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1、March 2025 Savings from smart chargingelectric cars and trucks inEurope:A case study forFrance in 2040Part of RAP and ICCTs Benefits of EVs Through Smart Charging Global ProjectBy Julia Hildermeier,Andreas Jahn,Jakob Schmidt,Marie Rajon Bernard,Pierre-Louis Ragon&Hussein Basma Acknowledgments We wou

2、ld like to thank the following people for their comments and insights on an earlier draft of this paper.The authors are entirely responsible for the content of this paper.Jaap Burger,Dave Farnsworth,Louise Sunderland Regulatory Assistance Project Marin Dil,Claire Lucas,Lo Quignon Artelys Felipe Rodr

3、iguez,Hongyang Cui,Palak Thakur International Council on Clean Transportation Authors Julia Hildermeier Regulatory Assistance Project Andreas Jahn Regulatory Assistance Project Jakob Schmidt International Council on Clean Transportation Marie Rajon Bernard International Council on Clean Transportati

4、on Pierre-Louis Ragon International Council on Clean Transportation Hussein Basma International Council on Clean Transportation Regulatory Assistance Project(RAP)Rue de la Science 23,1050 Brussels,Belgium inforaponline.org|www.raponline.org|RegAssistProj Regulatory Assistance Project(RAP).This work

5、is licensed under a Creative Commons Attribution-NonCommercial License(CC BY-NC 4.0).International Council on Clean Transportation(ICCT)Fasanenstrae 85,10623 Berlin,Germany communicationstheicct.org|www.theicct.org|TheICCT 2|SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE REGULATORY A

6、SSISTANCE PROJECT(RAP)Table of contents Acknowledgments.1 Benefits of EVs Through Smart Charging:A joint project by RAP and ICCT.3 Introduction.7 Policy context.8 Case study:Smart EV charging.10 EV uptake and charging demand in 2040.11 EV fleet projected for 2040.12 Smart charging scenarios.13 Grid

7、characteristics.14 Smart charging tariffs.15 Main findings.18 Unmanaged EV charging will increase Essonnes peak load by 33%in 2040.18 Smart EV charging can reduce peak in Essonnes grid by up to 6%.18 Bidirectional charging can further reduce peak load by up to 9%.19 Smart EV charging can save up to

8、25%on network reinforcement costs in Essonne annually.19 All EV customer groups can contribute with their flexibility to achieve system benefits.20 Conclusions and policy recommendations.24 Annex.27 REGULATORY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|3 Be

9、nefits of EVs Through Smart Charging:A joint project by RAP and ICCT This paper is part of a global project by the Regulatory Assistance Project(RAP)and the International Council on Clean Transportation(ICCT)studying the economic and environmental benefits of deploying smart electric vehicle(EV)char

10、ging in specific geographies.The project identifies those benefits as avoided system costs and avoided emissions,and shows how system costs can be reduced based on four regional case studies in selected areas within the four largest global EV markets:China,1 the United States,2 India3 and Europe.As

11、the last instalment in the series,this paper investigates the benefits of smart EV charging in Europe,based on a case study of a representative region in France,which is introduced separately below.The global market for EVs is maturing quickly.In 2023,EVs accounted for 15%of vehicle registrations in

12、 Europe(23%if plug-in hybrid vehicles are considered).4 This is two to three times higher than EV registrations in 2020.National and local policies such as the European carbon dioxide(CO2)standards for light-duty vehicles5 in several jurisdictions targeting tailpipe emissions of road transport vehic

13、les further contributed to this growth,resulting in an increasing EV fleet globally over the past decade.6 The global e-heavy duty vehicle(e-HDV)market witnessed significant growth between 2023 and 2024.In Europe,for instance,although e-HDVs only comprised 4.1%of total HDV sales in the EU-27 region,

14、data shows that the e-HDV market grew by 54%between the first half of 2023 and the first half of 2024.With a continuously growing fleet,challenges and opportunities arise in many regions with regard to the integration of the EV fleet into the power grid.If additional demand from EVs remains unmanage

15、d,this would lead to substantial cost increases to meet their needs both in terms of power production and distribution,as EVs would likely be charged during existing peak periods and exacerbate peak demands.If this transition is not managed carefully,the associated growth in electricity demand will

16、lead to higher costs for consumers,the power 1 Gao,C.(2025,March).Smoothing the way:Coaxing more flexible charging from Chinas mammoth EV fleet.Regulatory Assistance Project.https:/www.raponline.org/knowledge-center/smoothing-the-way/2 Farnsworth,D.,Enterline,S.,Basma,H.&Kadoch,C.(2024,June 24).Unlo

17、cking system savings with flexible EV charging:Lessons from Colorado.Regulatory Assistance Project.https:/www.raponline.org/knowledge-center/unlocking-system-savings-with-flexible-ev-charging-lessons-from-colorado/3 Hildermeier,J.,Scott,D.,Reddy,S.,Kaur,H.&Thakur,P.(2024,December 16).Optimising elec

18、tric heavy-duty truck charging in India.Regulatory Assistance Project.https:/www.raponline.org/knowledge-center/optimising-electric-heavy-duty-truck-charging-in-india/4 Monteforte,M.,Mock,P.,Mulholland,E.,Rodrigues Poupinha,C.&Tietge,U.(2024,December).European vehicle market statistics 2024/25.Inter

19、national Council on Clean Transportation.https:/theicct.org/wp-content/uploads/2024/12/250114_Pocketbook_2024_25_Web_korr.pdf 5 European Commission.(2024,February 12).CO emission performance standards for cars and vans.https:/climate.ec.europa.eu/eu-action/transport/road-transport-reducing-co2-emiss

20、ions-vehicles/co2-emission-performance-standards-cars-and-vans_en 6 U.S.Environmental Protection Agency.(2023,November 21).Light-Duty Vehicle Greenhouse Gas Regulations and Standards.https:/www.epa.gov/regulations-emissions-vehicles-and-engines/light-duty-vehicle-greenhouse-gas-regulations-and 4|SAV

21、INGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE REGULATORY ASSISTANCE PROJECT(RAP)system and the environment,and may slow down the transition to a cleaner road transport sector.7,8 Smart EV charging(also referred to as optimised,managed or controlled charging)can help overcome many of th

22、ose challenges,enabling EVs to be utilised to provide optimum system flexibility.Smart charging is a key tool to reduce the consumption of fossil-powered electricity and integrate more variable renewables into the grid by charging EVs when there is sufficient renewable energy available.In doing so,s

23、mart charging can promote reductions in carbon emissions and reduce or entirely avoid the need for costly upgrades to the power grid.9 A special category of smart charging is bidirectional or vehicle-to-grid(V2G)charging,which uses vehicle batteries to discharge electricity back to the power system

24、when it is not needed for transport purposes,at times when it is most beneficial to the user and the system.10 While smart charging of EV fleets has been studied from the user benefits point of view,11 it is important to better understand the value that EVs can have as flexibility assets12 for the p

