An overview on impacts of electric vehicles integration into distribution network

Ma, Youjie; Zhang, Bin; Zhou, Xuesong

doi:10.1109/icma.2015.7237804

Cited by 12 publications

(11 citation statements)

References 14 publications

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“…Slow charging processes have a small impact on the grid as a small current is used to charge the vehicle. On the other hand, fast chargers use high currents, and have a bigger impact on the grid [262]. Conventionally, home systems use plug-in chargers, but stationary WPT systems are commercially available.…”

Section: Standards For Ev Wpt 45mentioning

confidence: 99%

A critical review on wireless charging for electric vehicles

Machura

2019

Renewable and Sustainable Energy Reviews

220

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Electric vehicles (EVs) have recently been significantly developed in terms of both performance and 10 drive range. There already are various models commercially available, and the number of EVs on road 11 increases rapidly. Although most existing EVs are charged by electric cables, companies like Tesla, 12 BMW and Nissan have started to develop wireless charged EVs that don't require bulky cables. 13 Rather than physical cable connection, the wireless (inductive) link effectively avoids sparking over 14 plugging/unplugging. Furthermore, wireless charging opens new possibilities for dynamic chargingcharging while driving. Once realised, EVs will no longer be limited by their electric drive range and the requirement for battery capacity will be greatly reduced. This has been prioritised and promoted worldwide, particularly in UK, Germany and Korea. This paper presents a thorough literature review on the wireless charging technology for EVs. The key technical components of wireless charging are summarised and compared, such as compensation topologies, coil design and communication. To enhance the charging power, an innovative approach towards the use of superconducting material in coil designs is investigated and their potential impact on wireless charging is discussed. In addition, health and safety concerns about wireless charging are addressed, as well as their relevant standards. Economically, the costs of a wide range of wireless charging systems has also been summarised and compared.

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Section: Standards For Ev Wpt 45mentioning

confidence: 99%

A critical review on wireless charging for electric vehicles

Machura

2019

Renewable and Sustainable Energy Reviews

220

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“…∀i ∈ N i , ∀t ∈ T , ∀l 𝜖L Equations ( 8) and ( 9) describe the active and reactive power flows in line l, from bus i to bus i+1; Equation (10) shows the voltage at bus i and its adjacent bus, bus i+1; P l i,t and Q l i,t are active and reactive load flow of line, l from bus i to bus i + 1 at time t ; P D i,t and Q D i,t are the active and reactive pre-EV load demands at bus i; P EV i,t is EV active power demand at bus i; p i,t and q i,t are power injections at bus i; V i,t is the voltage of bus i; r i and x i are series impedance of branch from bus i to bus i + 1; tap t in ( 14) is the tap position at time, t…”

Section: Network Constraintsmentioning

confidence: 99%

“…Although these losses can be estimated and added to the total combined demands (typically, losses in DNs are 5−10% of the supplied total demands), a more accurate and common way to calculate losses is to perform standard power flow analysis. In this paper, steady state three-phase ac power flow is carried out using [46], with relevant constraints described in (8)(9)(10)(11)(12)(13)(14)(15)(16)(17). The two main network components that are of most interest are the substation transformer at Bus 1 and the highest loaded line from Bus 1 to Bus 2 (Figure 13).…”

Section: Network Constraintsmentioning

confidence: 99%

“…The main concern is related to uncontrolled charging of a large number of EVs, which is generally assumed to coincide with the peak demand of the existing pre-EV loads, therefore likely resulting in network overloading. The term EV hosting capacity (HC) is often used to denote the maximum number of EVs that can be accommodated in a given DN [4][5][6], where impact of EVs on the DN is typically determined through the analysis of the resulting load profiles, that is, combined demand of existing pre-EV loads and EV charging load associated with uncontrolled, or in some way controlled charging of EVs [5,[7][8][9][10].…”

Section: Introduction and Brief Literature Reviewmentioning

confidence: 99%

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Hosting capacity of distribution networks for controlled and uncontrolled residential EV charging with static and dynamic thermal ratings of network components

