University of Twente Student Theses
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Improving the execution time of the FOCS algorithm implementation to enable real-time optimized EV scheduling
Loonstra, Joas (2025) Improving the execution time of the FOCS algorithm implementation to enable real-time optimized EV scheduling.
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Abstract: | The Flow-based Offline Charging Scheduler (FOCS) and Flow Under Local PEnalties Solver (FULPES) algorithms were made to schedule the charging of electric vehicles (EVs). The FOCS algorithm schedules the EVs without accounting for any charging guarantees a parking lot might provide. The FULPES algorithm is based on the FOCS algorithm, however it does provide a schedule which adheres to the charging guarantees. This increases execution times significantly. Due to the increase in execution time, real-time implementation could not be reached.\\ This report details how the goal to speed-up the FOCS algorithm by a factor 100 was met. Finally achieving a speed-up of 185 times, reducing execution time from 300 ms to 1.6 ms for 200 simultaneously charging EVs.\\ Methods such as porting from Python to C++, improving memory locality and changing variable types were used. The speed-up amount decreases as the instance size increased, due to the need for a slower fall-back method in solving maximum flow problems. This makes the current solution not yet applicable for larger parking lots. |
Item Type: | Essay (Bachelor) |
Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
Subject: | 54 computer science, 55 traffic technology, transport technology |
Programme: | Electrical Engineering BSc (56953) |
Link to this item: | https://purl.utwente.nl/essays/107624 |
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