Multi-scale event-based optimization for matching uncertain wind supply with EV charging demand

Joint Optimization for Coordinated Charging Control of Commercial Electric Vehicles Under Distributed Hydrogen Energy Supply

“…We assume there are 20 Mennekes charging piles with two charging modes (P r 1 = 44kW and P r 2 = 88kW ) at each FCS [34]. The TOU price of electricity in [12] is used. Real commercial taxi data from [35] in Shanghai is used to generate time-varying EV trajectories (See Fig.…”

“…Morstyn et al solved the problem with consideration of battery voltage rise and maximum power limitation, which are commonly neglected [11]. Driven by the need of state space reduction, event-based optimization [12] and data-driven method [13] have been developed for a large-scale EV fleet charging operation.…”

Control for smart systems: Challenges and trends in smart cities

“…These methods are usually easy to implement, but they rely on some assumptions on the system and lack of performance guarantee. In light of this, event-based optimisation (Jiang, Jia, & Guan, 2022;Long & Jia, 2021b;Long, Tang, & Jia, 2017), ordinal optimisation (Long, Jia, Wang, & Yang, 2021) and hierarchical optimisation methods (Huang, Jia, & Guan, 2016) have been proposed recently to put forward new ideas for solving the problem quickly and efficiently.…”

Matching Uncertain Renewable Supply with Electric Vehicle Charging Demand—A Bi-Level Event-Based Optimization Method

“…where U t;i denotes whether the EV i is parking, then may be charged (or not). After the charging decisions have been made in the lower level, the state transition are defined as follows [31] : if U t;i D 0 and U t C1;i D 0 (33) where T is the length of the time interval. t C1; i is the random newly parking time and Á t C1; i denotes the random charging request.…”