QoS-Aware Capacity Planning of Networked PEV Charging Infrastructure

Abdalrahman, Ahmed; Zhuang, Weihua

doi:10.1109/ojvt.2020.2979820

Cited by 10 publications

(9 citation statements)

References 46 publications

(80 reference statements)

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“…• Grid Expansion Costs: these are evaluated in few articles: [84] includes substation expansions (power dependent) and feeder upgrades (length and power dependent). • Energy Losses: many studies include losses in the electric network [25,32,53,[58][59][60][61]63] due to charging-discharging behavior.…”

Section: Dso-oriented Planningmentioning

confidence: 99%

“…Electrical Network Ref Year [22] 2019 [23] 2019 [24] 2018 [25] 2016 [28] 2016 [32] 2019 [82] 2020 [50] 2017 [51] 2019 [84] 2020 [53] 2016 [55] 2016 [58] 2019 [60] 2017 [61] 2019 [62] 2016 [63] 2014 [65] 2017…”

Section: Energy Lossmentioning

confidence: 99%

“…Study [46] allocates and sizes chargers between AC Level 2 (20 kW) or DCFC (80 kW), whereas [83] calculates the charging capacity of low voltage networks for both single-phase 3.7 slow and three-phase 11.7 kW chargers. A unique case is considered in [84], a recent study in which wireless solutions are implemented together with DC fast charging and AC Level 2 charging. However, no analysis is made to assess which technology brings the highest benefits.…”

mentioning

confidence: 99%

“…Charging Coverage: together with downtime, this is a critical parameter to ensure an optimal QoS of the CI and is a measure of user satisfaction [84]. In literature, the authors use different factors to quantify charging coverage, e.g., in [62], the factor is the number of charging EVs; in [22], the factor is inversely proportional to the distance between two adjacent CSs on the same road; and [38,133,134] aim to maximize the flow captured in their model-driven study.…”

mentioning

confidence: 99%

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Planning of High-Power Charging Stations for Electric Vehicles: A Review

et al. 2022

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Electrification of mobility is paving the way in decreasing emissions from the transport sector; nevertheless, to achieve a more sustainable and inclusive transport system, effective and long-term planning of electric vehicles charging infrastructure will be crucial. Developing an infrastructure that supports the substitution of the internal combustion engine and societal needs is no easy feat; different modes of transport and networks require specific analyses to match the requirements of the users and the capabilities of the power grid. In order to outline best practices and guidelines for a cost-effective and holistic charging infrastructure planning process, the authors have evaluated all the aspects and factors along the charging infrastructure planning cycle, analysing different methodological approaches from scientific literature over the last few years. The review starts with target identification (including transport networks, modes of transport, charging technologies implemented, and candidate sites), second, the data acquisition process (detailing data types sources and data processing), and finally, modelling, allocation, and sizing methodologies. The investigation results in a decision support tool to plan high-power charging infrastructure for electric vehicles, taking into account the interests of all the stakeholders involved in the infrastructure investment and the mobility value chain (distributed system operators, final users, and service providers).

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Section: Dso-oriented Planningmentioning

confidence: 99%

Section: Energy Lossmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Planning of High-Power Charging Stations for Electric Vehicles: A Review

et al. 2022

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“…The optimisation model presented in this paper, however, captures the trade‐off between station capacity and aforementioned financial considerations. Queueing‐based optimisation approaches for PEV charging stations have been adopted in References 28 and 29…”

Section: Introductionmentioning

confidence: 99%

Optimal design of electric vehicle charging stations for commercial premises

Bayram

Devetsikiotis

Jovanović

2021

Intl J of Energy Research

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Summary Influx of plug‐in electric vehicles (PEVs) creates a pressing need for careful charging infrastructure planning. In this paper, the primary goal is to devise a closed‐form expression for the PEV charging station capacity problem. Two types of commercial charging stations are considered. The first problem is related to the calculation of the optimal service capacity for charging lots located at workplaces where PEV parking statistics are given as a priori. The second problem, on the other hand, is related to the optimisation of arrival rates for a given station capacity. In the second part, the mathematical models are expanded for the case where multiple charger technologies serve customer demand. This time the goal is to calculate the optimal customer load for each charger type according to its rate. Calculations are carried out for both social and individual optimality cases. Markovian queues are used to model the charging station system to capture the complex interactions between customer load, service waiting times, and electricity cost. The related optimisation problems are solved using convex optimisation methods. Closed‐form expressions of station capacity and optimal arrival rates are explicitly derived. Both analytical calculations and discrete‐event simulations are carried out and the results show that 60% of the waiting times and 42% of the queue length can be reduced by optimal capacity planning.

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