Report on Electric Vehicle Charging Trial
Prepared for Wellington Electricity By Jake Roos Consulting and Concept Consulting Final version - July 2018 Report on Electric Vehicle Charging Trial Final version - July 2018 7 8 5 7 17 13 16 16 10 19 14 16 11 12 ......
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Participant attitudes towards peak demand peak towards attitudes Participant Discussion Participants’ charging equipment and habits charging Participants’ Background and driving habits EVs Participants’ Acknowledgements Summary Executive management approaches 1.5.1 pricing electricity or time-of-use Demand-based 1.5.2 service control Centralised 1.5.3 grid to Vehicle 1.2.1 adopters’? ‘early participants Trial the EV Charging Are 0.2.1 Purpose 0.2.2 found What we
Contents 1.6 1.5 1.4 1.1 1.2 Section 1.0 data participant-provided of Analysis 0.2 0.1 Report on Electric Vehicle Charging Trial Final version - July 2018 3 34 36 35 37
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...... Customer A Customer analysis Percentile Terminology Appendix A Appendix or, analysis, Non-average look at individuals a closer 1.1 1.2 1.3 30 31 21 23 23 25 26 27 28 29 30 20 32 21 22 22 29 ......
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Conclusion Customer response to Time of Use signals Use Time of to response Customer Analysis Data validation Data Methodology 2.4.1 exposure price Spot 2.4.2 customers EV-Nite 2.4.3 pricing use time of of effect Overall 2.4.4 Power” “Hour of Kiwi Electric 2.3.4 model regression Linear 2.3.5 demand EV users Aggregate 2.3.6 research with international Comparison 2.3.1 comparison Simple before/after 2.3.2 curve Demand duration 2.3.3 period trading by Demand increase 2.1.1 approach and Purposes ection 2.0 ection
2.5 2.4 2.3 2.2 2.1 S usage data electricity of Analysis Contents Report on Electric Vehicle Charging Trial Final version - July 2018 4 36 28 29 30 30 31 32 35 36 12 14 15 27 27 ...... 1.0 Table trial participants by 2.0 or leased and model owned make Vehicle Table night tariff on a cheaper being not 3.0 for given Reasons Table 9pm EV after their charge don’t participants reason Main 15.0 Figure group in control demand per customer ICP day business winter Average 20.0 Figure customers and non-TOU TOU demand for EV 22.0 Figure customers and non-TOU TOU demand for EV 24.0 Figure a customer daily demand for Maximum 25.0 Figure with an EV individual consumers in P99 and P90 demand for Increase Tables 16.0 Figure EV customers for demand per customer ICP day business winter Average 17.0 Figure States EVs in the United for charging Weekday 18.0 Figure price the spot to exposed customers in demand for Change 19.0 Figure prices Use Time of to exposed customers in demand for Change 21.0 Figure demand customer Kiwi Electric 23.0 Figure customers multiple in demand for Increase 9 18 23 24 24 26 26 12 13 14 15 17 17 18 ......
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...... distribution the electricity into electricity feed to EV be used Grid) to (Vehicle times at key network Grid to Vehicle for EV be used 9pm EV after their charging system a centralised by be controlled EV charging their system a centralised by be controlled EV charging
13.0 Figure change in demand EV mean before/after Simple 14.0 Figure in demand EV increase modelled before/after regression Linear 11.0 Figure demand individual customer for curve Duration 12.0 Figure diversity for demand accounting individual customer for curve Duration 9.0 Figure their letting for expect would participants saving of Level 10.0 Figure demand with and without an EV Annual 8.0 Figure their letting of with the idea are participants comfortable How 7.0 Figure their letting for expect would participants saving of Level 5.0 Figure for reasons different to participants by given Importance 6.0 Figure letting of with the idea are participants comfortable How 2.0 Figure participants by EV reported first their of uses of Frequency 3.0 Figure participants by EV reported first in their driven Daily distance 4.0 Figure EV at home first their charge to participants by used Equipment 1.0 Figure customers and non-TOU TOU EV demand for Figures Report on Electric Vehicle Charging Trial Final version - July 2018 5 collaboratively. We*, JRCL and Concept working and Concept working JRCL We*, collaboratively. the trial. for team the project were together This trial was commissioned and funded by commissionedThis trial was and funded by but it Electricity Lines (we*), Limited Wellington people many involving effort a collaborative was a common have of whom each and organisations, of adoption in seeing the large-scale interest succeed. in New Zealand electric (EVs) vehicles Roos Consulting Limited Jake employed We* co-ordination. project overall provide to (JRCL) Section has written 1 of this report. JRCL Concept Consulting to also employed We* have They data. the electricityanalyse usage Sectionwritten report. 2 of the The executive been written have summary and preamble 0.1 Acknowledgements Report on Electric Vehicle Charging Trial Final version - July 2018 6 Regional Council. Many thanks and and thanks Regional Council. Many find the results you we hope that and useful. of the trial interesting the People and Ecotricity, Flip Flip and Ecotricity, the People Wellington and Greater the Fleet Charge.Net.NZ, EV Talk magazine, magazine, Talk Charge.Net.NZ, EV and Central EV car dealerships to Paua retailers Motors, Gazley allowed us to adapt some of their some of their adapt allowed us to and those that material; reference the trial including helped promote Energy, who also provided the the who also provided Energy, the Electricity data; group control Association who Networks Nova, Powershop, Paua to the the to Paua Powershop, Nova, and especially Genesis People Contact Energy, Meridian Energy, Energy, Meridian Energy, Contact Flick Trustpower, Energy, Mercury Electric Kiwi, Ecotricity, Electric, without whose help it would not without whose help it would not been possible; the electricity have data: who provided retailers acknowledge everyone that that everyone acknowledge foremost and contributed, first part, took that owners the EV The project team would like to to would like team The project
7 Report on Electric Vehicle Charging Trial Final version - July 2018 Executive Summary Executive
Specifically these insights were intended to help we* update its EV-Nite tariff. tariff. its EV-Nite update help we* to intended Specifically these insights were As part of this, differences in electricity charging approaches approaches in electricity charging As partof this, differences other time-of- (and EV-Nite receiving are that owners between EV not, alsouse examined. pricing plans), and those were that were attitudes towards new approaches for managing EV charging demand, demand, charging managing EV for new approaches attitudes towards incentives. including pricing and other information-based The trial also undertook a questionnaire survey to try and examine try to The trial also survey undertook and examine a questionnaire rise gave that and habits of the EV-owners motivations the reasons, It included questions their electricity about demand profiles. their to households (useful data was obtained for 77 of these in total), and 77 obtained of these for households was and (useful data in total), in total). owning households (860 of non-EV group a control The objective of the EV Charging Trial was to better understand the the understand better to was Trial Charging of the EV The objective measure to data metering using half-hourly by scale of this challenge of EV-owning and timing of electricity demand of both a group the size and managed carefully, this extra demand might require costly network costly network demand might require this extra carefully, and managed influence that approaches and technology-based Pricing-based upgrades. network impact. any minimize will help to charging and timing of EV the rate plan for the demand for EV charging, the majority of which is be expected to to of which is be the majority expected charging, EV demand for the plan for is concern if not planned that There home. at owners EV private be done by There are predicted to be in excess of 64,000 electric vehicles (EVs) on the on the electric (EVs) vehicles of 64,000 be in excess to predicted are There fleet. vehicle 2% of the total EVs 2021, by approximately in New Zealand road and manage how to electricity network operators: for a new challenge present 0.2.1 Purpose 0.2 Report on Electric Vehicle Charging Trial Final version - July 2018 8
on off-peak charging that was provided to them. Of the participants that them. Of to the participants that provided was that charging on off-peak convenience was cited after 9pm, the most common reason charge didn’t than the absence of a price rather signal. barriers, and practical In the absence of an electricity price signal or other information-based In the absence of an electricity price signal or other information-based occur to when trial appears a significant proportion intervention, work – coinciding electricity with system participants home from get capacities typically having chargers despite peak.evening However, in (variety) diversity be material to appears there 4 kW, to of 2.5 meaning the after- of such charging, the start of and duration kW. 0.8 to of 0.5 be of the order to is likely kW impact diversity proportion a greater examined, customers of EV in the sample However, This is even midnight and beyond. – i.e. much later charge to appears the Given do so. to no electricity tariff incentive have when customers technology (i.e. group of the sample nature ‘unusual’ small, and potentially approaches about charging information that and the fact early-adopters), whether this would not possible it is infer to this sample, to provided was widely. more adopted are when EVs behaviour be typical of charging while that found the questionnaire to response of participants’ Analysis after 9pm of charging the behaviour of participants adopted said they 78% 10% did so after switching their EV, getting within a month of immediately then had point they that at it was which it can be inferred (from retailer electricity) and 7% did during the trial period, for a cheaper night rate guidance and practical the information to responding suggesting were they 0.2.2 found What we average increase materially will charging EV that found It was kWh 2,500 approximately electricity demand: By residential demand. residential of the average 35% per annum – roughly
