An electric vehicle charging station access equilibrium model with M/D/C queueing

Liu, Bingqing; Pantelidis, Theodoros P.; Tam, Stephanie; Chow, Joseph Y.J.

doi:10.1080/15568318.2022.2029633

Cited by 15 publications

(4 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The EV charging event at the charging station is a birth-death process; that is, the charging station's status increases as the EV arrives and decreases as the EV departs [27]. By applying Little's law, the charging station status L, which is the average number of charging EVs at the charging station, is given by [28]…”

Section: Data Analysis Resultsmentioning

confidence: 99%

Data-Driven Modeling of Vehicle-to-Grid Flexibility in Korea

Jang,

Kim,

2023

Sustainability

View full text Add to dashboard Cite

With the widespread use of electric vehicles (EVs), the potential to utilize them as flexible resources has increased. However, the existing vehicle-to-grid (V2G) studies have focused on V2G operation methods. The operational performance is limited by the amount of availability resources, which represents the flexibility. This study proposes a data-driven modeling method to estimate the V2G flexibility. A charging station is a control point connected to a power grid for V2G operation. Therefore, the charging stations’ statuses were analyzed by applying the basic queuing model with a dataset of 1008 chargers (785 AC chargers and 223 DC chargers) from 500 charging stations recorded in Korea. The basic queuing model obtained the long-term average status values of the stations over the entire time period. To estimate the V2G flexibility over time, a charging station status modeling method was proposed within a time interval. In the proposed method, the arrival rate and service time were modified according to the time interval, and the station status was expressed in a propagated form that considered the current and previous time slots. The simulation results showed that the proposed method effectively estimated the actual value within a 10% mean absolute percentage error. Moreover, the determination of V2G flexibility based on the charging station status is discussed herein. According to the results, the charging station status in the next time slot, as well as that in the current time slot, is affected by the V2G. Therefore, to estimate the V2G flexibility, the propagation effect must be considered.

show abstract

Section: Data Analysis Resultsmentioning

confidence: 99%

Data-Driven Modeling of Vehicle-to-Grid Flexibility in Korea

Jang,

Kim,

2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…This is unappealing because it slows the charging process, for example, filling up a 130 km battery takes 16 hours and 3.5 hours for level 1 and level 2, respectively [86]. On the other hand, the ease of integrating RES, ESS, and EV in DC MGs provides an opportunity for supplying the high power required to charge the EV within 20-30 minutes [87].…”

Section: Evolutionary Algorithmsmentioning

confidence: 99%

Enhancing Microgrid Operation Through Electric Vehicle Integration: A Survey

Sora,

Serban,

Petreus

2024

IEEE Access

View full text Add to dashboard Cite

The integration of renewable energy sources (RES) and electric vehicles (EVs) into microgrids (MGs) has significant potential for enhancing energy resilience, addressing environmental concerns, and promoting decentralized energy systems as a global shift towards sustainable energy solutions. Therefore, this survey paper provides a comprehensive discussion on improving MG operation through EV integration. This study evaluates the status of EV integration into MGs, focusing on technological advancements, and emerging trends, while pinpointing key technical challenges and opportunities. Furthermore, this paper examines the pivotal role of EVs in participating in vehicle-to-grid (V2G) services, providing ancillary support to improve MG performance. The importance of a reliable communication infrastructure for information exchange between EV, EV charging stations (EVCSs), and MG has been emphasized for the effective implementation of V2G services. This discussion extends to the contributions of EVs to primary, secondary, and tertiary MG controls. The paper also analyzes the integration of EVs into AC and DC MGs and further proposes configurations for both MG cases. Finally, the paper concludes by providing recommendations for future research to unlock the full potential of EV contributions to MG performance, thereby contributing to the ongoing advancement of sustainable and resilient energy systems. The key findings of this work include solutions for MG voltage and frequency regulation implemented through EV bidirectional converter power flow control, EV charger configurations for integration into AC and DC, EV contributions in improving the MG's operational resilience and adaptability, and the noteworthy challenges arising from V2G implementation in such systems.INDEX TERMS electric vehicle charging, microgrids, renewable energy sources, vehicle-to-grid

show abstract

“…This limited driving range penalizes the user, especially when considering long travels over Energies 2023, 16, 8030 2 of 29 extra-urban scenarios. Another issue is related to the long charging times, which may lead to long queues at charging stations [5]; this is also due to a lack of charging infrastructure. Regarding required charging times, even when considering fast chargers (60 kW) instead of conventional Level 1 chargers (1.8 kW), a recharging time of 20 min is still required to deliver an average driving range of 95-130 km [6].…”

Section: Introductionmentioning

confidence: 99%

Model-Based Calibration and Control of Tailpipe Nitrogen Oxide Emissions in a Light-Duty Diesel Engine and Its Assessment through Model-In-The-Loop

d’Ambrosio,

Di Dio,

Finesso

2023

Energies

View full text Add to dashboard Cite

The present paper investigates two different strategies for model-based calibration and control of tailpipe nitrogen oxide emissions in a light-duty 3.0 L diesel engine equipped with an aftertreatment system (ATS). The latter includes a diesel oxidation catalyst (DOC), a diesel particulate filter (DPF), and an underfloor selective catalytic reduction (SCR) device, in which the injection of diesel exhaust fluid (DEF), marketed as ‘AdBlue’, is also taken into account. The engine was modeled in the GT-SUITE environment, and a previously developed model-based combustion controller was integrated in the model, which is capable of adjusting the start of injection of the main pulse and the total injected fuel mass, in order to achieve desired targets of engine-out nitrogen oxide emissions (NOx) and brake mean effective pressure (BMEP). First, a model-based calibration strategy consisting of the minimization of an objective function that takes into account fuel consumption and AdBlue injection was developed and assessed by exploring different weight factors. Then, a direct model-based controller of tailpipe nitrogen oxide emissions was designed, which exploits the real-time value of the SCR efficiency to define engine-out NOx emission targets for the combustion controller. Both strategies exploit the model-based combustion controller and were tested through a Model-in-the-Loop (MiL) under steady-state and transient conditions. The advantages in terms of tailpipe NOx emissions, fuel consumption, and AdBlue injection were finally discussed.

show abstract

An electric vehicle charging station access equilibrium model with M/D/C queueing

Cited by 15 publications

References 25 publications

Data-Driven Modeling of Vehicle-to-Grid Flexibility in Korea

Data-Driven Modeling of Vehicle-to-Grid Flexibility in Korea

Enhancing Microgrid Operation Through Electric Vehicle Integration: A Survey

Model-Based Calibration and Control of Tailpipe Nitrogen Oxide Emissions in a Light-Duty Diesel Engine and Its Assessment through Model-In-The-Loop

Contact Info

Product

Resources

About