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In his dissertation, computer scientist Roel Brouwer seeks to answer, among other questions, how a mathematical model can assist in the smart charging of electric vehicles. Brouwer defended his thesis on 8 July, focusing on controllable demand in electricity networks.

Regularly, news reports highlight the issue of overloaded electricity networks struggling to meet peak demand. The root cause is the energy transition, Brouwer notes in his dissertation. “Electricity is fulfilling an increasingly larger share of our energy needs. Simultaneously, the methods of electricity generation are changing, with a growing share coming from renewable sources that depend heavily on weather conditions.”

According to Brouwer, who conducted his research within the AI & Mobility Lab, scheduling techniques can aid in planning the demand and supply of electricity. He explains: “Currently, energy consumption is often adjusted with price incentives: making electricity cheaper when you want people to use it and more expensive when you don't. With scheduling techniques, you can adjust the timing and rate of energy consumption by considering certain constraints.”

Optimally aligned

Scheduling ensures that demand adjustments are optimally aligned within constraints such as the vehicles' charging needs, energy availability, and network capacity. Brouwer: “Advanced algorithms essentially create a jigsaw puzzle, where you calculate how each piece, or task, meets its total requirement. For instance, you can evenly distribute the charging needs over the available charging time to prevent peak loads on the network.”

The optimisation algorithm developed by Brouwer could potentially lead to more efficient use of available resources, a more stable electricity grid, and better utilisation of renewable sources. However, he emphasises that this is not yet a reality. “My research explores an abstract mathematical problem with a practical application. But reality is never as neat as the abstraction of a problem. Therefore, legal and technical steps are still needed to make this truly feasible.”

Two different roles

Brouwer is one of the first doctoral candidates from the Utrecht AI Labs to complete his research. He began his PhD-IT programme, the precursor to the Labs, in late 2017, combining work and research at the university's IT department. “Initially, the intention was for my IT work and research to be closely aligned, but for various reasons, this did not materialise. So, I was effectively juggling two different jobs, which made the process significantly more challenging.”

Nevertheless, the combination of dual roles proved to be highly valuable, says Brouwer, who continued working at the university’s IT department after submitting his thesis. “As a research engineer, I now support scientists with the software aspect of their research. Having conducted research myself, I can better understand their questions. It’s now primarily about recognising their problem rather than writing the best code ever.”