Paid MASTERs Thesis: Considering Uncertain Electrical Power Surplus in Model Predictive Control of Smart Homes

Farkas Kiss Endre legjobb állása BEST - Bioenergy and Sustainable Technologies GmbH

Bewerbung fur Paid MASTERs Thesis: Considering Uncertain Electrical Power Surplus in Model Predictive Control of Smart Homes

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Lieber BEST - Bioenergy and Sustainable Technologies GmbH!

Ich möchte mich bei Ihrem Unternehmen als Paid MASTERs Thesis: Considering Uncertain Electrical Power Surplus in Model Predictive Control of Smart Homes bewerben. 
Ich bin ein Fullstack-Entwickler, bei dem ich meine 10-jährige Erfahrung mit verschiedenen Technologien einsetzen kann.

Ich habe meinen Lebenslauf an diese E-Mail angehängt.

Wir freuen uns darauf, von Ihnen zu hören!


Endre Farkas Kiss "Sodika"
Java and PHP Fullstack Developer, Nudist, Vlogger

https://www.linkedin.com/in/farkas-kiss-63bb9210a
https://sodika.org

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Welcome to the sustainable world of BEST!

BEST - Bioenergy and Sustainable Technologies GmbH is the competence center in Austria that conducts pre-competitive industry-related research in the field of bioenergy and biobased economy.

At BEST we work as a team to actively shape the transition to a sustainable and climate friendly bioeconomy.

Your talent and your passion for research and science are explicitly needed with us. Collaborate with us on interesting and promising tasks and develop your scientific creativity. Join us on our approach to a more environmentally and climate friendly future!

Team player? Enthusiastic? Open-minded? Then you are exactly right at BEST.

Don’t wait any longer and apply now!

Tasks

To dedicated students (m/w/d) of electrical / mechanical engineering, information and computer engineering, or related disciplines we offer the opportunity to write a paid Master’s thesis. The thesis will be conducted in cooperation with the Institute of Automation and Control, Graz University of Technology.

Smart energy management systems for homes increasingly need to consider multiple energy sectors, i.e., electricity, heating and cooling, in order to reach their maximum potential. For example, surplus electricity from photovoltaics (PV) often is stored as heat in a thermal buffer by driving a heat pump or a heating rod. Varying electricity prices already provided by certain tariffs (e.g., aWATTar) and uncertainties in PV yield, however, make deciding on the best starting time and operating strategy difficult. We at BEST have developed a modular framework for energy management applications which answers such questions by formulating and solving an optimization problem. However, this optimization takes time, and systems often need to react quickly to changes in surplus electricity to avoid unwanted import from, or export to, the electricity grid.

Your tasks

Investigate existing solutions and typical setpoints for power inverters (minimum / maximum battery charging power) and heating rods / heat pumps
Deduce setpoints for low-level controllers based on optimization results that guarantee optimal behaviour even when only optimizing at a low sampling rate using, e.g., stochastic optimization
Test your algorithms in simulations and implement them on a real system
Requirements

Your interests

Studies in electrical, mechanical or computer engineering or physics
Ideally with some background in control engineering
Programming experience with MATLAB, Python or (ideally) Julia
Study admission for an Austrian university, EU visa, residence permit
Benefits

Your benefits

Integration into a dedicated team
Perspective of participation in follow-up projects after successful completion
Financial compensation based on student staff salary scheme
Provision of a work place (remote work from home also possible)
In the spirit of diversity, BEST would especially welcome applications from women.

Please also have a look at our homepage for 2 other master theses and one PhD position at our competence area Automation and Control.