Analyzing the Charging Flexibility Potential of Different Electric Vehicle Fleets Using Real-World Charging Data

Barthel, Vincent; Schlund, Jonas; Landes, Philipp; Brandmeier, Veronika; Pruckner, Marco

doi:10.3390/en14164961

Cited by 18 publications

(2 citation statements)

References 25 publications

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“…The logistics site exhibits consistent charging profiles and high flexibility, distinguishing it from office and public agency sites. These findings hold implications for smart charging and ancillary services provision [101]. Seamless integration of EVs into distribution systems for grid operation and planning is crucial.…”

Section: F the Role Of Evs In Grid Flexibility Servicesmentioning

confidence: 95%

A Comprehensive Review and Analysis of the Allocation of Electric Vehicle Charging Stations in Distribution Networks

Yuvaraj,

Devabalaji,

Kumar

et al. 2024

IEEE Access

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In recent times, the limited availability of fossil fuels and growing concerns regarding the emission of greenhouse gases (GHGs) have directly impacted the shift from conventional automobiles to electric vehicles (EVs). Additionally, there have been notable advancements in new energy research, which have significantly improved the viability of EVs. Consequently, EVs have gained widespread recognition and have been rapidly adopted in many countries worldwide. However, the rapid growth of EVs has given rise to several challenges, such as insufficient charging infrastructure, unequal distribution, high costs, and a lack of charging stations, which have become increasingly significant. The limited availability of charging facilities is hindering the widespread adoption of EVs. However, as more people embrace EVs, there has been a growth in the installation of electric vehicle charging stations (EVCSs) in public locations. Recent research has focused on identifying the ideal locations for EVCSs in order to assist the electrification of transport systems and meet the growing demand for EVs. A well-developed EVCS infrastructure can help address some key issues facing EVs, such as pricing and range limitations. Researchers have used various methodologies, objective functions, and constraints to formulate the problem of identifying the best sites for EVCSs. Current research is focused on determining the best locations for EVCSs. This endeavor intends to ease the transition to electrified transport networks while also addressing the growing demand for EVs. This review article explores various optimization techniques to achieve optimal solutions while considering the impact of EV charging load on the distribution system (DS), environmental implications, and economic impact. The research used a standard IEEE 33-bus radial distribution system (RDS) with a full variety of potential energy sources to improve understanding of the subject. The use of the bald eagle search algorithm (BESA) and cuckoo search algorithm (CSA) aided in the best identification of energy source locations and their relative capacities. In addition, the examination of EV charging techniques, including both the traditional charging technique (TCT) and the innovative charging technique (ICT), is being undertaken to assess the effectiveness of these approaches. The study included ten separate scenarios, each of which was thoroughly evaluated to demonstrate the individual and synergistic usefulness of various energy sources in mitigating the effects of EV charging on the DS. The collected data from the empirical inquiry was aggregated and thoroughly analyzed.

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Section: F the Role Of Evs In Grid Flexibility Servicesmentioning

confidence: 95%

A Comprehensive Review and Analysis of the Allocation of Electric Vehicle Charging Stations in Distribution Networks

Yuvaraj,

Devabalaji,

Kumar

et al. 2024

IEEE Access

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“…It is recommended that this model be developed to be applicable in BEB studies associated with opportunity and overnight charging. Using real-world charging data to examine the charging flexibility potential of different electric vehicle fleets was introduced in [109]. The temporal and power-specific flexibility behavior of three separate vehicle fleets was explored in this research.…”

Section: Varying Energy Lossesmentioning

confidence: 99%

Review of the Estimation Methods of Energy Consumption for Battery Electric Buses

Al-Ogaili¹,

Al-Shetwi

Al‐Masri

et al. 2021

Energies

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In the transportation sector, electric battery bus (EBB) deployment is considered to be a potential solution to reduce global warming because no greenhouse gas (GHG) emissions are directly produced by EBBs. In addition to the required charging infrastructure, estimating the energy consumption of buses has become a crucial precondition for the deployment and planning of electric bus fleets. Policy and decision-makers may not have the specific tools needed to estimate the energy consumption of a particular bus network. Therefore, many state-of-the-art studies have proposed models to determine the energy demand of electric buses. However, these studies have not critically reviewed, classified and discussed the challenges of the approaches that are applied to estimate EBBs’ energy demands. Thus, this manuscript provides a detailed review of the forecasting models used to estimate the energy consumption of EBBs. Furthermore, this work fills the gap by classifying the models for estimating EBBs’ energy consumption into small-town depot and big-city depot networks. In brief, this review explains and discusses the models and formulations of networks associated with well-to-wheel (WTW) assessment, which can determine the total energy demand of a bus network. This work also reviews a survey of the most recent optimization methods that could be applied to achieve the optimal pattern parameters of EBB fleet systems, such as the bus battery capacity, charger rated power and the total number of installed chargers in the charging station. This paper highlights the issues and challenges, such as the impact of external factors, replicating real-world data, big data analytics, validity index, and bus routes’ topography, with recommendations on each issue. Also, the paper proposes a generic framework based on optimization algorithms, namely, artificial neural network (ANN) and particle swarm optimization (PSO), which will be significant for future development in implementing new energy consumption estimation approaches. Finally, the main findings of this manuscript further our understanding of the determinants that contribute to managing the energy demand of EBBs networks.

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Quantifying the Charging Flexibility of Electric Vehicles; An Improved Agent-Based Approach with Realistic Travel Patterns

Hogeveen¹,

Mosmuller²,

Steinbuch³

et al. 2023

Lecture Notes in Intelligent Transportation and Infrastructure

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Analyzing the Charging Flexibility Potential of Different Electric Vehicle Fleets Using Real-World Charging Data

Cited by 18 publications

References 25 publications

A Comprehensive Review and Analysis of the Allocation of Electric Vehicle Charging Stations in Distribution Networks

A Comprehensive Review and Analysis of the Allocation of Electric Vehicle Charging Stations in Distribution Networks

Review of the Estimation Methods of Energy Consumption for Battery Electric Buses

Quantifying the Charging Flexibility of Electric Vehicles; An Improved Agent-Based Approach with Realistic Travel Patterns

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