Master Thesis - Energy Trading Optimization

Company Description


At AFRY, we bring together cutting-edge digital expertise and technologies in AFRY X. The new AFRY X division is a digital leader and expert hub in industrial IoT, AI, design and cyber security that helps our customers accelerate their digital transformation.
AFRY is a leading European company with a global reach in technology, design and consulting. We are accelerating the transition to a sustainable society. We are 19 000 dedicated experts in infrastructure, industry, energy and digitalization, who create sustainable solutions for future generations.




Job Description


AFRY X are looking for students who want to do their master's thesis with us. For this project we see that you can work individually or in pairs. You will be located at our office in Nordstan, Gothenburg and carry out the project on your own initiative with the help of a supervisor from our data science team.
Note that we have two different projects out and you are welcome to apply to both of them and we will see which one suits you the most.
Optimization of pool-based local energy trading in energy communities
In a research project funded by the Swedish Energy Agency, we are designing and prototyping a trading platform for energy communities. Local producers and consumers will place bids hour-by-hour for their forecasted energy need and availability, with the purpose of enabling more efficient usage of energy on a neighborhood level. This project is based on Fossil-free Energy Districts (FED[2]), a previous project tested on Chalmers campus Johanneberg. They used the GAMS[3] software to support dependencies between
bids over time. This for instance allows a building to hold off on purchasing heat one trading period if it has some margins and estimates it will be able to purchase the heat it needs for a cheaper price at a later time.


We wish to explore the same functionality in our ongoing research project. Students will be able to explore and evaluate available ready-made solutions, as well as trying their hands at implementing their own solution from scratch.
The first and most important dependency to introduce would be between energy carriers. Dependencies between trading periods can be explored if time allows, or left as a subsequent thesis subject for another person or group.


Read more:
https://www.johannebergsciencepark.com/en/projects/fed-fossil-free-energy-districts




Qualifications


We expect you to be familiar with programming in Python. Experience with linear programming or similar optimization techniques will also be necessary.


Other than this it is important for us to find the right person who identifies with our core values - Brave, Devoted, Team Player.






Additional Information


Time
Spring 2023. Specific starting date to be discussed.


Compensation
You will receive financial compensation after completed project.


Location
You will be located at our office in Nordstan - Gothenburg. This can be combined with remote work.


Recruitment process
Last date to apply is: 16/12
Note that the position may be filled before the last date of application.


Do you have any questions? Feel free to contact us.


Liam Håkansson, Team Lead Future Technologies
liam.hakansson@afry.com

Sofia Enander, Recruiter
sofia.enander@afry.com


AFRY is committed to creating an inclusive & diverse environment and we are actively looking for qualified candidates irrespective of gender, gender identity, sexual orientation, ethnicity, religion, disability, or age. You will be part of a global and diverse company where our differences are our strengths. Join us to accelerate the transition towards a sustainable society.