable in our classification model. The results of this model are then scored and interpreted in a business context. During the entire process, possible business hurdles will be identified and solutions will be offered.
 

Speakers
avatar for Bram Steurtewagen

Bram Steurtewagen

Ghent University
Bram Steurtewagen received his M.Sc. degree in Commercial Engineering (2013) and his M.Sc. degree in Marketing Analytics (2014) from Ghent University in Belgium. Since then, he has been pursuing a PhD in Data Analytics at the Faculty of Economics and Business Administration of Ghent University. His research interests lie mainly in predictive and prescriptive analytics in the utilities and retail sector. He has co-authored “Predicting Consumer... Read More →



Monday May 9, 2016 2:00pm - 2:50pm
Regency E

Attendees (18)