PhD Candidate in Data-driven Load Disaggregation and Building Load Profile Classification

Updated: 4 months ago
Deadline: 01 Feb 2022

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About the position

The Department of Electric Power Engineering (IEL), at the Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU), invites applications for a PhD Candidate position in “Data-driven load disaggregation and building load profile classification”. This PhD position is associated with the Electricity Markets and Energy System Planning (EMESP) research group at IEL and a part of COFACTOR project funded by the Research Council of Norway. 

Electrification of all end‐use sectors, including transportation and buildings, is identified as a key enabler in the transition to a sustainable energy system. This will lead to increased electricity demand, increased peak load and modified consumption patterns, challenging traditional grid planning practices.

COFACTOR project will provide new knowledge on current and future load profiles for typical Norwegian buildings and establish a methodology for calculating their peak load considering coincidence factors of different energy services. The project will collect a comprehensive data set of detailed energy measurements for approximately 400 buildings. However, most Norwegian buildings have meter values for hourly total net energy use, but detailed measurements of energy use separated on different energy services behind the meter are usually not available. 

COFACTOR will develop new data-driven methods for load disaggregation. Detailed knowledge on disaggregated load profiles behind the meter provides the basis to evaluate how these technologies interact and how buildings can become active nodes in the electricity grid, thus playing a key role in the transition to a sustainable energy system.

In this context, the main task of the PhD candidate in the doctoral work will be two-fold. First, to develop a modeling framework and methodologies for load disaggregation to specially account for energy demand services and energy technologies (domestic hot water, space heating, EV charging, PV panels, other appliances, etc.) using advanced statistics and machine learning. Second, to use disaggregated load data for classifying building load profiles and providing insights into the relationship between different buildings categories and their energy demand services.

The prospective candidate will be part of the Electricity Markets and Energy System Planning (EMESP) research group . The candidate will also cooperate closely with the Cofaktor research team. The PhD candidate will have the opportunity to collaborate with researchers in project partner institutions and benefit from collaborative research and education activities.

The duration of the PhD employment is 3 years.

Main supervisor: Associate Professor Jayaprakash Rajasekharan - NTNU
Co-supervisor: Associate Professor Karen Byskov Lindberg - NTNU
The position's working place is NTNU campus in Trondheim.

The candidate will report to the Head of the Department at IEL.

We are looking for PhD candidates from all nationalities, who want to contribute to our quest to create knowledge for a better world.

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