Supervised EV Charging Scheduling Algorithms with AMI System Coordination

This research explores the effectiveness of three electric vehicle (EV) charging models-Balance Load Sharing, First-Come, First-Served (FCFS), and Shortest Job First (SJF)-in managing electrical loads and preventing transformer overloads within Thailand's distribution systems. This is achieved...

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Vydané v:IEEE ... International Smart Cities Conference (Online) s. 1 - 6
Hlavní autori: Mateesakulkan, Supiwat, Suwanasri, Thanapong, Pirak, Chaiyod
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 29.10.2024
Predmet:
Delays
Electric vehicle charging
Electric Vehicles (EVs) Charging
Load management
Load modeling
Scheduling algorithms
Smart cities
Smart Grid
Smart grids
Smart meters
Tariffs
Transformers
ISSN:2687-8860
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Popis
Shrnutí:This research explores the effectiveness of three electric vehicle (EV) charging models-Balance Load Sharing, First-Come, First-Served (FCFS), and Shortest Job First (SJF)-in managing electrical loads and preventing transformer overloads within Thailand's distribution systems. This is achieved through collaboration between the Advanced Metering Infrastructure (AMI) smart meter and EV charger within the system. With the growing adoption of EVs, particularly during off-peak periods under Time-of-Use (TOU) tariffs, the study addresses the need for efficient load management to prevent system overloads. The Balance Load Sharing model, which dynamically adjusts charging power based on real-time load conditions, demonstrated superior efficiency by reducing overall charging times and eliminating queuing delays. In contrast, the FCFS and SJF models, while yielding similar overall charging times, showed significant differences in queue management. The FCFS model, which charges vehicles in their order of arrival, led to extended waiting times during peak periods. On the other hand, the SJF model, which prioritizes vehicles requiring shorter charging durations, effectively minimized queuing times, thereby enhancing overall system efficiency.
ISSN:2687-8860
DOI:10.1109/ISC260477.2024.11004232