Modelling, Simulation, and Management Strategy of an Electric Vehicle Charging Station Based on a DC Microgrid

Abstract

The rapid development of electric vehicles (EVs) increases the power demand, which causes an extra burden on the public grid, increasing the load fluctuations and, therefore, hindering the high penetration of EVs. In this paper, a real-time rule-based algorithm for electric vehicle (EV) charging stations empowered by a direct current (DC) microgrid is proposed. Such a DC microgrid model consists of EVs, an electrochemical storage system, a public grid connection, and photovoltaic sources. The EV charging station model is based on data-driven modelling while its management model takes into account discrete events. This paper focuses on power management strategy of an EV charging station under power limitation and considers most of the drivers' choices. The EV charging system topology is presented and common problems during an EV charging process are discussed, e.g., disconnection operation, standby mode, shedding, and restoration operation. Furthermore, the proposed power management deals with the uncertainties of EV drivers' behavior considering arbitrary and random choices through the human-computer interface. The simulation results obtained under MATLAB/Simulink verify the feasibility of the proposed management strategy that presents a good performance in terms of precise control.Appl. Sci. 2020, 10, 2053 2 of 21 load profile. In Li, Q et al. [13], a max-weight EV dispatch algorithm is proposed to control the EV charging rates, which can optimally utilize the distribution system capacity, respecting to power system's physical limits. The author of [5] discussed three main charging patterns of EV drivers from observations on measured data and proposed a novel schedule strategy based on "valley filling" concept to manage EV charging behaviors in order to relieve its impact on the public grid. However, the proposed methods do not make EVs to downscale the total charging power absorbed from the public grid.Xu, Z et al. [14] proposed a three-level (provincial level, municipal level, and charging station level) EV charging strategy that jointly optimizes system load profile and charging costs while satisfying customer charging requirements, which reduces system peak demand charging costs. A robust energy management strategy for EV charging stations is proposed in [15]. It is based on randomized algorithms and determines a day-ahead upper bound profile on the power consumption of EV charging stations and strictly respected in real-time, guarantying the grid stability in a more efficient and less costly manner. However, no additional storage unit could be used to compensate for EV uncertainties.Although various charging strategies have been employed to design different EV charging protocols in existing work, the current research outcomes are still limited to the interactions and power transfer between EVs and the public grid. The distributed energy generation system has attracted wide attention because of its on-site power consumption, which improves the peak performance of the public grid without increasing the grid c...

PV-Powered Charging Station for Electric Vehicles: Power Management with Integrated V2G

“…In the DC microgrid system, PV sources include 400 PV panels (40 in parallel and 10 in series), and its power under standard conditions is 100 kW [31]. The storage voltage and capacity are 300 V and 300 Ah, respectively.…”

“…The closer the time point to these two time-periods, the higher the tariff to absorb power from the public grid, which encourages EVs to discharge close to the "peak" periods of the public grid and charge away from the "peak" periods of the public grid. The simulation parameters of the system are detailed in Table 1 [31], where is the constant discharge power, which was chosen 89.6kW, _ is the storage current limitation, and are the lower limit and the upper limit, respectively, is the capacity of the storage, and _ is the rated voltage of DC bus. In order to highlight the "peak" periods of the public grid, the energy tariff of the public grid from 8:00 to 22:00 is designed as shown in Figure 7.…”

“…The closer the time point to these two time-periods, the higher the tariff to absorb power from the public grid, which encourages EVs to discharge close to the "peak" periods of the public grid and charge away from the "peak" periods of the public grid. The simulation parameters of the system are detailed in Table 1 [31], where is the constant discharge power, which was chosen 89.6kW, _ is the storage current limitation, and are the lower limit and the upper limit, respectively, is the capacity of the storage, and _ is the rated voltage of DC bus. The simulation parameters of the system are detailed in Table 1 [31], where P DIS is the constant discharge power, which was chosen 89.6 kW, I S_MAX is the storage current limitation, SOC MIN and SOC MAX are the soc lower limit and the soc upper limit, respectively, C ERF is the capacity of the storage, and v C_REF is the rated voltage of DC bus.…”

Smart charging impact on electric vehicles in presence of photovoltaics

“…Smart charging strategies are designed to accomplish the goals mentioned in section V using optimisation algorithms which is discussed in this section. A real-time rule-based algorithm for the management of EV charging stations in DC microgrid is simulated under MATLAB/Simulink which presents a reliable performance in terms of precise control [39]. Authors of [42] use a combination of deterministic and rule-based approaches for implementing energy storage management in the PV-integrated EV charging station which shall reduce EV charge cost using a wholesale energy pricing system.…”

PV-Powered Electric Vehicle Charging Stations: Preliminary Requirements and Feasibility Conditions

“…Their test results have proved the capability of the EV charging station under different conditions. In [26], a real-time rule-based algorithm has been proposed for the operation of a DC microgridbased EV charging station with imposing charging power limit depending on power availability. They have focused on the management strategy for the EV charging station, highlighting the interaction with EV users.…”