2021
2020
increase from EV chraging from increase 35% 2019 EVs on the road in NZ by 2021 by in NZ EVs on the road
Average residental electricty demand electricty residental Average 64,000 2018 Report on Electric Vehicle Charging Trial Final version - July 2018 9
All the time Occasionally Seldom Never Long trips (e.g. holidays) Weekend excursions Local trips What is your first EV used for? 0 . Contracting 2
e the off-peak period. In particular, if all vehicles start charging start if all vehicles charging period. In particular, the off-peak period all the significant diversity the startat of the off-peak would be been observed charging EV with have benefits that than the lost, new peak the being to significantly greater leading network peak. peak demand could This additional becurrent of kW per 1.5 of the approximately – on top of 4kW per EV the order evening. 9pm on a cold winter’s demand at after-diversity customer peak demand of the current than greater This is considerably 2.25 peak periods. during current kW per customer approximately period) but 21:00 at (the start of the EV-Nite a sharp increase this would be the case. It is not clear why later. hours a few EV demand outside of the electricity system peak. the electricity demand outside of system EV peak a new coinciding with the start of create it may increases, In the short-term it has a beneficial effect in terms of moving moving of in terms a beneficial it has effect In the short-term customers by purchased as the number of EVs In the long-term, That said, the sample group with the EV-Nite tariff did not show show tariff did not with the EV-Nite said, the sample group That 0% igur 80% 60% 40% 20%
100% F exceedance on the low voltage (LV) networks (which typically have 50 ICPs). (which typically have networks (LV) the low voltage on exceedance comfortable with suggested trial participantsGenerally were approaches on the grid (which included demand-based of EVs managing the impact to electricity pricing, a centralised the timing of their EV’s service control to of financial although the level technology), grid to and vehicle charging, use these to important most was people. agreeing for them from benefit to effect, while the anytime of the diversity shows that In terms the analysis an significantly with increases peak demand of individual customers peak the sample), the after-diversity 4 kW for approximately (by EV kW). 0.8 kW to 0.5 the sample is significantly less (approximately for increase small is significant, relatively effect for This beneficial diversity even As such, unless TOU of 5 or so. of the order – i.e. of customers groups the start peak step-change at a new sharp, incentives for signals create capacity widespread not cause may uptake period, EV of the off-peak This customer response to tariffs is potentially a double-edged a potentially tariffs is to sword: response customer This ● ●
02:00 01:00
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e 0
1.0 0.8 0.6 0.4 0.2 Increase in demand (kW) demand in Increase igur Figure 1.0 Figure customers and non-TOU TOU EV demand for F (e.g. Flick customers). This difference is illustrated in Figure 1.0 below. 1.0 in Figure illustrated is This difference (e.g. customers). Flick (TOU) tariff signal charged their vehicles outside of the evening and morning and morning outside of the evening their vehicles tariff signal charged (TOU) EV-Nite those the we* exposed to for greatest was This effect peaks. those spot wholesale exposed also to significant for prices but was tariff, vehicles overnight even without an electricity tariff incentive (potentially (potentially an electricity without tariff incentive even overnight vehicles them as part of the study), a far provided was that the information due to a time-of-use exposed to who were consumers of EV proportion greater and cabin while the car is plugged-in in order to increase the vehicle range. the vehicle increase to while the car is plugged-inand cabin in order their in this study charged consumers of the EV many Notwithstanding that of the evening demand increase) was observed was profiles. in demand increase) demand of the evening winter in the EVs of be ‘pre-conditioning’ with associated to This is understood the battery up warming be driven, the car is to or so before the half-hour in – i.e. A material increase in demand in the morning peak (although half that half that peak in the morning in demand (although increase A material Report on Electric Vehicle Charging Trial Final version - July 2018
Section 1.0 Analysis of participant-provided data Prepared by Jake Roos Consulting Limited About Jake Roos Consulting Limited Jake Roos Consulting Limited (JRCL) is a provider of expert advice and assistance in the fields of sustainable energy and climate change mitigation, from policy development through to project delivery. Areas of expertise include energy markets, energy management, renewable energy, electric vehicles, Greenhouse gas emissions accounting (ISO-14064) and innovative community engagement. For more information see www.jakeroosconsulting.co.nz
Content © Copyright 2018 Jake Roos Consulting Limited All rights reserved. 10 Report on Electric Vehicle Charging Trial Final version - July 2018 11
an Have advanced (HHR) data)
were recruited. The recruited. were were inclusion criteria must: that participants eligible participants at least or lease Own one EV that they at home charge
Wellington Electricity catchment supply within Live 92 advice on the use of timers for charging if they did not already use use did not already if they charging for on the useadvice of timers on electricity on their views pricing and also surveyed were They one. and information EVs, for approaches other demand management also collected. habits was and charging about their EVs Participants were given information about the importance of off-peak about importance the information of off-peak given were Participants and practical off-peak charge on how to advice practical charging,
we* replaced EV-Nite with EVB, a new time a new time with EVB, EV-Nite replaced we* * 1 July 2018. from owners, EV of use tariff for catchment was obtained from an electricity retailer. an electricity retailer. obtained from was catchment For the control group, 24 months of anonymised HHR electricity months of anonymised HHR electricity 24 group, the control For domestic selection a random of 6,000 for consumption data Electricity supply in the Wellington electricity connections (ICPs) HHR datasets were successfully assembled from the data supplied supplied successfully data the assembled were from HHR datasets 77 the participants, of for the analysis. used and this was for Half hourly resolution (HHR) electricity data for the 24-month period period the 24-month for electricity data (HHR) hourly resolution Half homes sought from was the participant’s for 6 October 2017 to through companies Complete in total). different (twelve their electricity retailers The call for participants to sign up was promoted via Facebook groups, groups, via Facebook participants promoted sign up was The call for to Talk’ the ‘EV some electricity retailers, and advertisements, pages through dealerships. and two car initiative the Fleet’ the ‘Flip radio, news website, gave rise to their electricity demand profiles, and their attitudes and their attitudes their electricity rise demand profiles, to gave demand. charging managing EV for new approaches towards The trial also had the objective of gaining a greater understanding understanding a greater of gaining the objective The trial also had that and habits of the EV-owners motivations of the reasons, Differences in peak electricity demand between EV owners that were receiving receiving were that in peak owners electricity demand between EV Differences participants a cheaper get some (or other pricing option whereby EV-Nite also examined. not were night) and those are electricity at that for rate EV-owners and a control group of non-EV owners, to to owners, of non-EV group and a control EV-owners tariff*. EV-Nite Electricity’s Wellington to changes inform The objective of the trial was to better understand understand better to of the trial was The objective the peak electricity of households demand of both Background 1.1 Report on Electric Vehicle Charging Trial Final version - July 2018 12 All the time Occasionally Seldom Never
Long trips (e.g. holidays) Weekend excursions Local trips What is your first EV used for? What is your first EV used
0 . Contracting 2
e 0% igur 80% 60% 40% 20% 100%
F
The main uses of the participant’s first EV were for local local for were EV first The main uses of the participant’s trips 2.0. and commuting, as shown in Figure 2.0 Figure participants by EV reported first their of uses of Frequency 02:00
2 3 4 6 11 72 01:00
98
No.