25、ower system13 in large EV markets.14,15 The analytical framework used in all four regional case studies of this project is designed to demonstrate the economic and environmental value of smart charging of electric light-duty and heavy-duty vehicles.It is composed of five sequential steps,summarised

26、in Figure 1 below.16 First,the EV stocks are estimated in a given geography for all main vehicle segments(for the segments considered in this EU regional case study,see Annex),highlighting their battery size needs and the expected fleet growth over time.Second,based on the EV stocks,the charging inf

27、rastructure needs are assessed,quantifying metrics such as the number of charging stations required and the stations power capacity and charging load.The third step entails an estimate of the optimal geospatial deployment of those charging stations,considering constraints related to the local grid p

28、ower capacity,space limitations,logistical constraints,and drivers behaviours.Step four identifies smart charging techniques available or implementable in the region,and opportunities for EV load to 7 Das,H.S.,Rahman,M.M.,Li,S.&Tan,C.W.(2020,March).Electric vehicles standards,charging infrastructure

29、,and impact on grid integration:A technological review.Renewable and Sustainable Energy Reviews,120(109618).https:/doi.org/10.1016/j.rser.2019.109618 8 Ashfaq,M.,Butt,O.,Selvaraj,J.&Rahim,N.(2021,May).Assessment of electric vehicle charging infrastructure and its impact on the electric grid:A review

30、.International Journal of Green Energy,18(7):657686.https:/doi.org/10.1080/15435075.2021.1875471 9 Hildermeier,J.,Kolokathis,C.,Rosenow,J.,Hogan,M.,Wiese,C.&Jahn,A.(2019,December).Smart EV Charging:A Global Review of Promising Practices.World Electric Vehicle Journal,10(4):80.https:/ 10 Burger,J.(20

31、23).Enabling two-way communication:Principles for bidirectional charging of electric vehicles.RAP.https:/www.raponline.org/knowledge-center/enabling-two-way-communication-principles-for-bidirectional-charging-of-electric-vehicles/11 Hildermeier,J.,Burger,J.,Jahn,A.&Rosenow,J.(2023,January).A Review

32、of Tariffs and Services for Smart Charging of Electric Vehicles in Europe.Energies,16(1):88.https:/ 12 Flexibility assets are assets to decouple time of supply and consumption,as battery storage,heat storage or EVs.13 International Energy Agency.(2022,December).Grid Integration of Electric Vehicles

33、A manual for policy makers.https:/ 14 Anwar,M.B.,Muratori,M.,Jadun,P.,Hale,E.,Bush,B.,Denholm,P.,Ma,O.&Podkaminer,K.(2022,January).Assessing the value of electric vehicle managed charging:a review of methodologies and results.Energy&Environmental Science,15(2):466498.https:/doi.org/10.1039/D1EE02206

34、G 15 Xue,L.,Jian,L.,Ying,W.,Xiaoshi,L.&Ying,X.(2020,January).Quantifying the Grid Impacts from Large Adoption of Electric Vehicles in China.World Resources Institute.https:/www.wri.org/research/quantifying-grid-impacts-large-adoption-electric-vehicles-china 16 Basma,H.(2024,April 26).Assessing the E

35、conomic and Environmental Benefits of Electric Vehicles Smart Charging Presentation.EVS37.REGULATORY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|5 integrate into,based on which charging can be optimised.To quantify savings from smart EV charging in step 5,we

36、 consider optimisation strategies based on flexibility options provided in programmes that utilise time-of-use rates,direct load control,and incentives that can help optimise EV load to support the use of existing grid capacity and renewable energy.Figure 1.Framework for smart electric transport Sou

37、rce:Basma,H.(2024,26 April).Assessing the Economic and Environmental Benefits of Electric Vehicles Smart Charging This interplay between EVs and power systems represents a significant opportunity for demand-side flexibility if policymakers and planners in the power and transport sectors adopt smart

38、charging in decision-making via,for example,charging infrastructure regulation and build-out.Results of the regional case studies that we consider here illustrate benefits from smart EV charging for both power sector planning and transport.6|SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EU

39、ROPE REGULATORY ASSISTANCE PROJECT(RAP)Findings and recommendations This paper studies grid benefits of smart EV charging in the French region of Essonne,south of Paris,which comprises a well-developed,urban and rural power network representative of many other European regions.The study finds that u

40、sing EV flexibility through smart charging has the potential to reduce Essonnes electrical infrastructure costs significantly.We analysed savings from optimally charging the fleet of electric passenger and heavy-duty vehicles forecasted for the region in 2040,taking into account expected transport p

41、ractices,charging patterns and grid characteristics projected from current traffic behaviour and grid use.We find that:Smart charging of the EV fleet can reduce peak load on electricity grids and related system costs.In our case study,smart charging can reduce peak load on the grid by 6%in 2040,comp

42、ared to unmanaged charging.Bidirectional charging can add an even greater reduction of 9%,compared to unmanaged charging in 2040.Smart charging is a collective task across all EV fleets:it covers not only smart residential overnight charging,but also optimised daytime charging of EV fleets at workpl

43、aces,and fully using electric trucks flexibility windows while parked at the depot.Even high-capacity truck charging at highways doesnt necessarily contribute to peak load if other fleets present in the grid are charging smartly in parallel and thus free up grid capacity.Smart charging also avoids d

44、istribution system costs by flattening system peaks.In our analysis,smart charging in 2040 could reduce the need for power line reinforcements by 23%,and allow for 37%less transformer reinforcements in Essonne than unmanaged charging.Overall,a broad estimate suggests that smart EV charging avoids ab

45、out one-quarter of yearly network reinforcement costs in the area studied.As Frances power grids are relatively well developed thanks to electrified heating,its likely that other average European grids will benefit to an even greater degree from smart charging.REGULATORY ASSISTANCE PROJECT(RAP)SAVIN

46、GS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|7 Savings from smart charging electric cars and trucks in Europe:A case study for France in 2040 Introduction The aim of this study is to quantify the savings on a selected distribution grid from optimising charging of a fleet of electric car

47、s and trucks.A lack of investment in distribution grids,paired with the need for more efficient use of existing capacity,are currently one of the key bottlenecks for EV uptake in Europe.Efficient electrification of transport is key to the EUs future competitiveness and to meeting climate targets.Thi

48、s study shows that with optimised charging of EVs,power grids can be used in a more cost-efficient way,that can save grid investment costs and hence accelerate the adoption of transportation electrification.To quantify savings from smart EV charging and illustrate how these savings can be achieved,R

49、AP and ICCT contracted with Artelys(),a consultancy specialised in Recommendations:To make EV grid integration cost-efficient and prepare rapid transport electrification,we recommend that policymakers and energy regulators at EU and national levels:Ensure that smart residential and workplace chargin

