THESIS WORKER - PREDICTIVE MODELS FOR HOME ENERGY MANAGEMENT SYSTEM

Thesis Worker at Volvo Cars Welcome to explore the world of Volvo Cars by writing your thesis with us! As a thesis worker in our organization, you are supported by a supervisor who follows you during your project.
All thesis projects are arranged in business-critical areas and therefore you will be able to contribute to our company purpose – providing freedom to move in a safe, sustainable and personal way – from day one!   Background.
The transition towards a more sustainable society is driving a trend of increased electrification and an increasing share of renewable energy production.
Many residential homeowners have, or are expected to, invest in battery electric vehicles (BEV), heat-pumps, solar panels, and residential energy storage systems (RESS).
To control such a household in a cost optimal manner, a so-called Home Energy Management System (HEMS) is needed, in order to schedule and execute the charging / discharging of BEVs and RESS.
Access to accurate information is needed to create such optimized plans for cost-efficient allocation of energy between, e.
., BEVs with bidirectional charging capabilities and RESS.
The plans should also take the price of buying energy from the grid into account.
However, they are unlikely to be useful without reliable forecasts regarding, e.
., hour-by-hour household energy consumption, solar panel energy production, or BEV availability and charging demands.
In addition, predictive models which are only able to provide point estimates of these quantities risk being insufficiently robust with respect to common disturbances, such as late BEV arrivals   Objective.
The aim of this thesis project is to develop predictive models which will be used for HEMS optimization.
In other words, the models should be well-adapted for integration with HEMS optimization algorithms, with a particular emphasis on robustness and computational efficiency.
For this purpose, it is also important that they include accurate uncertainty estimates along with the predictions.
Scope.
Develop predictive models for e.
., BEV availability and charging demands, and evaluate them on realistic usage data.
Integrate the developed models with HEMS optimization algorithms and evaluate their performance and sensitivity towards disturbances.
Qualifications.
M.
c.
in Data Science, Computer Science, Engineering Physics, Mathematics, or similar.
Relevant courses in machine learning, data science, algorithms, optimization, and programming.
Residence permit in EU / Schengen, i.
., a valid visa for Sweden.
Willingness to work in a pair with another student.
Contact information.
Manager.
Ole-Fredrik Dunderberg, Industrial Advisor.
Niklas Åkerblom, Ph.
.,     Volvo Cars - Driving change together​ Volvo Cars’ success is the outcome of a collaborative, diverse, and inclusive working environment.
Today, we are one of the most well-known and respected car brands, with around employees across the globe.
At Volvo Cars, your career is designed around your skills and aspirations, allowing you to reach your fullest potential.​  By , we aim to sell 1.
million cars annually, with 50 per cent being electric cars and sold directly to customers mainly through digital channels.
Make sure you’re in the front seat on this exciting journey as we pioneer the driving and electrification technologies of the future.