Zakaria,

Duan,

Djokic

2023

IET Generation Trans & Dist

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The ongoing electrification of road transportation sector, which is expected to continue to strongly increase over the next years, will result in the connection of a significant number of electric vehicle (EV) chargers in LV and MV distribution networks, particularly in residential applications with on‐board (“slow”) EV chargers. In order to evaluate loading limits of existing distribution networks for the maximum number of EV chargers that can be safely connected (commonly denoted as a network EV “hosting capacity”, HC), this paper introduces a general approach to determine one commonly used network design parameter (after‐diversity maximum demand, ADMD) and one new parameter (maximum daily energy demand, MDED), which are both obtained from the load profiles of maximum per‐hour demands for uncontrolled residential EV charging. The presented approach uses actual EV charging data from the UK as the inputs in Monte Carlo simulations to generate daily EV charging profiles for arbitrary numbers of EVs, enabling to identify related ADMD, MDED and per‐hour maximum demand values, as well as their seasonal variations. The assessed ADMD, MDED and hourly maximum EV charging demands for uncontrolled EV charging are then combined with available UK residential daily load profiles before the EVs are connected (“pre‐EV demands”), where their combined coincidental and noncoincidental maximum demands are evaluated against the static thermal rating (STR) and dynamic thermal rating (DTR) loading limits of network components (transformers and overhead lines), taking into account relevant weather/ambient conditions. This is denoted as a network HC for uncontrolled EV charging. Finally, evaluating the resulting per‐hour maximum demand values against the STR and DTR loading limits and MDED values allows to select one particular scheduling method for controlled EV charging, which gives the absolute maximum number of EVs that can be safely connected in the considered network, that is, maximum network HC for fully controlled EV charging. The presented approach is illustrated on the example of the IEEE 33‐bus test network (modelled using typical UK network components), for the pre‐EV residential demands taken from the recordings at a UK MV substation, and for ambient data taken from a UK Met Office weather station. Obtained results allow to evaluate the range of network EV HC values for uncontrolled and controlled EV charging, that is, lower and upper HC limits, which can be correlated with the commonly used allocations of the firm and non‐firm network HC, respectively.

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“…Cable system does not only suffer from the EVs deployment, but also from the charging stations that pollute the selected system. Cables in accordance with [194] are prone to skin effect and proximity effect caused by the exposure to high frequency harmonics that deteriorate the life expectancy of the cable system. The bad power quality measures mean unevenly distributed current among the three-phase system, resulting in a high neutral current value.…”

Section: ) Transmission Cablementioning

confidence: 99%

Electric Vehicles Beyond Energy Storage and Modern Power Networks: Challenges and Applications

2019

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Electric vehicles (EVs) have been increasingly experiencing sales growth, and it is still not clear how to handle the associated impacts of a substantial integration of EVs against the power network performance and electricity deregulated market. Power networks development moves slowly compared to EVs, so it is hard to harmonize the two systems. Also, the associated cost required to modernize electric networks to accommodate the EVs additional loading is so huge that it makes it impractical. An electric network would suffer from many performances and quality-related problems if a significant number of EVs are not taken into account. Thus, it is vital to calculate at a reasonable accuracy the additional capacity to which the network would take. Also, the modeling of these EVs in terms of charge/discharge procedure (central or distributed) is essential to enable the optimization and compute potential impacts. The electricity market has to interface with the bidirectional supply nature of the EVs, so they become economically feasible. A business model that incorporates market structure and standards is selected in harmony with the charge/discharge model for best outcomes. Some approaches, algorithms, and schemes are deemed necessary to mitigate the effects of having EVs in the network. This paper presents a comprehensive review categorically on the recent advances and past research developments of EV paradigm over the last two decades. The main intent of this paper is to provide an application-focused survey, where every category and subcategory herein is thoroughly and independently investigated.INDEX TERMS Business model, central charging model, distributed charging model, electric vehicle, power network.

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An overview on impacts of electric vehicles integration into distribution network

Cited by 12 publications

References 14 publications

A critical review on wireless charging for electric vehicles

A critical review on wireless charging for electric vehicles

Hosting capacity of distribution networks for controlled and uncontrolled residential EV charging with static and dynamic thermal ratings of network components

Electric Vehicles Beyond Energy Storage and Modern Power Networks: Challenges and Applications

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