50、g for EVs,and smart depot charging for e-trucks,are the default mode of charging and create maximum system benefits.Broadly introduce cost-reflective pricing of power networks,e.g.through time-varying network pricing,to incentivise smart EV charging.Require transparency on network use from distribut

51、ion grid operators(DSOs)so that more cost-reflective tariffs can be designed and implemented.Allow EVs to participate as flexibility resources in energy markets to generate value for customers through demand-response programmes,e.g.via smart tariffs and services.Facilitate joint planning by transpor

52、t and energy stakeholders to ensure balanced build-out of charging infrastructure;as well as scale distribution system upgrades to the appropriate levels,locally and time-wise,avoiding overinvestment.8|SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE REGULATORY ASSISTANCE PROJECT(RAP)d

53、istribution grid modelling,to analyse potential studied impacts of light and heavy-duty vehicle electrification.This paper is structured as follows.First,we set out the policy context for smart EV charging in Europe,providing the broader regulatory background for our case study.The main section of t

54、his paper(Case study)presents projections from EV charging provided by ICCT,and the modelling of grid benefits from smart charging in the selected French region of Essonne.For this analysis,Artelys conducted a physical simulation of Essonnes electrical distribution network,17 based on projections fo

55、r electricity demand from EVs in three scenarios with different degrees of EV flexibility used for smart charging(see also Table 2).The Main findings section discusses results for all scenarios.Granular analysis of a mixed EV fleet composed of electric passenger cars and trucks illustrates how diffe

56、rent(smart)EV charging use cases can contribute to reducing peaks on the local electricity system.In addition to positive grid effects from overnight residential EV charging,for example,we also illustrate how midday workplace charging and overnight depot charging of trucks can help to shave peak loa

57、ds in the grid.In the last section,Conclusions and policy recommendations,we discuss policy options for decision-makers.These are derived from the French case but apply more broadly to enhancing smart EV charging in the European policy context.Policy context There is growing understanding among EU p

58、olicymakers that smart EV charging is an essential tool to ensure that EV uptake is beneficial for users,the power grids and the environment.18 The EUs first regulation to set up a pan-European public charging network,the so-called Alternative Fuels Infrastructure Regulation(AFIR),entered into force

59、 in April 2024 and requires the build-out of essential public charging network starting from 2025.It sets installed capacity and coverage targets for both light and heavy-duty EV charging infrastructure.All new charging infrastructure is capable of smart charging,which means being able to measure an

60、d communicate consumption.19 In addition to this basic smart capability of the charging infrastructure itself,an enabling energy market framework is necessary to ensure that the value of EVs as flexibility assets20 can be fully captured by 17 A detailed documentation of the simulation and results ca

61、n be found here:https:/ 18 Energy-efficient electrification of transport,among other sectors,is identified e.g.in the European Commissions report on The future of European competitiveness(the Draghi report),https:/commission.europa.eu/document/download/97e481fd-2dc3-412d-be4c-f152a8232961_en.The dev

62、elopment of an Electrification Action Plan is identified as a policy priority for the Commission,e.g.Energy Commissioner Jorgensens Mission Letter of 17 September 2024:https:/commission.europa.eu/document/download/1c203799-0137-482e-bd18-4f6813535986_en?filename=Mission%20letter%20-%20JORGENSEN.pdf.

63、A new policy focus on improving investments into and smart use of power grids is suggested in the European Commissions Grid Action Plan(2023):https:/ec.europa.eu/commission/presscorner/detail/en/ip_23_6044 19 European Commission.(2021,July).Proposal for a regulation of the European parliament and of

64、 the council on the deployment of alternative fuels infrastructure,and repealing Directive 2014/94/EU of the European Parliament and of the Council.https:/eur-lex.europa.eu/resource.html?uri=cellar:dbb134db-e575-11eb-a1a5-01aa75ed71a1.0001.02/DOC_1&format=PDF 20 Claeys,B.,Hogan,M.,Jahn,A.,Morawiecka

65、,M.,Pat,Z.,Scott,D.&Yule-Bennett,S.(2022,July)Power System Blueprint:Market access for demand-REGULATORY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|9 market actors the key condition required to make smart charging beneficial.European energy market reforms f

66、rom 2019,as well as their recent partial recast in 2023,build toward this goal by adopting some important foundations.21 For example:Transparency is increased by enabling consultation of grid development plans,requiring grid operators to disclose grid information,and providing greater market access

67、for aggregators and charging point operators(CPOs).22 Network operators are encouraged to introduce time-varying network fees.23 Requirements are placed on national energy regulators to introduce standards that apply to DSOs and transmission system operators(TSOs)for using flexible grid agreements.2

68、4 Smart and where appropriate bidirectional EV charging is also encouraged through the amended Renewable Energy Directive,25 which requires Member States to increase the share of renewable energy used(e.g.)in buildings and transport.To increase the energy efficiency of and renewable energy used in b

69、uildings,the Directive requires Member States to develop national support schemes or regulations promoting“substantial increases in renewables self-consumption,renewable energy communities,local energy storage,smart recharging and bidirectional recharging,other flexibility services such as demand re

70、sponse”26.To reach the Directives renewable energy share target set for the transport sector,Member States also have to establish a mechanism to allow fuel suppliers to exchange credits for supplying renewable energy used in transport.This includes renewable energy supply to EVs at public,and in som

71、e countries private,charging points,both of which can be helped by smart charging.Another important regulatory building block enabling smart EV charging is the recently revised European building regulation.The Energy Performance of Buildings Directive27 requires charging equipment and precabling to

72、be placed in parking areas of new and renovated non-residential buildings,and encourages Member States to support charging equipment for residential buildings.Both requirements present an important opportunity to accelerate smart residential and workplace charging.An important gap in the EPBDs side

73、flexibility.Regulatory Assistance Project.https:/blueprint.raponline.org/market-access-for-demand-side-flexibility/21 European Commission.(n.d.)EU electricity market design.https:/energy.ec.europa.eu/topics/markets-and-consumers/electricity-market-design_en That said,previous energy market provision

74、s concluded in 2019 designed to advance demand-side flexibility in national legislation are not yet fully implemented,and the rollout of smart meters has been slow in some European countries such as Germany.22 This is not from the recent adjustments(Directive 2019/944 Article 32 from 2023)but it is

75、not yet implemented into national law everywhere.23 Article 2(7)Amendments to Regulation(EU)2019/943.24 Amendments to Directive(EU)2019/944 Article 2(3)These agreements provide a guaranteed capacity and a non-guaranteed capacity for a grid connection,as an alternative to todays secured grid capacity

76、 agreements.25 DIRECTIVE(EU)2023/2413 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 18 October 2023 amending Directive(EU)2018/2001,Regulation(EU)2018/1999 and Directive 98/70/EC as regards the promotion of energy from renewable sources,and repealing Council Directive(EU)2015/652.(RED III)https:/

