The Optimise Prime network innovation project has today published its final deliverable, detailing the lessons learnt from four years of trial activity.
The project has gathered data from over 8,000 electric vehicles (EVs) driven for commercial purposes through three trials and implemented a range of technical and commercial solutions with the aim of accelerating the transition to EVs for commercial fleet operators, while helping GB’s distribution network operators (DNOs) plan and prepare for the mass adoption of EVs.
This report provides a comprehensive overview of lessons learnt from conducting the trials, throughout which the project has collected and analysed data from a wide range of sources in order to carry out a wide range of experiments and developed recommendations for future use of the project methods and data in order to reduce the impact of commercial EV growth on distribution networks.
Three trials have involved studying British Gas’s Home Based Fleet, Royal Mail’s depot based fleet and Uber private hire vehicles.
The key findings, which are discussed in more detail throughout the report, include:
Return-to-Home Trials
Unmanaged, home-based fleets will create concentrated load peaks from 17.00 on weekdays due to the timing of the end of shifts coinciding with network peaks
Smart charging can be very effective at changing load patterns, however it may lead to significant ‘secondary peaks’ overnight. Incentives to drive the smart charging behaviour should be considered to reduce the impact of this behavioural change on the network
The British Gas home-based fleet was found to be very reliable in the delivery of weekday flexibility services, over a one hour period at specific times, due to its predictable pattern of charging load. Revenue from flexibility, which could amount to around £215 per vehicle per year, can help to improve the total cost of ownership (TCO) for home-based fleets
Winter EV energy requirements are approximately 30% higher than in the summer
The proportion of the home-based fleet that relies on public infrastructure has increased throughout the trial. This is because drivers that could charge at home were initially targeted, before moving on to those who needed to use public infrastructure. British Gas estimate that up to 60% of their fleet may need to use public infrastructure once fleet electrification is complete.
Depot Trials
Load profiles are depot specific and can change seasonally, with two main peaks appearing at 14:00 and 19:00, which follow the depot delivery schedules. More rural Royal Mail depots are likely to see their demand peak in the afternoon
The short and sharp load peaks at some depots limit the duration (up to three hours) and volume of flexibility (up to 25% of the depot’s charging capacity) that can be offered. Flexibility products should incentivise participation from fleets that can offer flexibility very reliably and fleets that are less reliable, as well as different volumes of flexibility, to maximise access to controllable load at the best possible price
Factors impacting reliability of flexibility services include:
the size of the depot – minor changes at small depots can have a large impact on delivery of flexibility
the charge point to EV ratio – sharing charge points results in higher utilisation, but timing of charge events can be challenging to predict
daily EV mileages – impacting how long flexibility events can be sustained
operational processes – such as when EVs are plugged in, the variability of shift patterns and the use of vehicles on different shifts
Using smart charging to manage load in line with a profiled connection was shown to save some depots up to £95,000 on the cost of connection and up to 12 weeks in the time to connect. While the changes to connection charges announced in the Access and Forward Looking Charges Significant Code Review will lead to customers no longer having to pay for reinforcement of shared assets, these costs were made on extension assets that would still be the responsibility of the customer after the change
Trials suggest that between seven and 20% of fleet charging costs could be covered by revenue from flexibility services. However, whether this can be achieved depends on the DNO’s requirements for flexibility services, the electricity tariff and how this aligns with the depot’s charging schedule
Profiled connections can be successfully implemented, but EV load must be the dominant load in the depot for its control to reliably ensure compliance.
Mixed Trials
Most (77%) demand from PHVs occurred off-shift, with plug-ins peaking at about 20:00, but continuing through the night – later than other fleets would normally plug in
Future demand from PHVs is likely to shift further towards off-shift charging close to home, as vehicles with larger batteries are able to complete full shifts on one charge, further reducing the proportion of on-shift charging
It is expected that the rapid growth in the number of Uber EVs will result in a maximum load from off-shift charging in Greater London increasing from an estimated 10 MW in May 2022 to 69 MW by the end of 2025. Over the same period, annual electricity demand from these EVs is expected to reach 497 GWh, compared to 63 GWh used in the year to May 2022. Based on modelling of driver shift times, charging needs and home locations, Optimise Prime estimates that approximately 33,500 fast charge points may be required to service this demand if drivers opt for overnight fast charging.
The trials piloted two methods aimed at reducing the impact of EV charging on the distribution network, provision of flexibility services and profiled connections. Optimise Prime has developed several recommendations for DNOs regarding the implementation of the methods trialled in the project, including:
Flexibility Services
The month (or more) ahead product should allow fleets to re-forecast their baseline in the run up to delivery to improve predictability/reliability of outcome
Pricing incentives should be structured to reward good performance without disincentivising participation by some fleets. A range of products with different performance/reliability thresholds could be implemented to achieve this, with fleets with a higher probability of successful delivery attracting a higher price
Automation is required in the tender, bidding, dispatch and settlement calculation processes to make provision by smaller assets cost effective
Baselining establishes a ‘normal’ level of load against which the delivery of flexibility is judged and rewarded. As EV demand fluctuates, establishing an accurate baseline can be difficult. Tests of several baselining methodologies highlighted the need to use recent data and demonstrated that the most accurate method varied and needs to be chosen based on fleet characteristics.
Incentives should be structured to prevent the occurrence of secondary peaks which could cause additional problems for the network.
Profiled Connections
A process to model the expected load flow (such as using UK Power Networks’ LV utilisation modelled data), as a proxy for the substation data may be required if no monitoring is available, supplemented with half-hourly data and/or diversity modelling
Planning systems need to have the capability to assess network loading at a half-hourly granularity, in order to assess the feasibility and benefit of a profiled connection
The range of contracts should allow for dynamic profiled connections, that can be changed or activated at the request of DNOs to act as flexibility products
A process to revise profiled connections is needed to allow changes in fleet operations during the life of the connection. A review is likely to be required approximately one month after implementation to ensure the EV load is in line with the forecast. Seasonal updates may also be required, in addition to ad hoc reviews in response to significant changes in fleet or depot operations.
Integrated monitoring is required to provide the DNO with visibility of breaches, a method of communicating alerts to the provider is also required
A method to police the profile, either through physical disconnection, economic penalties, or a combination of the two, must be agreed in the contract and implemented.
The report also contains a number of appendices, providing a deeper insight into topics of interest to DNOs and fleets, including the project’s behavioural research, total cost of ownership analysis and practical learnings from implementing EV infrastructure.
Optimise Prime is an industry-led EV innovation and demonstration project that brings together partners from leading technology, energy, transport and financing organisations, including Hitachi Vantara, UK Power Networks, Centrica, Royal Mail, Uber, Scottish and Southern Electricity Networks, Hitachi Europe and Novuna Vehicle Solutions. Through cross-industry collaboration and co-creation, the project has been aiming to reduce the impact of EVs on distribution networks and ensure security of electricity supply, while saving money for electricity customers, helping the UK meet its ‘clean air’ and climate change objectives.
