Thesis Project - Optimization of Forecast Control for Electric Vehicle Charging

Thesis Project - Optimization of Forecast Control for Electric Vehicle Charging

Published 12/6/2022

Thesis Project - Optimization of Forecast Control for Electric Vehicle Charging

Are you studying computer engineering or programming with a focus on system development and looking for a thesis project? We have the assignment for you!

Background
Electricity supply continues to be a hot topic and at GARO, efficient energy consumption has always been an important parameter and driving force in the development of new products and solutions. In the current situation, it is becoming increasingly important to use energy at the right time. Some electrical products are easier to control and manage than others. Electric vehicle charging has a relatively well-developed infrastructure for the ability to control and schedule charging at specific times, and more and more players in the market provide services to obtain detailed forecasts for energy prices.

Assignment
The task is to propose how the existing algorithm and technology for charging electric vehicles when energy is cheap according to forecasts can be improved and/or optimized. An important parameter in the project will also be to take into account the load balancing against other external energy consumers, such as heat pumps, dishwashers, and stoves in the building.

Purpose/Goal
The purpose is to investigate how an algorithm for charging electric vehicles can be optimized with regard to forecasts for electricity prices. The goal is to supplement or replace today's algorithm to minimize energy costs for electric vehicle users.

Important information for applicants

  • Education: University or civil engineer with a focus on programming/system development
  • Start: According to agreement
  • Extent: Full-time 15/30 Hp (credit points)

After completion of the project, there is a possibility of employment after completed studies.

The person responsible for this recruitment is Daniel Carlson. Applications are submitted via email to  daniel.carlson@garo.se. Please attach your grades and a personal letter.

Welcome with your application!