77、eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=OJ:L_202302413 26 RED.III,Art.15a 27 DIRECTIVE(EU)2024/1275 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 24 April 2024 on the energy performance of buildings(recast)(EPBD).https:/eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=OJ:L_202401275 10|SAV

78、INGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE REGULATORY ASSISTANCE PROJECT(RAP)definition of non-residential buildings is that it does not include freight vehicle depots,which would further enable smart charging of electric delivery and long-haul trucks,an essential EV use case.28 Thi

79、s gap could be addressed by Member States through other regulatory means to further support the electrification of truck depots.Case study:Smart EV charging We chose the representative French department of Essonne,south of Paris,France(pictured in Figure 2)to study the economic benefits defined as a

80、voided grid costs that could be achieved through optimising EV charging.Figure 2.Case study grid area By choosing a representative area of electricity consumption,our case study covers the majority of EV charging use cases in the EU and their demands on the electricity network.This region is represe

81、ntative of a European mix of consumption patterns due to its 28 Hildermeier,J.,Jahn,A.&Rodriguez,F.(2020).Electrifying city logistics in the European Union:Optimising charging saves cost.https:/www.raponline.org/wp-content/uploads/2023/09/rap-icct-eu-city-logistics-factsheet-2020-nov-19.pdf REGULATO

82、RY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|11 composition.Essonne offers a mixture of urban,semi-urban and rural areas,as well as major highways,each featuring one or several dominant EV charging use cases.For example,public and private electric light du

83、ty vehicles(eLDVs)charging in urban areas,heavy-duty vehicles(HDVs)depot charging in semi-urban areas,fast eLDV and eHDV charging along highways,and residential eLDV charging in rural areas.The degree to which the French grid is representative of other European grids is discussed further down in Gri

84、d characteristics.In general,the findings of this case study can be considered as rather conservative,as the French grid is comparatively well developed compared to other EU countries thanks to electrified heating.This implies that our findings would apply to an even greater degree in other average

85、European grids.EV uptake and charging demand in 2040 We quantified the EV fleets energy and charging needs using models developed in-house by ICCT,which will be highlighted in this section.The charging needs are directly related to the EV penetration rate across different road transport segments.Tho

86、se include light-duty vehicles(LDVs)and heavy-duty vehicles(HDVs).Given the different operational and charging patterns for the LDV and HDV segments,and also for sub-segments within them,we further segment LDVs into passenger cars and light commercial vehicles(LCVs),and further segment HDVs into bus

87、es,coaches,trucks,regional tractors,and special vehicles,in line with the approach employed by the French Bureau of Statistics.We estimate there will be 582,510 eLDVs(which include battery and plug-in-hybrid electric vehicles)and 8,355 e-HDVs in Essonne in 2040.As a share of the projected national f

88、leet,this means Essonne will hold 1.9%of all eLDVs and 1.8%of all eHDVs in France in 2040.The EV penetration rate and fleet size are estimated using local vehicle stock and registration data from the Statistical Data and Studies Department,29 which is then combined with electrification scenarios fro

89、m the ICCTs Roadmap model,30 derived from policy scenarios.The policy scenarios considered in this study reflect the policies currently adopted in the EU,namely the 2035 100%CO2 reduction targets for LDVs and the revised HDV CO2 standards,which mandate a 45%reduction by 2030,65%by 2035,and 90%by 204

90、0.31 We used ICCTs EV CHARGE model32 to quantify infrastructure needs for LDVs.This considers several factors when quantifying passenger car and light van charging 29 Statistical Data and Studies Department.(2023,November 16).Donnes sur le parc automobile franais au 1er janvier 2023.Ministres Amnage

91、ment du territoire Transition cologique.https:/www.statistiques.developpement-durable.gouv.fr/donnees-sur-le-parc-automobile-francais-au-1er-janvier-2023?rubrique=&dossier=1348 30 Braun,C.,Jin,L.&Miller,J.(2019).Roadmap Model Documentation.The International Council on Clean Transportation.https:/the

92、icct.github.io/roadmap-doc/.Forecasts were adjusted with Essonne-specific downscaling factors and data on EV fleet shares.31 More details about those projections can be found in the following report under Baseline Scenario:Sen,A.,Miller,J.,Hillman Alvarez,G.&Ferrini Rodrigues,P.(2023,November).Visio

93、n 2050:Strategies to align global road transport with well below 2C.https:/theicct.org/wp-content/uploads/2023/11/ID-22-%E2%80%93-1.5-C-strategies-report-A4-65005-v8.pdf 32 Schmidt,J.,Rajon Bernard,M.,Hillman Alvarez,G.,Sen,A.,Miller,J.&Jin,L.(2024).EV CHARGE v1.2 documentation(computer software).In

94、ternational Council on Clean Transportation.https:/theicct.github.io/EVCHARGE-doc/versions/v1.2/12|SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE REGULATORY ASSISTANCE PROJECT(RAP)infrastructure needs.These include charging access at home,work and depot,commuting behaviour,and housin

95、g types.The model then distributes the energy needs across home,workplace,public alternating current(AC),public direct current(DC)fast,and LCV depot chargers,taking the aforementioned factors into account,as highlighted in the publicly available model documentation.Highway charging is also included,

96、with the assumption that 5%of the eLDV fleet energy needs are recharged on highways.33 For HDVs,ICCTs HDV CHARGE model34 uses daily vehicle-kilometres travelled(VKT)distributions and charging patterns to allocate energy consumption to overnight,fast and ultra-fast chargers at depots or public locati

97、ons.Highway charging needs were calculated separately,based on annual average daily traffic data from the French road network.35 This includes VKT on autoroutes and national roads,using 2019 data.To isolate the effect of smart charging,no battery storage capacity other than that of EVs was modelled

98、on the distribution network EV fleet projected for 2040 For our analysis,we identified eight different EV fleets(named EV1-EV8,see below)to reflect the main types of use and charging patterns for both electric passenger cars and trucks.Four fleets are considered manageable,i.e.able to optimise their

99、 charging.These fleets represent use cases in which EVs are parked and connected for a longer time window,offering flexibility that can be exploited with smart charging:electric passenger cars charging at home,at work,those charging at normal speed in public,as well as electric trucks charging at th

100、e depot.Each fleet is defined by a charging type,a volume of energy,an average charging power level and specific arrival and departure curves(see Table 1).For details on how each fleet was mapped,see Table 5 in the Annex.33 Based on share of vehicle km driven on highways and drivers surveys,and the

101、assumption that EVs will predominantly charge at home and on highways only for longer trips.Details outlined in https:/theicct.org/publication/charging-infrastructure-to-support-the-electric-mobility-transition-%E2%80%AFin-france%E2%80%AF/34 Schmidt,J.,Egerstrom,N.,Hillman Alvarez,G.&Ragon,P.(2024).