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07:00
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05:00 04:00 TOU tarriff participants, 85 had one EV, 6 had 6 had participants, one EV, 85 had
1 0 . 03:00
1
e
0
0.8 0.6 0.4 0.2 1.0 Increase in demand (kW) demand in Increase igur
F Other Total Nissan Leaf Mitsubishi Outlander PHEV Electric Van Nissan E-NV200 Hyundai Ioniq A3 SportbackAudi E-Tron Make and model Make Table 1.0 Table trial participants by or leased owned and model make Vehicle 1. 92 eligible people registered from the trial. Usable electricity from 1. 92 eligible people registered these. 77 of for obtained was data consumption
participants are shown in Table 1.0. shown in Table participants are no internal combustion engine vehicles. no internal types owned of EV or leased by The breakdown two EVs and one participant owned three and one participant owned three EVs two 32% of participating households owned EVs. and driving habits driving and Of the 92 Participants’ EVs Participants’ 1.2 Report on Electric Vehicle Charging Trial Final version - July 2018 13
Other
(Charging box) Dedicated EVSE socket 15A caravan Type of equipment used at home to charge first EV Type of equipment used 0 . 3-pin socket Standard 8A 4
e ), many of recent purchasers do not completely fit the definition. do not completely purchasers of recent ), many 0% 2 igur 50% 40% 10% 60% 30% 20% F
Diffusion of Innovations (1962). ‘Innovators’ and ‘early adopters’ adopters’ and ‘early ‘Innovators’ (1962). Diffusion of Innovations 15% the first bell-curve adoption in the technology represent in this case EVs. of people a technology, who adopt to definition, tend the formal to according adopters, Early allow them its supplier that to on a product feedback give service of systems or the associated product the refine to a product, for and more and support. pay to often They have of the with early versions deal with bugs associated to have tax’. adopter as the ‘early to product, sometimes referred fleet up much less in than 1% of the light vehicle make As EVs all of the participants trial couldNew Zealand, in the be considered especially itself as this trial is a means of gathering early adopters, and of support’ charging (home EV system on a ‘associated feedback price the given However, for. volunteered have its pricing) they that significantly and has reduced particularly the Nissan Leaf, of EVs, (The Nissan Leaf faults to not prone are that products mature are they Consumer conducted by car in a survey most reliable NZ’s rated was NZ 1.2.1 Trial the EV Charging Are adopters’? ‘early participants M. Rogers’ Everett adopter’ from originates ‘early The term 2. https://www.consumer.org.nz/articles/car-reliability 2. https://www.consumer.org.nz/articles/car-reliability
>1838 135,138
125,135
115,125
105,115
95,105
85,95
75,85
65,75
55,65 45,55
Bands of average daily distance driven (km) 35,35
How far do you drive this EV in a typical day? How far do you drive this
25,35 15,25
5,15 0 . 3
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8 6 4 2 0
16 14 12 10 Number of participants of Number igur F Figure 3.0 Figure participants by EV reported first in their driven Daily distance 41% of participants have owned their EV for 6 months or less. 6 months for owned their EV of participants41% have
on a typical day. The distribution of the estimated average daily daily average of the estimated The distribution day. on a typical 3.0. is shown in Figure EV the first in distance driven 49% of participants drive their EV an average of 40km/day or less less or of 40km/day an average of participants49% their EV drive Report on Electric Vehicle Charging Trial Final version - July 2018 14
2 2 2 3 5 5
No. of respondents No. of
Reason stay to Not worth effort/cheaper retailer with current switching are switch/presently Going to supplier current to Loyal this offered anyone Unaware learn more to the benefits/need of Unsure Other Table 2.0 Table night tariff on a cheaper being not for given Reasons data found that 50% of participants had their peak electrical demand between participants 50% of that their peak electrical had demand between found data between these times. charging 9pm and 7am, highly suggestive of EV then, but their early It is possible also charging other participants were their highest, still peak was evening related because of other non-EV of participants’ a significant proportion Interestingly, their home. demand at profiles. with their load did not match charging claimed timing of their EV’s Of those not on such a tariff, their reasons are given in Table 2.0. in Table given are their reasons Of those not on such a tariff, (PHEVs) EVs hybrid some participants Outlander plug-in with Mitsubishi Also, their from so switching little charging, relatively required their vehicles noted deals would not be beneficial. financially existing after 9pm, and a their EV charged 31% of participants always claimed they of electricityfurther consumption usually did this. Analysis said they 49% Other (Charging box)
Dedicated EVSE socket 15A caravan Type of equipment used at home to charge first EV Type of equipment used at home to charge first 0 . 3-pin socket Standard 8A 4
e
0% igur 10% 50% 40% 30% 20% 60% F
Figure 4.0 Figure EV at home first their charge to participants by used Equipment
EV-Nite, and including these, 63% are on a home electricity on a home electricity 63% and including these, are EV-Nite, is cheaper betweensupply option that 9pm and 7am. 26% of participants are on an electricity tariff incorporating on an electricity tariff incorporating of participants26% are by participants is given in Figure 4.0. Over half are using using half are Over 4.0. participants in Figure by is given 8A household plug. a standard equipment and habits and equipment equipment used charging EV of home The breakdown Participants’ charging Participants’ 1.4
>1838
135,138
125,135
115,125
105,115
95,105
85,95
75,85
65,75
55,65 45,55
Bands of average daily distance driven (km) 35,35
How far do you drive this EV in a typical day?
25,35
15,25 5,15 0 . 3
e
8 6 4 2 0
16 14 12 10 Number of participants of Number igur F Report on Electric Vehicle Charging Trial Final version - July 2018 15 1 2 4 0 12
Very
No. of respondents No. of uncomfortable Uncomfortable Neutral Comfortable you be with the described arrangement? Centralised control service: How comfortable would Centralised control service: How comfortable 0 Very . 6
comfortable e 0% 50% igur 40% 30% 20% 10% F Reason barriers practical are It is inconvenient/there (no cost me to saving) no difference Makes charging daytime home solar PV so prefer Have a difference it made not aware I was it yet, to around got I haven’t do this to but I intend Table 3.0 Table 9pm EV after their charge don’t participants Main reason included participants barriers later needing usePractical the EV to the car a boost needing give charge to therefore (and in the evening programme during the 5 – 9pm peak period) how to and understanding is Japanese. language console’s their vehicle given their charger, the main reason given why in Table 3.0. in Table why given the main reason Of the participants who always or usually charged after 9pm, 78% said said after 9pm, 78% usually charged or Of the participants always who 10% their EV, started a month of getting or within they this immediately Trial Charging 7% during the EV electricity switched suppliers, when they some other time. at and 5% their EV) after than a month getting (but more after 9pm, their EV Of the participants not charge did that
Very important Important Unimportant Very unimportant for me It is more convenient Better for the electricity grid (avoids adding to peak demand) environment Better for the If you usually charge your EV after 9pm, please rate the importance to you of reasons why please rate the importance to you of reasons
price for after 9pm electricity 0 Get a cheaper . 5
e 0 40% 30% 20% 10% 70% 60% 50% Figure 5.0 Figure different to participants by given Importance 9pm EV after their charging for reasons igur F by 57% and 49% of participants respectively. See Figure 5.0. See Figure 49% of participants and respectively. 57% by 9pm’ was rated as ‘very important’ by 66% of participants. ‘Better for as ‘very important’ of participants. 66% rated by was ‘Better for 9pm’ as ‘important’ rated were the environment’ electricity ‘Better for grid’ and timer of some kind to control when home charging starts. charging when home control timer of some kind to rate to asked after were 9pm their EV charge did that Participants a cheaper price after ‘Getting reasons. the importance of different Two thirds of participants said they always or usually used an automatic used or usually automatic an participants of always said they thirds Two Report on Electric Vehicle Charging Trial Final version - July 2018 16
Rather than relying on electricity users to make their own their own make on electricity to users than relying Rather arrangements to control the timing of EV charging and other other and charging the timing of EV control to arrangements electricity supplier peak demand, your manage to load flexible you. could for do this potentially or distribution company and duration is collected on the typical size if data Furthermore, your the amount of time it usually takes example, (for of loads electricity usecould across be co-ordinated charge) to EV in demand. It is likely peaks large a neighbourhood avoid to electricity to financial advantage be would an additional there them to for and a means this approach, to who agreed users necessary.” time if it was time to from the control override “ be with this arrangement’, ‘how comfortable would you When asked or ‘very comfortable‘. would be ‘comfortable’ said they 70% or ‘very uncomfortable’. would be ‘uncomfortable’ said they 18% 1.5.2 service control Centralised and services charging EV Centralised control for participants: to this way explained was other load
arrangements where load would have to be carefully managed to minimise costs. to managed be carefully to would have load where arrangements Electricity pricing options for EV owners that are presently available generally generally available presently are that owners EV Electricity pricing options for this question the no downside price-wise. The responses to shows that have pricing sophisticated more for appetite has considerable participant group overall depending on when you timed certain activities timed certain depending on when you activities overall it?” to consider switching you would charging) EV like electricity price at certain times of the day, but more expensive expensive but more electricity certain price at times day, of the or less more cost you it may (so other times of the day at 89% of participants responded yes to the following question: the following 89% of participants to yes responded a cheaper electricity supplier offered current “If your 1.5.1 pricing electricity or time-of-use Demand-based towards peak demand peak towards approaches management Participant attitudes Participant 1.5 Very uncomfortable Uncomfortable Neutral with the described arrangement? Comfortable Vehicle to grid: How comfortable would you be Vehicle to grid: How comfortable 0 Very . 8
