Electric Vehicles and the Grid Working Together

By Jairo Quirós-Tortós, Luis (Nando) Ochoa

In the next decade or so, hundreds of thousands of new electric vehicles (EVs)—from plug-in hybrid to fully electric—will hit the roads around the world, adding to the current EV fleet of more than 3 million. To understand the challenges and opportunities that come with the widespread adoption of EVs, particularly passenger light-duty vehicles, many distribution network operators (DNOs) and stakeholders in different countries have carried out EV trials.

One of the largest (if not the largest) EV trials in the world was “My Electric Avenue” in the United Kingdom (MEA) which run from January 2013 to December 2015. The MEA project, led by EA Technology with partners from industry, DNOs, and academia, and funded by the Low Carbon Networks Fund, deployed over 200 Nissan LEAFs (24 kWh battery) to customers to study the charging habits of a geographically and socioeconomically diverse population. It also investigated the technical effects of EVs on European-style low-voltage (LV) networks and trialed the direct control (management) of EV charging points to increase hosting capacity.

Below, we present some of the key findings from the MEA project. Readers interested in knowing more about the project are invited to check a recent article published in the Power & Energy Magazine.

EV Charging Behavior

Understanding when and for how long EV users will charge their vehicles is one of the most critical aspects to realistically study EV interactions with the grid. However, EV data is scarce, which highlights the need for more EV trials that make key data publicly available. This project recorded the charging behavior of non-managed EV users (85,000 charging events) in the UK for almost 2 years. Among all key outcomes, the data analysis of this EV population highlighted the following:

  • About one EV out of three are charged more than once per day—a unique finding not explored previously.
  • The first charge might occur any time during the day, but the second one is more likely after midday.
  • Over 65% of the EV users charge their vehicle when the state-of-charge is above 20%.
  • Two EVs out of three are charged until the battery is full.
  • Not all EVs are charged on the same day; as there were 2 days during each month in which no EV was charged at all.

EV Impact on LV Networks

MEA studied the hosting capacity of three-phase LV networks (modeled in OpenDSS) considering EV penetration levels (number of houses, all single-phase connected, with a single EV) from 0% to 100% in steps of 10%. Different from many other impact studies, the assessment followed a stochastic approach to consider the uncertainties associated with the demand of households as well as the location and demand of EVs. The analysis showed the following key conclusions:

  • The peak demand of the EVs is likely to coincide with the existing evening peak.
  • From the perspective of DNOs, the maximum demand of households with an EV charging is slow-mode will grow, on average, to almost 2 kW per household (i.e., DNOs in the UK will need to plan for 2 kW per house) – double the conventional demand.
  • Studies on 9 different low-voltage networks found that, for some of them, problems start at 40% penetration (i.e., hosting capacity of 40%) mainly due to the transformer located at the substation, followed by thermal problems at the LV feeders, and only long feeders may face voltage issues for very high EV penetration levels.
  • The proposed methodology to assess this hosting capacity can be adapted in other countries that are in the process of deploying EVs.

EV Management Solution

To mitigate the impacts resulting from the adoption of EVs and, thus, increase the ability of LV networks to host more EVs, the MEA project trialed a solution to manage EV charging points. This solution disconnects EV charging points when a technical issue occurs in the LV network. When there is spare headroom (i.e., no more problems), it then reconnects them. The following conclusions could be drawn:

  • The EV management solution can increase the hosting capacity of LV networks to 100% in all the simulations and the actual trials.
  • Although the technical impacts could be fully mitigated, as the EVs are switched off when a problem arises, the studies showed that charging delays and battery degradation can occur because of the repeated management of the EV.
  • If EV management solutions are to be truly adopted, an effective deployment should consider the trade-off between the benefits from the control, the capabilities of the EV batteries, and the potential technical issues on the networks.
  • The EV management solution trialed by the MEA project is considered practical and scalable enough to be deployed by other DNOs.

What is Next?

The outcomes from the MEA project can help integrate EVs into most electricity systems around the world. In the United Kingdom, a new project called Electric Nation (www.electricnation.org.uk) is already progressing on the understanding from MEA and plans to deploy more than 500 EVs to study different cost-effective solutions to manage networks ranging from demand response to V2G applications are on-going. The deployment of this project, and many others that will take place in the next decade, demonstrates the value of EV trials in providing outcomes that will facilitate the transition toward the electrification of the transportation sector.

Jairo Quirós-Tortós

Jairo Quirós-Tortós (S’08, M’14, SM’17) received the B.Sc. and Licentiate degrees in Electrical Engineering from the University of Costa Rica, Costa Rica, in 2008 and 2009 respectively, and the Ph.D. degree in Electrical Engineering (Power Systems) from The University of Manchester, U.K., in 2014. He worked as Post-Doctoral Research Associate at the University of Manchester from Feb. 2014 to Jan. 2016. He is currently Associate Professor and Head of the Power & Energy Department at the University of Costa Rica. His current research interests include network integration of distributed energy resources and integrated energy planning.

nando

Luis(Nando) Ochoa is Professor of Smart Grids and Power Systems at The University of Melbourne, Australia and part-time Professor of Smart Grids at The University of Manchester, UK. His expertise in network integration of low carbon technologies and his extensive portfolio of industrial and academic projects have led to 150+ publications, 60+ technical reports, and two patents, one filed by Psymetrix Ltd (now part of GE) and one filed by The University of Melbourne. Prof Ochoa is an IEEE PES Distinguished Lecturer and is also Editorial Board Member of the IEEE Power and Energy Magazine. Prof Ochoa is an IEEE Senior Member since 2012. He holds a Bachelor's degree in Mechanical and Electrical Engineering from UNI (Peru), and a Research MSc and a PhD in Electrical Power Engineering, both from UNESP Ilha Solteira (Brazil).


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