102、HDV CHARGE v1.0 documentation(computer software).International Council on Clean Transportation.https:/theicct.github.io/HDVCHARGE-doc/versions/v1.0/35 Ministre de la Transition cologique.(2021,December).Trafic moyen journalier annuel sur le rseau routier national.Rpublique franaise.https:/www.data.g

103、ouv.fr/en/datasets/trafic-moyen-journalier-annuel-sur-le-reseau-routier-national/REGULATORY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|13 Table 1.EV fleet characteristics in 2040 Smart charging scenarios We define three scenarios:S1(low flexibility)and S2(h

104、igh flexibility)cover the range of the flexibility value that can be captured from smart charging.S1 represents a reference scenario for 2040 assuming 30%of smart charging is already developed,but 70%of charging is not being managed.Table 2.Smart charging scenarios Percentages correspond to the volu

105、me of energy needed to meet EVs mobility demand associated with each charging mode.14|SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE REGULATORY ASSISTANCE PROJECT(RAP)The high flexibility scenario S2 assumes that 90%of the energy comes from optimised charging.That means that 90%of th

106、e energy used for charging is charged at times when it is optimal for the grid within a flexibility window.A third scenario S3(vehicle-to-grid,V2G)builds on the high flexibility scenario S2 to explore additional benefits of V2G:it assumes that 10%of the overall energy used is by bidirectionally capa

107、ble EVs.Optimal times for charging are determined by grid characteristics and smart tariffs,discussed in the two following sections.Grid characteristics Most power systems in Europe face winter-driven peak demand due to early sunsets,low temperatures,and higher demand during the week compared to wee

108、kends.Since the grids are typically built to serve this peak,a steep or even moderate increase of this peak demand can result in significantly different network extension needs and associated grid costs.In European winter peaking systems,January or February evening peak load drives the annual grid e

109、xtension costs.Solar energy supply has a limited impact on reducing peak winter consumption:it can only help to reduce the demand at noon or in the evenings via storage to a limited extent,but not at both times,nor significantly.In this study,no battery storage capacity other than that of EVs was mo

110、delled on the distribution network.Compared to power networks in other European countries,the French networks are already built out for the heating demand,and overall need less reinforcement than average EU grids.That is explained by the specifics of the French system:the 2024 peak load was only abo

111、ut 82 GW,but it was above 100 GW a decade ago.36 This means that most of the time the French system has available grid capacity on the transmission and distribution levels,since the proportion of electrified heating demand is much higher in France than in other EU power networks.37,38 Even an increa

112、se of peak load on a line or substation does not result in an immediate need for grid extension,as might be the case in grids in other European countries which are prepared for less heating demand and are more congested.As a result,the recommendations in this case study are likely to apply to an eve

113、n greater degree in other EU countries.The next section discusses the underlying incentive to drive grid savings from smart charging that we assumed for this study:the availability of time-varying electricity tariffs,which are considered here as the main signal based on which consumers optimise thei

114、r charging.36 Veyrenc,T.(2015,September 28).The French capacity market design.Rseau de Transport dElectricit.https:/competition-policy.ec.europa.eu/document/download/5ace3816-89e2-419e-a6a8-8ca0656d2a67_en?filename=capacity_mechanisms_conference_2015_slides_veyrenc_en.pdf&prefLang=pl 37 Artelys cons

115、idered the electrical distribution network for these analyses by modelling the load changes on every high-voltage/mid-voltage transformer,mid-voltage power line,mid-voltage/low-voltage transformer/substation.For details,https:/ FfE(2020,June).Case study on final electricity consumption for space hea

116、ting in French private households and the danger of data misinterpretation.https:/www.ffe.de/veroeffentlichungen/case-study-on-final-electricity-consumption-for-space-heating-in-french-private-households-and-the-danger-of-data-misinterpretation/The availability of smart energy tariffs and services h

117、as almost tripled in recent years.See Burger,J.(2024).Imagine all the people:Strong growth in tariffs and services for demand-side flexibility in Europe.Regulatory Assistance Project.https:/www.raponline.org/toolkit/strong-growth-in-tariffs-and-services-for-demand-side-flexibility-in-europe/REGULATO

118、RY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|15 Smart charging tariffs To quantify the potential grid savings from smart EV charging,our model assumes that they are created by EV users aiming to save money by moving charging to cheaper hours.For modelling

119、purposes,we assume that a certain percentage(e.g.in S2,90%)of energy is charged into EVs based on a time-varying tariff,indicating hours when charging is cheaper.This implies that demand is highly responsive to these price signals.How these tariffs are set(opt-in,mandatory etc.)and the degree of aut

120、omation and support they offer(e.g.,through smart charging apps)is not in scope within this study.For the purposes of this study,we assumed a time-varying tariff for 2040 as depicted in Figure 3.Figure 3.Smart charging tariff assumed for 2040 Tariff on a weekday 16|SAVINGS FROM SMART CHARGING ELECTR

121、IC CARS AND TRUCKS IN EUROPE REGULATORY ASSISTANCE PROJECT(RAP)The tariff design is based on a literature review,39 and has two components:An energy price-based component(depicted in orange),built from French pre-energy-crises wholesale power day-ahead prices in 2019.A time-of-use(ToU)network fee(il

122、lustrated in blue).The price spread between low and high prices is modelled on already existing ToU network fee designs e.g.in Denmark,where the standard network tariff applying in low-usage times(i.e.nights)is three times cheaper than the peak tariff(i.e.early evenings).Experience suggests that the

123、se ToU network fees are a key tool to incentivise consumers to move consumption away from peaks.40 For both components,we conservatively kept the price differential between highest and lowest tariff rather moderate,making the scenarios more representative for other EU countries.In some markets today

124、 there are already wider price spreads,allowing for potentially higher savings.Based on Artelys net demand projections for 2040,two price peaks have been identified:7:009:00 and 18:0021:00.They only occur on weekdays.Both the energy and network price components combined form a price signal that ince

125、ntivises consumers to shift charging to cheaper hours.41 For simplicity,we assumed that all EV users use this tariff,and that they are fully reactive to these price signals in other words,that the projected share of smart-charging EVs forecast in Essonne in 2040 will adapt their charging to the patt

126、ern of the curve in Figure 3.Tariff assumptions for bidirectional EV charging(Scenario 3)Bidirectional(V2G)charging that is,discharging energy stored in EVs back into the grid at hours of peak demand can add additional grid savings.To reflect the potential additional benefits from bidirectional char

127、ging,analysis for S3(V2G)sought further optimisation of the observed consumption in S2.Thus,the impact of bidirectional charging discussed in this section is evaluated with regards to the S2 high flexibility scenario.We assumed that EVs discharge back into the grid at the most beneficial times and,a

128、s a result,flatten the remaining consumption peaks observed in S2 through bidirectional charging.To determine these times,we assumed the same price spreads as in S2,but moved on-peak prices to times in which EVs can address local grid constraints and act as a grid resource,rather than addressing the