comfortable e 5% 0% igur 30% 35% 30% 25% 20% 15% 10% F
Report on Electric Vehicle Charging Trial Final version - July 2018 17 No level of cost saving me to do this would persuade $40+
$20-$40 $10-$20 $0-$10 $0 you to take up an arrangement like the one described? you to take up an arrangement saving on your monthly electricity bill that would motivate saving on your monthly Centralised control service: What is the mimimum level of Centralised control service: 0 (would do it for free) . 7
e
5% 0% 25% 20% 15% 10% igur F
Figure 7.0Figure letting for expect would participants saving of Level service a centralised by be controlled EV charging their Electric vehicles could potentially be set up to feed power back could powerElectric be back feed potentially vehicles set up to Owners of these vehicles would get a payment or reward of of or reward a payment Owners of these get would vehicles could this, mean the vehicle allowing as it would some kind for recharge. to longer not be these used at times take and would if the set-up the choice of overriding have would The owner be would less as a result.” payment but their neededthey to, into the grid at critical times to help manage peak demand. peak demand. help manage critical times to the grid at into 1.5.3 grid to Vehicle participants: to this way explained was grid technology to Vehicle “ Very
uncomfortable Uncomfortable Neutral Comfortable you be with the described arrangement? you be with the described Centralised control service: How comfortable would Centralised control service: 0 Very . 6
comfortable e
0% 50% igur 10% 40% 30% 20% F their EV charging be controlled by a centralised service a centralised by be controlled EV charging their Figure 6.0Figure lettingof idea with the are participants comfortable How would expect to enter into such an arrangement is given in Figure 7.0. in Figure is given such an arrangement into enter to would expect 93% of the people that said they would be uncomfortable or very be would uncomfortable93% of the people said they or very that home all electricity of my use at full control ‘I want uncomfortable gave participants of financial advantage The level as the reason. all times’ at
Very important Important Unimportant Very unimportant for me It is more convenient Better for the electricity grid (avoids adding to peak demand) environment Better for the If you usually charge your EV after 9pm, If you usually charge your please rate the importance to you of reasons why please rate the importance price for after 9pm electricity 0 Get a cheaper . 5
e 0 70% 60% 50% 40% 30% 20% 10% igur F Control Group Without EV With EV 0 10.
e 0 igur
8,000 6,000 4,000 2,000
F 12,000 10,000 Annual demand (kW) demand Annual
Report on Electric Vehicle Charging Trial Final version - July 2018 18
No level of cost saving me to do this would persuade $200+ $100-$200 $60-$100 $20-$60 $0-$20 $0 0 would motivate you to take up the described arrangement? would motivate you to take . Vehicle to grid: What is the mimimum monthly payment that Vehicle to grid: What is 9 (would do it for free)
e 5% 0% 25% 20% 15% 10% igur F Figure 9.0Figure letting for expect would participants saving of Level Grid to Vehicle for used EV be their The level of financial advantage participants would expect to enter into into participants enter to expect would advantage of financial The level below. 9.0 Figure in is given such an arrangement Very uncomfortable Uncomfortable Neutral with the described arrangement? Comfortable Vehicle to grid: How comfortable would you be Vehicle to grid: How comfortable 0 Very . 8
comfortable e
5% 0% igur 30% 35% 30% 25% 20% 15% 10% F distribution network at key times (Vehicle to Grid) to (Vehicle times at key network distribution Figure 8.0Figure letting of with the idea are participants comfortable How the electricity into electricity feed to used EV be their 52% ranked ‘it would be inconvenient’ as their top reason, while 39% while 39% reason, as their top would be ‘it inconvenient’ ranked 52% reason. EV’ as their top of my ‘it might shorten life the battery ranked Of those that said they would be uncomfortable or very uncomfortable, Of would be uncomfortable those said they or very uncomfortable, that they would be ‘comfortable’ or ‘very comfortable‘. 31% said they would be would be they 31% said ‘very or comfortable‘. be would ‘comfortable’ they 8.0. See Figure ‘very or uncomfortable’. ‘uncomfortable’ When asked ‘how comfortable would you be with this arrangement’, 63% said 63% said be this arrangement’, with comfortable ‘how you would asked When No level of cost saving me to do this would persuade $40+ $20-$40 $10-$20 $0-$10 $0 you to take up an arrangement like the one described? you to take up an arrangement saving on your monthly electricity bill that would motivate saving on your monthly Centralised control service: What is the mimimum level of Centralised control service: 0 (would do it for free) . 7
e 5% 0% 25% 20% 15% 10% igur F Report on Electric Vehicle Charging Trial Final version - July 2018 19
Registered EVs in NZ EVs Registered the trial at the time of 5,500
EV charging will increase slightly compared to what has been measured has been what measured to slightly compared will increase charging EV ratings. higher current have formats the other charging in this trial, given standard 8A domestic wall socket. WorksafeNZ guidance discourages the guidance discourages the 8A domestic socket. wall WorksafeNZ standard as that It could be leads. expected charging EV for use of this plug format peak power for demand these become leads less common, the average to work with to further develop such systems and products. such systems further work with to to develop with a their EV half of participants charge over It should be that noted timing and vehicle to grid technology were all high, with some all high, with some were grid technology to timing and vehicle It suggests people use no financial reward. these willing to for owners EV in current a willing group the electricity sector have Interest/comfort amongst the participant group for pricing pricing for amongst the participant group Interest/comfort of charge centralised control demand charges, incorporating response to advice and practical guidance would suggest public guidance suggest would and practical advice to public response influencing charging for could be that employed tool is a education alongside price based and technology measures. behaviours, However, the fact a small but significant proportion of participants of participants a small but significant proportion the fact However, after started 9pm doing so in charge who did not already clear signals regarding this). Therefore the finding that most participants most participants the finding that this). Therefore clear signals regarding peak would not necessarily evening traditional outside the charge already widely adopted. more are once EVs large at the population apply to charging. (It should be noted that Flick Electric, who supplied 20 of the who supplied 20 of the Electric, Flick (It should be that noted charging. on the emissions information real-time participants in the trial provides especially this group give which would of grid-supplied electricity, intensity expected that they are more conscious of environmental issues given their their issues given conscious of environmental more are they that expected conscientious about charging be more may and thereby in EVs interest night, at with emissions associated gas later minimise the greenhouse to of what is currently an exclusive group, there being around 5,500 registered registered 5,500 being around there group, an exclusive is currently of what conducted. It could be the time the trial was at in New Zealand EVs Discussion part are they in that exceptional somewhat The participants the trial are in 1.6 Report on Electric Vehicle Charging Trial Final version - July 2018
Prepared by Concept Consulting Concept Consulting Group Ltd (Concept) specialises in providing analysis and advice on energy-related issues. Since its formation in 1999, the firm’s personnel have advised clients in New Zealand, Australia, the wider Asia-Pacific region and Europe. Clients have included energy users, regulators, energy suppliers, governments, and international agencies. Concept has undertaken a wide range of assignments, providing Section 2.0 advice on market design and development issues, forecasting services, technical evaluations, regulatory analysis, and expert evidence. Analysis of electricity usage data Further information about Concept can be found at concept.co.nz
Disclaimer While Concept has used its best professional judgement in compiling this report section, Concept and its staff shall not, and do not, accept any liability for errors or omissions in this report or for any consequences of reliance on its content, conclusions or any material, correspondence of any form or discussions, arising out of or associated with its preparation. No part of this report section may be published without prior written approval of Concept. Content © Copyright 2018 Concept Consulting Group All rights reserved. 20 Report on Electric Vehicle Charging Trial Final version - July 2018 21
in demand that results from an EV. from results in demand that difference years for most customers, and most customers have have and most customers most customers, for years less time than that. for been using their EV and after starts the customer using an EV. Electricity data was provided for the previous two two the previous for provided was Electricity data before demand can be examined This means that
well because charging an EV is a substantial increase in demand. is a substantial increase EV an well because charging In addition to data from EV customers, data was received from from received was data customers, EV from data to In addition from The data without an EV. number of customers a large help to group” served as a “control an EV without customers establish the available isn’t data metered is that in this process challenge A key are as most EVs charging, electricity used EV specificallyfor for Therefore, demand. household’s as a part of the entire metered from be inferred to has had charging EV the electricity used for techniques. using mathematical household demand data the total customers on directly focussed The majority of the analysis comparing them with themselves: by with an EV ● ● changes in electricity demand to things might contribute Although many customers, different many at looks the analysis customer, single any for also works This process out”. so the individual changes mostly “cancel
