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A Rule-Based Method for Efficient Electric Vehicle Charging Scheduling at Parking Lots
George Konstantinidis, Emmanuel Karapidakis, Alexandros Paspatis

A Rule-Based Method for Efficient Electric Vehicle Charging Scheduling at Parking Lots

Science & Mathematics Published 2022 Verification Pending

Overview & Synopsis

Electromobility is being promoted to reduce the greenhouse gas emissions. To this extend, and through the technical advancement of electric vehicles (EVs), EVs are increasing in a fast pace. However, their charging could impose problems to the distribution network, local substations and transformers. This holds true especially in charging stations with a high number of EV chargers, such as the parking lots. To address this, a rule-based algorithm is proposed in this paper to minimize the charging cost, participate in a demand response program, and simultaneously satisfy the technical and operational constraints of the EVs and parking lot’s local transformer. The proposed rule-based algorithm is compared with the case of uncoordinated charging and with an optimization-based charging schedule based on the particle swarm optimization (PSO). The obtained results indicate that even if the charging cost with the proposed algorithm is not significantly reduced compared to the PSO charging strategy, the executed time is significantly lower. Comparing with the uncoordinated charging, the proposed algorithm has a lower charging cost and a similar execution time.

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Document Information

Document Title A Rule-Based Method for Efficient Electric Vehicle Charging Scheduling at Parking Lots
Author / Organization George Konstantinidis, Emmanuel Karapidakis, Alexandros Paspatis
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2022
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-192413
Original Source Link Visit Source Page on hal.science »