129、 national grid situation as assumed for S1 and S2.We assumed that:39 Eicke,A.,Hirth,L.&Mhlenpfordt,J.(2024,March).Mehrwert dezentraler Flexibilitt.Neon Energy.https:/neon.energy/mehrwert-flex 40 Radius.(n.d.).Tariffer og netabonnement.https:/radiuselnet.dk/elnetkunder/tariffer-og-netabonnement/41 No

130、te that the study considers tariffs as input variables into the model to illustrate potential savings from smart charging of EV fleets in 2040.It does not aim at studying the design or cost-effectiveness of the assumed tariffs,nor whether the assumed design will be cost-neutral,nor how additional sy

131、stem savings will be distributed(see Limitations and further research section below).They do not reflect network investment costs nor wholesale power market scarcity prices.Further,since it can be considered that the tariffs cover the costs,the changes of load from smart charging are network cost sa

132、vings.REGULATORY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|17 The share of EVs connected to the grid in a V2G mode is set at 10%in 2040;this means,we assume that 10%of the EVs can charge the system if needed.This is slightly more ambitious than other natio

133、nal projections for V2G uptake in France,42 but allows us to explore the potential added value of V2G compared to classic one-directional smart charging.Network charges are varying more precisely along the regional network utilisation,not as a national year-ahead network tariff.The uptake rate of bi

134、directionally charging EVs is the same for the four manageable fleets.42 RTE foresees 3%in 2035 and 6%in 2050 in a median scenario;20%in 2050 in its highest flexibility scenario.Rseau de Transport dElectricit.(2022,February 16).Futurs nergtiques 2050:les scnarios de mix de production ltude permettan

135、t datteindre la neutralit carbone lhorizon 2050.https:/www.rte- 18|SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE REGULATORY ASSISTANCE PROJECT(RAP)Main findings Unmanaged EV charging will increase Essonnes peak load by 33%in 2040 Without smart EV charging in place(S1),peak load in t

136、he Essonne department is about 1,134 MW in 2024.As illustrated in Table 3 below,the peak demand modelled in this low flex scenario increases by one-third to 1,511 MW in 2040.Smart EV charging can reduce peak in Essonnes grid by up to 6%Optimised charging of the EV fleet based on price-based incentiv

137、es can reduce peak and therefore system costs.In S2(high flex),system peak only increases by one-quarter(25%)in 2040,compared to 33%in S1 with unmanaged charging.There is a 6%difference in peak load reduction between high flex and low flex scenarios.43 Table 3.Scenario results for peak load in 2040

138、Source:Lucas,C.Dil,M.,Quignon,L.(2025,March.)Savings from smart charging electric cars and trucks in Europe:A case study for France in 2040-Technical Report.43 Lucas,C.Dil,M.,Quignon,L.(2025,March.)Savings from smart charging electric cars and trucks in Europe:A case study for France in 2040-Technic

139、al Report.Artelys.https:/ REGULATORY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|19 Bidirectional charging can further reduce peak load by up to 9%Bidirectional EV charging can further reduce system peaks and therefore system costs.S3 modelling indicates tha

140、t with only 10%of all controllable EVs charging bidirectionally,a further 3%of the expected peak load can be saved,adding to savings from the high flex scenario.The peak load increase in 2040 compared to today is therefore lower than in S1 and S2,at only 21%or 1,374 MW.This illustrates the high pote

141、ntial of bidirectional charging to reduce network peaks and save grid investment costs.Smart EV charging can save up to 25%on network reinforcement costs in Essonne annually More efficient grid use from smart EV charging helps to avoid the need for grid investments.In our analysis for Essonne,summar

142、ised in Figure 4 below,we quantified the savings from avoided reinforcements of medium-voltage power lines and substations for the studied region.We estimated reinforcement costs against projected 2040 capacity needs;44 the savings are estimated based on network development plans projected by French

143、 DSO Enedis.45 In the high flexibility scenario(S2),the need for line reinforcements(in kilometres)is 23%lower than in the low flexibility scenario(S1).S2 allows for 37%less transformer reinforcements than S1.Overall,we estimate that the annual costs of network reinforcements expected through to 204

144、0 can be reduced to about 2.1 million per year in the high flex scenario(S2)compared to 2.8 million in the low flex scenario(S1),a potential saving of 25%per year.44 Methodology for line and substation reinforcement cost estimated documented in Artelys technical report:https:/ 45 ENEDIS Network Deve

145、lopment Plan,according to local requirements,considering its number of MV/LV transformers.ENEDIS.(2023).Plan de dveloppement de rseau.https:/www.enedis.fr/sites/default/files/documents/pdf/plan-de-developpement-de-reseau-document-preliminaire-2023.pdf 20|SAVINGS FROM SMART CHARGING ELECTRIC CARS AND

146、 TRUCKS IN EUROPE REGULATORY ASSISTANCE PROJECT(RAP)Figure 4.Grid reinforcement needs in low and high flex scenarios Source:Lucas,C.Dil,M.,Quignon,L.(2025,March.)Savings from smart charging electric cars and trucks in Europe:A case study for France in 2040-Technical Report.Figure 4 shows that,in bot

147、h scenarios,the need for reinforcement is generally below 10%as there is ample capacity on the grid.This is a specific characteristic of the French grid,due to its high share of direct electrified heating.Because of this electric heating demand,the demand and peak of the French power system correlat

148、e more closely to temperature than is the case in other EU power systems.The average grid utilisation therefore is lower and there will be less need for grid extension if utilisation increases(by smart EV charging)than in other,less temperature-related power systems.It is likely that the potential s

149、avings in other European systems would be significantly higher.All EV customer groups can contribute with their flexibility to achieve system benefits Our analysis reveals flexibility gains from smart charging in all studied areas,as the potential to shift charging from different fleets can be combi

150、ned.The right smart charging mix depends REGULATORY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|21 on which fleet is the most dominant by amount of energy and flexibility potential at a given location.In the next section,we discuss selected results from the

151、grid modelling focusing on high-load areas within the studied region.Based on load curves established for these selected areas close to highways,in commercial zones and residential areas within Essonne46 we can illustrate the impact of smart EV charging depending on which form of it is dominant.Resu

152、lts show that smart daytime workplace or depot charging of EVs can contribute to reduce system peaks,in addition to the better-known overnight charging of residential EVs.Moving residential EV charging to overnight is essential to reduce peak Findings illustrated in Figure 5(below)show that smart re

153、sidential charging is highly effective to reduce system peaks.In the low flex scenario in a residential area,EV charging mostly from privately-used passenger EVs contributes to a peak in the system after 6 p.m.This peak can be fully reduced by shifting the charging of that fleet(EV1)into overnight h

154、ours from 10 p.m.to 6 a.m.,which are the low-utilisation hours on the grid.These results confirm that classic smart residential charging will remain essential to reduce the costs of electrification for consumers and the grid for years to come.Measured by amount of energy and flexibility that can be

155、exploited,truck depot charging is the second-most relevant fleet to look at in the selected area.Figure 5.Smart residential charging Load curves in a residential area at the peak consumption in low flex and high flex scenarios.46 For areas,see Artelys technical background report,slide 42,and 52ff.ht