tariffs behave differently to others. to differently tariffs behave for how long, use. much powerfor and how do they In particular, do customers on Time of Use (TOU) on Time of Use (TOU) do customers In particular, In particular, what time of day do they start charging, start do they charging, time of day what In particular,
● ● How this might change in response to price signals. price to might change in response this How How and when customers charge their EVs their charge and when customers How it specifies how much electricity is used in each 30-minute it specifies how much electricity is used 30-minute in each the period for of a trading This is the length day. block of each wholesale available. market, data is the highest and resolution challenges, including considerable effort acquiring and processing and processing effort acquiring challenges, including considerable it. who provided retailers different the eleven from the data is, – that “half-hourly” The electricity was consumption data model, to enable EV charging patterns to be discerned. to patterns charging EV enable model, to a number of other data overcome to also had The exercise Given the relatively limited data set, and the fact that EV charging charging set, data limited EV that and the fact the relatively Given had techniques have mathematical metered, is separately of a linear regression be used,to including the development results of a customer survey that included information such as such as included information that survey of a customer results use. tariff they retail and what their EV, drive how often they This analysis was based on half-hourly data from 77 EV-owning 77 EV-owning from data based was on half-hourly This analysis network, and the (we*) Electricity’s in Wellington customers 2. This study is focussed on answering two broad questions: on answering two broad This study is focussed 1. 2.1.1 and approach Purposes Methodology 2.1 Report on Electric Vehicle Charging Trial Final version - July 2018 22 for how long, use. much powerfor and how do they others. to differently tariffs behave In particular, what time of day do they start charging, start do they charging, time of day what In particular, on Time of Use (TOU) do customers In particular,
● ● How and when customers charge their EVs their charge and when customers How signals. price to might change in response this How 1. 2. at by looking addressed was question The first and comparing users, their demand before EV startedand after they using their EV. Electricity demand is highly seasonal, and the the period the end of up to for set was data which an approach means that That winter. electricity how changed demand at simply looked might incorrectly an EV, got when customers charging. demand as EV winter extra perceive 2.3 Analysis questions: two broad answer to attempts The analysis
net demand was metered – it is simplest to ignore any electricity exports. any – it is simplest ignore to metered net demand was coincided questionnaires with a noticeable the customer from using an EV for necessary but where the case, this was in demand. Generally, increase in demand. the observed match increase to adjusted the start was date due to solar PV at their properties. This means that instead of importing of importing instead their properties. solar This means that at PV due to the exporting it. the local were power grid, they electricity For from complicates generation Local zero. set to were values negative any analysis, when modelling demand. for accounted and should be properly analysis, - only the available not directly was on generation since data However, be useful to look at differences between different types of meters or or types of meters between different differences be look useful at to was unclear which meter difficult because it was but this was registries, an ICP at doing the analysis for reason the main Ultimately, which type. splitting meant that because the small number was customers of level in very small sample sizes. type further would result meter the data into retailer continue to supply data, leading to multiple series for the the multiple series to for leading supply data, continue to retailer be identified to and removed. had Duplicates same customer. It might an ICP level. at aggregated was deal with this, demand To time. to be a standard electricity consumption format, many retailers used used electricity consumption format, retailers be a standard many to types. was The data fields and formatting with different their own format a single format, into table. and combined one database into standardized The demand data was also “eyeballed” to determine if the reported start date start if the reported determine date to also “eyeballed” was The demand data Some customers had net negative electricity demand at times – presumably times electricity demand at – presumably net negative had Some customers When a customer switches retailer, often both the new and old often both the new and old switches retailer, When a customer over ICP can change an at registries or The number and type of meters Different data formats from 11 different retailers. Although there appears appears there Although retailers. 11 different from formats data Different
● ● ● ● ● meant that a large amount of effort was required to convert the supplied data convert the supplied data to required was of effort amount a large meant that issues and processes included: validation data Key a useable form. into Half-hourly data was received from electricity retailers. Each retailer is required is required retailer Each electricity retailers. from received was data Half-hourly In when requested. customer each for two years the previous for data supply to complications but various process, bean ideal world, this would a straightforward Data validation Data 2.2 Report on Electric Vehicle Charging Trial Final version - July 2018 23
demand for all customers combined. This is also combined. This is also all customers demand for demand. known as the “after-diversity” The duration curve of demand for individual customers. curve for of demand The duration per-customer curve of average The duration
shows the top 1% of the curve, as this is of particular interest. as this is of particular 1% of the curve, interest. shows the top annual distance travelled of 13,900 km. This is consistent with MoT with MoT km. This is consistent of 13,900 annual distance travelled vehicles. light private by distance annual travelled on the average data 2.3.2 curve Demand duration Such curve”. “duration demand is with a look at to Another way from demand values all the individual half-hour a curve orders smallest. to of visualizing the peak largest good This is a way in between. percentiles demand, minimum demand, and all the two perspectives: from at looked This was ● ● individual curve from duration shows the demand 11.0 Figure point on the graph Each with and without an EV. customers so the ICP, a single for reading a single half-hour represents as well as time, through is showing both the variability graph within the main graph The graph between ICPs. the variability Average demand per customer increased by roughly 33% after after 33% roughly by increased per demand customer Average an kWh, and assuming 2,500 approximately At an EV. acquiring kWh/km, an to this corresponds of 0.18 fuel efficiency EV average
.
Control Group from customers who who customers from 3 Without EV even when they didn’t have an EV have didn’t when they even With EV 0 10.
e
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4,000 2,000 8,000 6,000
F 12,000 10,000 (kW) demand Annual
Figure 10.0 Figure demand with and without an EV Annual EV is different from normal. This may be because EV customers are are customers be because EV normal. This may from is different EV households. larger have or perhaps they that wealthier than average, (Control group) is shown, which indicates that customers with an EV used used with an EV customers that indicates is shown, which group) (Control group, than the control energy more household the typical with an that This is not surprising, and reflects purchased an EV, both after they acquired their EV (With EV), and before and before (With EV), their EV both acquired after they an EV, purchased an EV have who don’t the customers from data Equivalent (Without EV). from the corresponding month in previous years. It was assumed that assumed that It was years. previous month in the corresponding from than a seasonal effect. rather charging, EV to is due this difference demand annual estimated shows the 10.0 Figure Simple before/after comparison before/after Simple in demand increase the look at is to deal with this to The simplest way 2.3.1 months so may not accurately reflect a full year’s worth of demand. of worth a full year’s reflect accurately not may months so 3. This is extrapolated from daily demand data, which includes more winter more includes which daily demand data, from extrapolated is 3. This No level of cost saving me to do this would persuade $200+ $100-$200 $60-$100 $20-$60 $0-$20 $0 0 would motivate you to take up the described arrangement? . Vehicle to grid: What is the mimimum monthly payment that Vehicle to grid: What is the mimimum monthly 9 (would do it for free)
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5
99.1%
3% 99.1% 3%
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3.5 3.0 2.5 2.0 76% Without EV 76%
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0
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igur
igur Average customer demand (kW) demand customer Average F (kW) demand customer Average F basis. i.e. the average increase across all customers all customers across increase the average basis. i.e. Duration curve for individual customer demand accounting for diversity for accounting demand individual customer for curve Duration Figure 12.0 Figure
percentile the point on the x-axis that corresponds to 99%). to corresponds that the point on the x-axis percentile in the timing of is significant diversity there This shows that customers. occurs between different when charging Whereas Figure 11.0 previously showed the increase in individual in individual showed the increase previously 11.0 Figure Whereas Figure 4kW, be approximately to is likely EVs AMD due to customer in shows the increase 12.0 the 99 kW (at 0.5 be approximately to is likely EVs ICP due to Figure 12.0 shows the duration curve analysis on an on an curve analysis the duration shows 12.0 Figure diversity a per-ICP on basis. – but expressed with an EV 5. This graph only includes data for September 2016 compared with September 2016 compared September for data only includes graph 5. This data. available month with the most is this because is 2017. This
