Title: Decentralised event triggered receding horizon online charge management of electric vehicles

Authors: Maryam Amirabadi Farahani; Mohammad Haeri

Addresses: Department of Mechanical, Computer, and Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran ' Advanced Control System Lab, Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran

Abstract: In this work, energy management of home customers with electric vehicles and renewable resources is modelled in the form of multi-agent systems. The agent decisions affect the others and the mean field game theory could provide a good solution for decision-making and control in multi-agent systems with a large number of agents. Due to uncertainties in the number of cars, power consumption, and production, online optimisation process is proposed by using the receding horizon concept of predictive control. The main problem in such processes is the calculations each agent should perform every hour. Hence, an event-based optimisation is employed to reduce the computational load. The main contribution of the present work is to optimise electric vehicles charging level in a decentralised and online manner in order to keep the load profile smoother in certain interval while reducing the computational complexity.

Keywords: decentralised control; predictive control; electric vehicles charging; mean field game; computation load.

DOI: 10.1504/IJAAC.2024.140531

International Journal of Automation and Control, 2024 Vol.18 No.5, pp.537 - 555

Received: 16 Apr 2023
Accepted: 14 Aug 2023
Published online: 22 Aug 2024 *

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