156、tps:/ 22|SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE REGULATORY ASSISTANCE PROJECT(RAP)Source:Lucas,C.Dil,M.,Quignon,L.(2025,March.)Savings from smart charging electric cars and trucks in Europe:A case study for France in 2040-Technical Report.Smart workplace charging helps reduce

157、 peak load in commercial areas Results from a business/commercial zone in the grid area illustrated in Figure 6 clearly show how smart workplace charging can reduce the load peak occurring between 9 a.m.and 12 noon.In the high flexibility scenario,this is mainly achieved by shifting the charging of

158、EVs at workplaces(EV2)into the early afternoon,using the time window these EVs have while parked at office buildings.In the business area analysed,peak load reduction was additionally supported by a smaller portion of residential smart charging,moving the charging of privately used EVs(EV1)away from

159、 the 9 a.m.to 12 noon time window into night hours,as described above.This highlights the fact that from a system point of view,it is essential to use the flexibility of all EVs,stacking flexibility from different EV fleets,e.g.workplace and residential.Figure 6.Smart workplace charging Load curves

160、in a business zone at the peak consumption in low flex and high flex scenarios Source:Lucas,C.Dil,M.,Quignon,L.(2025,March.)Savings from smart charging electric cars and trucks in Europe:A case study for France in 2040-Technical Report.Smart depot charging is essential to accommodate charging demand

161、 from electric trucks Optimised depot charging for trucks,similar to residential smart charging of passenger EVs described above,is an essential condition to ensure a maximum of truck charging happens overnight,and that truck charging doesnt cause avoidable costs to the system.Figure 7 below shows a

162、 highway station area.The system peak occurring in the low flex scenario around 6 p.m.is shifted by moving depot charging of trucks(EV 6)to overnight hours with REGULATORY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|23 lower grid capacity;as a consequence,le

163、ss charging is added to an already stressed system during the morning through to midday.The systems morning peak(9 a.m.to 12 noon),mainly caused by a higher share of truck highway charging,is also flattened,mostly thanks to the smart workplace charging of passenger EVs in the same area.This case sho

164、ws that in areas where truck charging is the largest stress on the grid,its even more important to fully use the optimisation of other fleets to avoid them adding to system peaks during the day.Figure 7.Highway charging Load curves in a highway station area at the peak consumption in low flex and hi

165、gh flex scenarios Source:Lucas,C.Dil,M.,Quignon,L.(2025,March.)Savings from smart charging electric cars and trucks in Europe:A case study for France in 2040-Technical Report.Taken together,the three examples show that to achieve the full potential of smart EV charging,all EV user groups need incent

166、ives to contribute their flexibility to the system:consumers who are flexible need to be incentivised to move charging to grid-optimal hours within their window of flexibility,to allow others who are not flexible to use the grid without adding to peak.Contrary to frequently voiced doubts,the load cu

167、rve effects in Figures 5,6 and 7 above show that ToU network fees do not create new peak loads.To ensure this remains the case,effective coordination of charging processes is needed between vehicles,or the actual charging power needs to be adjusted(as was done during the optimisation process)to avoi

168、d creating new peaks(e.g.,by starting all charging processes at full power at the beginning of an off-peak hour).24|SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE REGULATORY ASSISTANCE PROJECT(RAP)Limitations and further research The purpose of the study is to illustrate the potentia

169、l benefits of savings from optimised charging given supportive factors,e.g.the presence of time-varying network pricing,or savings from the grid relative to the expected grid investments needed in 2040.There are several limitations linked to this approach,discussed below:The study is explorative and

170、 does not attempt to identify the ideal design of such tariffs,nor offer an exact calculation of grid savings.However,the finding that a relatively simple ToU network fee design can already achieve significant load shifts indicates that our assumptions have captured the potential for optimisation we

171、ll.The extent of savings from smart EV charging will depend on conditions in 2040 that are unknown at the time of writing.The modelling does however give an estimate of savings if current projections are correct.Our analysis is illustrative of the beneficial effects in one specific grid.To the degre

172、e that it is representative,it is likely that smart EV charging will produce similar benefits in similar grids.Other costs associated with development of smart/bidirectional charging such as the cost of chargers,land-use cost etc.were not in the scope of the study.Savings from using EV flexibility c

173、an be used in a variety of ways which are beyond the scope of this analysis.Policy options include investments into grid costs,investments in improving the design of ToU network fees to lower electricity bills,and investments into smart and bidirectional charging applications.Conclusions and policy

174、recommendations Our study has illustrated how smart EV charging can shave peak loads in the grid and consequently reduce grid costs.In the Essonne grid,smart charging of a fleet of electric cars and trucks charging at home,at work,at public charging stations,at depots and on highways can reduce the

175、load peaks expected for 2040 by up to 6%.This would allow savings in network reinforcement costs in Essonne of up to 25%annually.Further,we show that bidirectional charging of EVs has additional benefits and can further reduce overall system peak by up to 9%,suggesting that further value from optimi

176、sation can be achieved through discharging when it is beneficial for the fleet and tailored to local grid constraints.Results show that smart EV charging is a collective task,and that flexibility from all types of EVs can be harvested to contribute to a reduction in system peaks.Analysis per EV flee

177、t shows how EV users relying on residential charging,workplace charging and depot truck charging can significantly reduce peak load in areas where the relevant type of charging is dominant.Peak load can be further reduced through a combination of optimised charging regimes from all fleets that repre

178、sent demand on the local system.REGULATORY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|25 A general conclusion is that in grids where peak demand drives grid build-out,all major types of EV charging that are manageable in particular residential charging,work

179、place charging and depot charging of trucks need to be optimised to help reduce peaks on the system in order to reduce system costs.A fundamental tool to incentivise all EV user groups to charge smartly is volumetric time-of-use(ToU)network fees which should be adjusted over time to match the actual

180、 grid utilisation,by location and time to signal to consumers when to shift their charging,and for their flexibility to be rewarded accordingly through cost savings.Also,from a network price perspective there are no savings to be gained when the system is stressed,so ToU volumetric network fees will

181、 be high at such times.While not yet widespread across EU Member States,network pricing reforms are underway in some countries:Denmark has introduced ToU network tariffs(see above);France will introduce a seasonal ToU system with an off-peak grid price during daytime hours in summer 2025;47 and the

182、Netherlands48 are discussing the introduction of time-varying network fees.Although this study did not investigate optimal tariff design(which could be a topic for an additional analysis),its results show that peak load could already be shifted substantially with a relatively simple ToU network tari

183、ff design with an average price-spread between off-peak and peak prices,assuming flexible demand is price-responsive.This suggests that with a more granular ToU,or with dynamic pricing of network use to be more cost-reflective of network conditions and adjusted over time and also by location,more sa