99.1%
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72% 2 0 72% 8 6 4
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16 14 12 10 76% Without EV 76%
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igur igur (kW) demand Individual Individual demand (kW) demand Individual F F Figure 11.0 Figure demand customer individual for curve Duration 4. Which results in the overall increase of 33% shown earlier. 33% shown of increase in the overall results 4. Which This means that not only is average annual demand higher for EV customers, customers, EV higher for annual demand not only is average This means that it is also significantly peakier on an but the increase is proportionally lower the further down the curve. For lower the further is proportionally For down the curve. but the increase and demand in the middle of the curve is about 30% higher, example, the lowest partfor curve of the the demand is essentially the same can be more than 10 times the average for all customers. all customers. for than 10 times average the can be more increases customers individual EV On this AMD basis, peak demand for curve, the entire Demand is higher for or about 45%. about 4kW, by This graph shows the ‘peakiness’ of residential demand on an individual demand on an individual of residential shows the ‘peakiness’ This graph a customer by maximum demand (AMD) basis. Anytime customer
Report on Electric Vehicle Charging Trial Final version - July 2018 25
an after-diversity basis is appropriate to consider the impacts of of consider the impacts to basis is appropriate an after-diversity that given network level, LV the individual at – even demand EV 50 customers. approximately have typically such networks 2.3.3 period trading by Demand increase in demand the increase is when during the day consideration A key down broken in demand, shows the mean increase 13.0 occurs. Figure starts 3am, and not midnight. at the x-axis period. that Note trading by 11pm, and at dramatically demand increases The additional demand until 1am. Then the additional continues increase to also a small increase the night. through decreases There’s 7pm). peak 6:30pm to evening during the traditional their EV starting charge with mostThis is consistent customers to fully are EVs off as the after then drops 11pm. Demand increases, during is a small increase There power. drawing so stop charged plug in 7pm), as some customers to peak (6:30pm the traditional periods. until off-peak than waiting rather home, get when they There is insufficient data from this current Wellington Electricity study Electricity study Wellington current this from data is insufficient There effect the diversity of how analysis this Orion meaningfullyto replicate the number changes with of consumers. with EVs customers for and 11.0 basedFigure shown in on the analysis However, that it is considered 1.0, shown in Box and the data 12.0, Figure 6. ADMD = “After-diversity maximum demand” maximum 6. ADMD = “After-diversity
6
1.11 1.11 1.17 1.12 1.12 1.13 1.13 1.18 1.15 1.14 1.14 1.19 1.16 1.10 1.00 Diversity Factor Diversity 17 21 18 16 19 27 22 23 24 28 25 26 29 20 30 No. of houses No. of 1.21 1.75 1.27 1.33 1.43 1.38 1.23 1.25 1.30 1.50 1.60 1.20 2.50 2.00 4.00 Diversity Factor Diversity 1 7 2 3 8 5 4 9 6 11 12 13 15 14 10
No. of houses No. of 1.0 by a diversity factor shown in the following table: in the following shown factor a diversity by Box Box houses small with of numbers networks LV for standards Orion design connected are less than 30 residential — Where factor Diversity be the ADMD must increased or feeder, a substation to effects are significant, even for relatively small numbers of consumers. of consumers. small numbers significant, relatively for are effects even For example, Box 1.0 below shows an extract from Orion’s design standard for for design standard Orion’s from below shows an extract 1.0 Box example, For the diversity This indicates networks. building new LV for required the capacity after-diversity peak demand compared with individual customer AMD. customer with individual peakafter-diversity compared demand to is understood analysis benefit shown in the above of diversity This level demand. non-EV benefit for of diversity levels be general with the consistent This diversity in timing means that EVs cause much less increase in in much less cause increase EVs that means in timing diversity This
Report on Electric Vehicle Charging Trial Final version - July 2018 26
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igur e Average increase per ICP (kW) ICP per increase Average F 0 0.8 0.5 0.4 0.2 0.7 0.6 0.3 0.1
Figure 14.0 Figure demand in increase EV before/after modeled regression Linear x-axis) non-zero (note igur Average increase per ICP (kW) ICP per increase Average
F
battery and the cabin while plugged-in being driven prior to include all as they reliable, more are The linear model results should be approach simple before/after The data. the available of the linear model results. on the validity a “check” considered Similarly, warming pre-heated. been have if they better perform batteries weather, In cold 7. the vehicle. of the range will driven extend being prior to while plugged-in the vehicle of the interior sophistication. of degrees varying to such ‘pre-conditioning’ perform the functionality to EVs have Many well as the the linear model (as from shows the results 14.0 Figure The peak similar. The two curves are the simple approach.) from results occurs in demand about midnight,increase off through and then drops peak the night. evening in demand during the traditional The increase in the linear model approach. pronounced 7pm) is more to (6:30pm peak a small in the morning between 6am and 7:30am. It also reveals the or “pre-heating” “pre-conditioning” be EVs to This is likely
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igur (kW) ICP per increase Average F Figure 13 .0 Figure x-axis) non-zero (note change in demand EV mean Simple before/after of the EV, while correcting for other effects, such as seasonality. other effects, for while correcting of the EV, A more sophisticated method of looking at the before/after EV increase increase EV method the before/after of looking sophisticated at A more model EV” with “has an a linear regression create in demand is to the effect This model can isolate as one of the input parameters. 2.3.4 model regression Linear with data with an EV, and also without an EV. This was only the case for case only the for was This and also without an EV. with an EV, with data data. half the available approximately only 38 out of 77 – i.e ICPs a long period who have customers at has only looked analysis The above
Report on Electric Vehicle Charging Trial Final version - July 2018 27
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igur Average customer ddemand (kW) ddemand customer Average
igur F Average customer ddemand (kW) ddemand customer Average F Figure 16.0 Figure per customer demand ICP day business winter Average x-axis) non-zero (note EV customers for
evening and in the early hours of the morning. There is a small is a small of the morning. and in the early hours There evening midnight at increase and a larger 11pm, at in demand increase 2.4.4) has section (see behaviour charging with extreme that a customer 8. Note effect had a noticeable single customer This 16.0. Figure from removed been at 9pm. occur demand to peak demand, and caused on the overall 14.0. in Figure shown behaviour with the charging consistent is 9.This morning and early is still the traditional there On business days, in the later also noticeable peaks are but there peaks, evening
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igur (kW) ddemand customer Average igur (kW) ddemand customer Average F F in control group (note non-zero axis) non-zero (note group in control 15.0 Figure customer demand per ICP day business winter Average combining their EV demand with their other demand (heating, demand with lighting,combining their EV etc.) “after diversity” demand, was examined for EV customers during business and during business and customers EV for examined demand, was diversity” “after is no with/ and there approach This is a straightforward non-business days. customers, all EV demand for comparison – it just shows average without EV they are all charged at the same time. at all charged are they demand, a.k.a. per customer the average be the case, see if this may To if change this may of demand, that source such a large are EVs However, between 5:30pm and 8pm during winter evenings. between evenings. during winter 5:30pm and 8pm Aggregate EV users demand EV users Aggregate peak electricityoccurs demand sometime Currently, 2.3.5
Report on Electric Vehicle Charging Trial Final version - July 2018 28
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igur Change in demand (kW) demand in Change F in these figures is too low. After all, a single Nissan LEAF draws Afterdraws all, a single Nissan LEAF too low. is in these figures the charging yet charging, kW during steady-state about 3.3 however, Note, 1 kW. exceeds plot never demand time-of-day exceeds never connected a vehicle to of EVSE the percent that Thus, the normalized to is not here. referred 12 60%, - the figure 60% of the maximum exceed never will demand per EVSE charging that not all vehicles Furthermore, one vehicle. possible demand for a time, given any At power. drawing are connected EVSE to are and have full battery packs connected of the vehicles have fraction demand plots The charging the EVSE. power from ceased drawing connected with vehicles and demand of EVSE the resulting show set.” the data in all EVSE to with respect normalized power, drawing On first glance, it may appear that the charging demand magnitude the charging appear that it may glance, On first about 0.9kW for Wellington). These results are verysimilar. are These results Wellington). for about 0.9kW point is demand per charging observed the average The authors that and commented: an EV, for load significantly less than the typical charging “ peak in afterThis supports diversity the increase our observation that ICP. single any in demand for is significantly lower than the increase The median increase in demand during the evening peak was about about peak was the evening in demand during The median increase The highest median Wellington). for 0.4kW to (compared 0.3kW to (compared about 0.8kW was in demand during the day increase
20:00
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IQR 0:00 0 17.
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1.0 0.4 0.2 0.8 0.6 igur (kW) EVSE oer Demand F Figure 17.0 Figure States EVs in the United for charging Weekday below is the increase in demand at a location from EV charging. charging. EV from a location at in demand below is the increase charging EV in demand per ICP due to the increase to This is analogous others). (amongst 14.0 Study as shown in Figure the Wellington for of Electric Vehicle Charging on the Electric Grid in The EV Project” on the Electric Charging Vehicle of Electric similarly sized found and States, in the United charging EV at looked per EVSE” The “demand in demand. increases Comparison with international research with international Comparison Don Scoffield and John Smart, Schey, Stephen 2.3.6 10. https://energy.gov/sites/prod/files/2014/02/f8/evs26_charging_demand_manuscript.pdf 10. point. a charging aka Equipment EV Service short for is EVSE 11.
Report on Electric Vehicle Charging Trial Final version - July 2018 29
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igur Change in demand (kW) demand in Change F Figure 18.0 Figure the to exposed customers demand for Change in x-axis) non-zero (note price spot the spot price exposed to use customers shows that 18.0 Figure between demand midnight and 4amand less demand in other more periods. This suggests the spot price exposed to those that customers because sense, periods. This makes during off-peak more charge than it is during the day. the spot price is often lower overnight 20:00 16:00
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F price exposed” parameter for each customer with an EV. The model then The model then EV. with an customer each for price exposed” parameter were period. The differences trading each for in demand differences produced periods zero. was all trading across difference normalised the average so that The charging behaviour of customers exposed to the spot price was the spot price exposed to was of customers behaviour The charging do this, To structures. pricing traditional with those on more compared used, was and included a “spot the linear model described in section 2.3.4 More recently, some retailers provide their customers with the option to with the option to their customers provide some retailers recently, More the spot price. exposed to are they i.e. wholesale the price directly, pay The wholesale market settles every half-hour, with a different price for price for with a different settles half-hour, every The wholesale market faced directly not have customers period.electricity in each Traditionally, their retailer. price to an averaged pay the wholesale price and instead 2.4.1 exposure price Spot to different pricing structures. There were two main pricing options that two main pricing options that were There pricing structures. different to distribution charge. the EV-Nite and analysed – spot price exposure were Time of Use signals Use of Time respond how customers look at to was of the analysis focus The other key Customer response to response Customer 2.4
Report on Electric Vehicle Charging Trial Final version - July 2018 30
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Increase in demand (kW) demand in Increase Increase in demand (kW) demand in Increase igur igur being early-adopters of a technology, and likely to be more engaged engaged be more to and likely technology, of a being early-adopters may behaviour charging with the electricity market. Such consumers’ the electricity be least cost to for is likely what to attuned be more in the middle of the night, charging rather as a whole (i.e. market 9pm) / early night – i.e. evening late at than starting charging period of time, rather than setting them to start charging at a specific at time. start than setting to them charging rather periodof time, Possibly it is due to customers setting the EVs to ‘delay’ charging by a a by charging ‘delay’ to setting the EVs customers due to it is Possibly – owners of the EV nature ‘unusual’ the relatively it indicates Possibly F F Figure 20.0 Figure customers and non-TOU TOU EV demand for
2.4.3 pricing use time of of effect Overall of the linear model distinguishing between shows the results 20.0 Figure spot price and/or pricesignal (EV-Nite some Time-of-Use those who have tariff” a “TOU as having to – and those with no – referred exposure) tariff”. time-based signal “Non-TOU However, this step-change increase appears to occur midnight, to at appears increase step-change this which was However, period. be this would the case: why It is not clear not the start EV-Nite of the ● ●
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Change in demand (kW) demand in Change igur (kW) demand in Change igur F F Figure 19.0 Figure prices Use of Time to exposed customers for Change in demand x-axis) non-zero (note the reduction in demand during the evening peak is more pronounced. peak is more in demand during the evening the reduction the in demand at increase step-change pronounced a more It also indicates signal. start of the night period. concerns This is one of the potential with a TOU The change in demand is similar to Figure 18.0, but the effect is larger, and and is larger, but the effect 18.0, Figure in demand is similar to The change
on the EV-Nite tariff. on the EV-Nite 7am. Three retailers passed this onto their customers for the period covered the period covered for passed their customers this onto retailers 7am. Three in the trial. customers in demand for below shows the change 19.0 Figure EV-Nite customers EV-Nite is 5c cheaper betweenthat a tariff 9pm and Electricity offers Wellington 2.4.2
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. Such behaviour would put a high load on local networks if it were if it were on local networks would put a high load . Such behaviour
11 Increase in demand (kW) demand in Increase igur Figure 21.0 Figure demand customer Kiwi Electric average F to consume 45% of their demand during this hour. Bearing in mind that this Bearing this in mind that of their demand during this hour. consume 45% to is 18kW widely. more adopted only because is This the analysis. in the majority of included not 3 is customer 11. Unfortunately, an EV. used they before include a period doesn’t them, which for available was data 9 months of possible. Data was collected for four Electric Kiwi customers. four collected for was Data possible. power potential the of price incentives indicates one customer from The data influence consumerto behaviour. 3 manages Customer the day. demand through shows the average 21.0 Figure 2.4.4 Power” of “Hour Kiwi Electric of Power”, “Hour one off-peak their customers Electricity Kiwi offers creates This their electricity use. for not charged are they during which where hour that shift into to load their customers for incentive a strong
would likely charge when they get home in the absence of a home in the absence get of a when they charge would likely behaviour. price signal or guidance on desirable charging demand on the electricity network were rated as being important as being important rated demand on the electricity network were Only 7% of majority. after the 9pm by charging for motivations during this behaviour afterparticipants 9pm adopted charging on peak information of providing the act the trial, indicating a small influence. had guidance on timers demand and practical This would suggest of customers a higher proportion that many more customers delay charging their EV till night time. till night time. their EV charging delay customers more many responses detailed the survey in Section 1 indicate Participant on the environment the impact this both reducing for reasons of (which has a higher proportion utilising night time power, by peak and the other altruistic aim of reducing energy) renewable corresponds to customers who plug in their EV as soon as as soon as who plug in their EV customers to corresponds home. get they The first coincides with the traditional evening peak, and probably peak, evening and probably coincidesThe first traditional with the peak about midnight, larger The second, that indicates even is also a peak about midnight from delayed charging. delayed is also a peak about midnight from the traditional evening peak, although it is smaller. The The peak, evening although it is smaller. the traditional and there the evening through does not decrease increase corresponding to two different types of charging approach. approach. types of charging different two to corresponding TOU customers also have an increase in demand during in demand during an increase also have customers TOU Non-TOU customers have two distinct peaks in the evening, in the evening, peaks two distinct have customers Non-TOU — —
cabin on cold days to improve the range of the vehicle. the range improve to cabin on cold days much later. Both such peaks are likely to be due to vehicle pre- vehicle be due to to likely are Both such peaks much later. and up the battery warming conditioning while plugged-in – i.e. In the morning, customers on a TOU tariff showed an increase tariff showed an increase In the morning, on a TOU customers period (7am). The the end of the EV-Nite in demand prior to a morning peak but it is also have tariff customers non-TOU ● ● The two types of customers have noticeably different charging behaviour. behaviour. charging noticeably different have typesThe two of customers
Report on Electric Vehicle Charging Trial Final version - July 2018 32
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peak. This additional peak demand could be of the order of 4kW per EV – on – on peak. of 4kW perEV peak demand could This additional be of the order 9pm demand at after-diversity kW per customer 1.5 of the approximately top peak than the current greater This is considerably evening. on a cold winter’s 2.25 peak periods. during current kW per customer demand of approximately a double-edged tariffs is potentially to sword: response This customer ● ● period all the the start at of the off-peak start if all vehicles charging Further, would be been observed charging with EV have benefits that significant diversity network than the current lost, the new peak being to significantly greater leading