184、vings from smart EV charging could be achieved.49 Whats more,these are likely to be much more significant in other countries where networks are more constrained than in France.Our recommendations for policymakers,energy regulators and planners at EU and national level are as follows:Smart residentia

185、l charging and smart workplace charging for EVs,and depot charging for e-trucks,can make most impact on the system and should be the default mode of charging.47 Commission de Regulation de lEnergie.(2025).Annexe Communiqu de presse TURPE 7 Focus sur lvolution du placement des heures creuses.https:/w

186、ww.cre.fr/fileadmin/Documents/Communiques_de_presse/2025/250206_Annexe_CP_TURPE_7_HPHC.pdf 48 Bianchi,R.,Meijering,A.,Baks,S.&Wolda,J.(2024,October 21).Verkenning alternatief nettariefstelsel kleinverbruik.Netbeheer Nederland.https:/beheernederland.nl/publicatie/berenschot-verkenning-alternatief-net

187、tariefstelsel-kleinverbruik 49 For example,in Germanys new ToU network pricing system various grid operators aggregate to blocks.This diversification will likely help avoid power price-related peaks.FfE(2024,October).Variable Netzentgelte als Option fr steuerbare Verbrauchseinrichtungen nach 14a.htt

188、ps:/www.ffe.de/veroeffentlichungen/variable-netzentgelte-als-option-fuer-steuerbare-verbrauchseinrichtungen-nach-%C2%A714a/26|SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE REGULATORY ASSISTANCE PROJECT(RAP)Time-varying tariffs for energy,and in particular for networks,are the key to

189、ol to incentivise consumers to optimise charging.This is helped by a growing number of smart charging tariffs and services available for consumers in the EU.50 Expanding the availability of time-varying network pricing is a competence of national energy regulators and can be helped by Member States

190、ambitious implementation of energy market reforms,as the Agency for the Cooperation of Energy Regulators(ACER)recommends.51 To support the design and implementation of more cost-reflective tariffs,energy regulators could require more transparency on network use from distribution grid operators.Energ

191、y market regulation,e.g.following implementation of recent energy market reforms,should allow EVs to participate fully as flexibility resources in energy markets to generate value for customers through demand-response programmes,e.g.via smart tariffs and services.Grid and consumer-beneficial build-o

192、ut of charging infrastructure requires a balance between normal and fast charging:unless supported by local battery storage,fast charging of cars and trucks offers very little flexibility for smart charging,but charging at normal speed offers plenty.From a grid point of view,it is essential to optim

193、ise the types of charging where the EV spends longer connected to the grid,to help reduce system peak and to allow faster,higher-capacity charging to use grid capacity without adding to the peak.Smart depot charging is key to help reduce charging costs for fleet owners,and presents an important tool

194、 to facilitate the electrification of road freight.Incentives at a national level could include subsidies for depot electrification and targeted information for fleet/depot owners.52 On the energy market side,time-varying tariffs are key to increase benefits for fleet owners from smart depot chargin

195、g.To allow a more cost-efficient build-out of megawatt charging where needed,time-varying tariffs are equally important to support the business case for high-capacity charging of e-trucks along highways.53 Joint planning of charging infrastructure,in particular granular and systematic forecasting of

196、 charging demand from all EVs,is essential to keep grid upgrade costs in check and to ensure cost-efficient EV uptake.In conclusion,this study has illustrated how smart EV charging can shave peak loads in the grid and consequently reduce grid costs.By ensuring EVs are integrated into power grids cos

197、t-optimally,with savings for users,the grid and the environment,smart EV charging is a key tool to accelerate the electrification of road transport and the energy transition.50 Burger,2024.51 Agency for the Cooperation of Energy Regulators(ACER).(2023,January).Report on electricity transmission and

198、distribution tariff methodologies in Europe.https:/www.acer.europa.eu/sites/default/files/documents/Publications/ACER_electricity_network_tariff_report.pdf 52 Hildermeier,J.,Jahn,A.&Rodriguez,F.(2020,November).Electrifying city logistics in the European Union:Optimising charging saves costs.The Inte

199、rnational Council on Clean Transportation.https:/theicct.org/wp-content/uploads/2021/06/EU-city-logistics-FS-nov2020.pdf 53 Hildermeier,J.&Jahn,A.(2024,February 1).The power of moving loads:Cost analysis of megawatt charging in Europe.Regulatory Assistance Project.https:/www.raponline.org/knowledge-

200、center/power-moving-loads-cost-analysis-megawatt-charging-europe/REGULATORY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|27 Annex Mapping of different heavy-duty vehicle classes used in HDV CHARGE For the HDV sector,fleet projections using the ICCTs Roadmap m

201、odel are conducted at the VECTO group level,which is the official classification considered by the European Comission.For charging needs estimates with ICCTs HDV CHARGE model,several VECTO54 groups are aggregated into broader vehicle segments.Table 4 outlines this mapping.Table 4.Mapping from HDV CH

202、ARGE to Vecto groups Mapping EV1EV8 fleets to vehicle segment and charger setting combination in the charging models Table 5 illustrates the mapping of modeled charging energy needs across various charger settings for different fleets and how these are attributed to the eight distinct fleets(EV1EV8)

203、introduced in the section EV fleet projected for 2040.For light-duty vehicles(LDVs),charging is modeled separately for passenger cars(PCs)and light commercial vehicles(LCVs).For heavy-duty vehicles(HDVs),charging is modeled for the vehicle segments listed in Table 5.54 European Commission.(n.d.)Vehi

204、cle energy consumption calculation tool VECTO.https:/climate.ec.europa.eu/eu-action/transport/road-transport-reducing-co2-emissions-vehicles/vehicle-energy-consumption-calculation-tool-vecto_en 28|SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE REGULATORY ASSISTANCE PROJECT(RAP)Table

205、5.Mapping of modeled charging energy needs to fleets(EV1EV8)across charger settings REGULATORY ASSISTANCE PROJECT(RAP)SAVINGS FROM SMART CHARGING ELECTRIC CARS AND TRUCKS IN EUROPE|29 Projected eLDV and eHDV fleets This section provides an overview of the projected EV stock in Essonne,France,modeled

206、 with the ICCTs Roadmap model,separated into LDVs(Table 6)and HDVs(Table 7).Each table provides a breakdown of the EV stock across different segments within LDVs and HDVs.Table 6.Projected eLDV stock in Essonne,France,segmented by vehicle type and year Table 7.Projected eHDV stock in Essonne,France,

207、segmented by vehicle type and year International Council on Clean Transportation Fasanenstr.85 10623 Berlin +49 30233268-411 communicationstheicct.org www.theicct.org Regulatory Assistance Project(RAP)Belgium China Germany India United States Rue de la Science 23 B 1040 Brussels Belgium +32 2 789 3012 inforaponline.org raponline.org Regulatory Assistance Project(RAP).This work is licensed under a Creative Commons Attribution-NonCommercial License(CC BY-NC 4.0).