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igur F peaks. This effect was greatest for those exposed to the we* EV-Nite EV-Nite those the we* exposed to for greatest was This effect peaks. those spot wholesale exposed also to significant for prices was but tariff, 22.0. in Figure is illustrated This difference (e.g. customers). Flick their vehicles overnight even without an electricity tariff incentive, a far a far without an electricity tariff incentive, even overnight their vehicles a time-of-use exposed to who were consumers of EV proportion greater morning) (and of the evening outside their vehicles tariff signal charged while the car is plugged-in in order to increase the vehicle range. the vehicle increase to while the car is plugged-in in order in this study charged consumers of the EV many Notwithstanding that half that of the evening demand increase). This is understood to be be to This is understood demand increase). of the evening half that in the half- – i.e. winter in the of EVs with ‘pre-conditioning’ associated up the battery and cabin warming be driven, the car is to hour or so before be typical of charging behaviour when EVs are adopted more widely. widely. more adopted are when EVs behaviour be typical of charging in demand in the morning peak (although increase is also a material There when customers have no electricity tariff incentive to do so. Given Given do so. to no electricity tariff incentive have when customers (i.e. sample group of the nature ‘unusual’ the small, and potentially whether this would it is not possible infer to early-adopters), technology the order of 0.5 to 0.8 kW. 0.8 to of 0.5 the order proportion a greater examined, customers of EV in the sample However, This is even and beyond. midnight – i.e. occur to much later appears to 4 kW, there appears to be material diversity in the start of and duration of of in the start of and duration diversity be material to appears there 4 kW, to be of to is likely kW impact meaning the after-diversity such charging, In the absence of an electricity price signal, a significant proportion appears In the absence of an electricity price appears signal, a significant proportion work – coinciding with electricity system occurto when people home from get capacities of 2.5 typically having chargers despite peak.evening However, By approximately 2,500 kWh per annum – roughly 35% of the average of the average 35% kWh per annum – roughly 2,500 approximately By demand. residential Conclusion demand: residential average increase will materially charging EV 2.5 Report on Electric Vehicle Charging Trial Final version - July 2018 33
exceedance on the low voltage networks (which typically have 50 ICPs). have (which typically networks the low voltage on exceedance customers – i.e. of the order of 5 or so. As such, unless TOU signals signals As such, unless TOU so. of 5 or of the order i.e. – customers the start peak step-change at of sharp, a new incentives for create capacity widespread not cause may uptake period, EV the off-peak for the sample is significantly less (approximately 0.5 kW to 0.8 kW). kW). 0.8 kW to 0.5 is significantly less the sample (approximately for of small groups is significant, relatively effect for This diversity even In terms of the diversity effect, the analysis shows that while the anytime effect, while the anytime of the diversity shows that In terms the analysis significantly with an EV increases peak customers demand of individual peak the sample), the after-diversity increase kW for 4 approximately (by increase at 9pm (when the EV-Nite period started) but a couple period started) couple but a the EV-Nite 9pm (when at increase would be this the case. clear why It is not later. of hours Conclusion (cont.) Conclusion tariff did not show a sharp EV-Nite with the group The sample 2.5 Report on Electric Vehicle Charging Trial Final version - July 2018 Appendix A Non average analysis or, a closer look at individuals
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Report on Electric Vehicle Charging Trial Final version - July 2018 35
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F out, and have increases of 4kW or more, which is many times the average times the average which is many of 4kW or more, out, increases and have those particular for increase this is still the average Bear in mind that increase. single day. be much higher on any may value and the actual customers, 1.1 A Customer in demand increase has a very large 23.0 Figure A from Customer starting at their EV charge they that It appears hours. during off-peak shows their average 23.0 2am. Figure normally finished by 11pm, and are details of their behaviour. the but this obscures in demand, increase over the customer shows the maximum daily demand from 24.0 Figure between daily demand was 1 and 3kW Maximum two years. the previous that, After in early 2016. most of the time an EV acquired they before in the with the change 6kW consistent above maximum daily demand was previously. 11.0 curve shown in Figure load-duration individual customer their EV, did not charge when they presumably occasionally, However, the earlier period. similar to much lower, maximum demand was the to these can lead two situations see to how averaging easy It’s this average However, 23.0 shown in Figure increase 4-5kW average the EV. charge didn’t when the customer includes those days Clearly there is a lot of difference between customers. Some customers stand stand Some between customers customers. of difference is a lot Clearly there
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customers whereas Figure 23.0 below shows the average 23.0 Figure whereas customers graph. up that made that the individual customers demand for This appendix examines the impact of EV charging on individual customers. on individual charging EV of the impact This appendix examines 38 in demand across change showed the average previously 13.0 Figure principally focussed on the average increase increase on the average principally focussed EV charging due to in demand The analysis in the main report has main report in the The analysis a step further and averaged each customer’s average increase in demand. increase average customer’s each further and averaged a step 12.The linear model analysis is also a form of averaging. of a form also is model analysis 12.The linear a particular for increase the average is This going on here. still averaging is some 13. There went 13.0 Figure days. different a number of period across in that trading customer
Report on Electric Vehicle Charging Trial Final version - July 2018 36 02:00
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certain risk level. It is hard to quantify exactly what risk level, because this is because this is risk level, what quantify exactly to certainis hard It risk level. dependent on assumptions so it is heavily all customers, the distribution for diversity. load around a in demand at increase as the expected can be interpreted This graph Figure 25.0 shows the increase in the P90 and P99 demand for customers customers for P99 demand P90 and in the the increase shows 25.0 Figure with an EV behaviour extreme as more sense, makes This but the scale is much larger. the average. than rather is being examined, consumer an individual basis. not an after-diversity basis, this is for Again, Note: 14. It is slightly counterintuitive that the P90 curve is higher than the P99 curve at times, but this at times, higher than the P99 curve is that the P90 curve slightly counterintuitive is 14. It still The P99 demand is higher than the P90 the differences. showing is graph this since correct, is in P90 demand. than the increase less in P99 demand is but the increase demand in all cases,
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90th percentile value. For example, the P90 value of the data in Figure 11.0 11.0 in Figure of the data the P90 value example, For value. 90th percentile the “P99” the 90% mark. at Similarly, the value to corresponds 99%. to corresponds value Percentile analysis Percentile different look at is to parameter a highly variable of looking at One way the of a distribution is value “P90” of the distribution. The percentiles 1.2 appropriate. However, an alternative approach that doesn’t just use averages, just use averages, doesn’t that approach an alternative However, appropriate. the local looking level. at might be useful for is averages the wider network, considers lookingthat at an analysis For
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-1 -2 -3 e Average increase in demand (kW) demand in increase Average igur F Report on Electric Vehicle Charging Trial Final version - July 2018 37 electricity infrastructure. The charge is packaged by electricity retailers electricity retailers by is packaged The charge electricity infrastructure. customers. to bill the energy this to who add (TOU) Use Time of time rates in different charge which uses different Tariff A Lines Charge costs. different periods. Hence the time of use of electricity will attract periods signal cheaper costs higher usage to assigned to Higher costs are shifting less congested demand to for time periods. The period of the day when there is the least demand for energy on the energy is the least demand for there when The period of the day network. will occur This between the peak demand periods. Peak is the highest demand for there collectively when The period of the day and is a morning there level residential the the network. on At energy Electricity network. peak the Wellington on evening Retailer for with all customers relationship Electricity has the financial Retailer of the lines tariff company portion. used, including packaging billing energy Price Spot on a half hour which changes price of energy wholesale market The actual however energy, price for retail an average take basis. Most customers a wholesale take to allowing customers are market the to new retailers of expensive and risk of cheaper energy price reward which has the price option. of the retail the averaging unlike energy Tariff using the customers for a lines recovers company or utility fee The charge Off-Peak
but also use a conventional internal combustion engine to extend their range. extend combustion engine to internal but also use a conventional PHEV their battery recharge can connect power a supply to to PHEVs EV. hybrid A plug-in Lines Companies recover their network costs through lines charges which are which are lines charges their network costs through Lines Companies recover electricity bill. the customer Electricity into Retailer the customers bundled by customer consumption of electricitycustomer units (kWh). Tariff Charge Lines Kilowatt (kW) Kilowatt an hour represents over when measured demand which of energy Measurement HHR a half hour period. over an electricity meter from a measurement Hour resolution, Half Electric Vehicle Supply Equipment – what is used as the device to charge the EV. charge is used to – what as the device Supply Equipment Electric Vehicle EVB replaced EV-Nite from 1 July 2018. from EV-Nite replaced EVB EVSE EVB cheaperhaving Electricity Wellington from TOU tariff A cost reflective peak demand period charges. expensive periods and more night charge Electric Vehicle. cost between lower consumption higher and periods. EV Cost Reflective Pricing Reflective Cost in An electricityvariable prices tariff which usesto signal the difference
1.3 Terminology
Report on Electric Vehicle Charging Trial Final version - July 2018
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