Accessing new revenue pools through virtual power planting of electric vehicle fleets

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Electric vehicles can make a significant contribution to the climate-neutral future of mobility - politics, business and science agree on this. However, the exact nature of this contribution and where it should be made differ in terms of ideas and timetables. While the German government is laying the foundations for a solid charging infrastructure for electric cars with the help of the so-called Gebäude-Elektromobilitätsinfrastruktur-Gesetz law, or GEIG, new, innovative ideas are already being developed. These parallel developments show once again how important the exchange between science and politics is in order to bring innovations to the market in the best possible way and not to prevent them by well-intentioned, political pre-determinations.

One of the ideas is to use electric cars as virtual power plants. Prof. Dr. Wolfgang Ketter and Karsten Schroer of the University of Cologne have examined this approach in detail and have provided us with the results in a guest article in our Mobility Policy Brief.

The ensuing COVID-19 crisis has inflicted a deep shock on the mobility sector. Following comprehensive and strictly enforced lockdown measures mobility demand plummeted by as much as 80% or higher in some markets. The impact is especially strongly felt by privately-backed platform-based mobility networks that are poised for growth and often light on cash.

While lockdowns are being eased around the world and mobility markets seem headed for a careful recovery, the crisis has shed light on the fact that mobility providers do not typically have alternative revenue streams at their disposal and are therefore exposed to external shocks. Our research shows that shared mobility platforms with electric vehicle fleets can profitably access new revenue pools by turning their existing fleet into a virtual power plant. Our approach solely relies on advanced analytics and automated electricity markets and can generate additional profits gains of up to 4.3% in selected markets.

The business logic of virtual power plants arises from demand and supply imbalances in the electricity markets that have become more frequent as the results of the energy transition. With the trend today moving away from top-down vertically integrated fossil fuel generation towards decentralized electricity sources, certain factors are no longer within a power plant operator’s control. For example, the operator cannot predict with any high degree of accuracy how hard the wind will blow or how long the sun will shine, and there could be large fluctuations in generating capacity. In times when renewable output is low, back-up fossil fuel plants or other technologies such as Power2Gas have to be brought into use to make up the shortfall. At other times when output is high, wind farms might have to be taken offline to avoid overloading the grid, which is both wasteful and inefficient. Our research shows that using electric vehicles (EVs) as virtual power plants (VPPs) can play a crucial role in balancing smart electricity grids, thereby addressing these key issues.

While individual drivers can make a difference, the impact will be much greater at scale. For this reason, we focused our study on the management of EV fleets organized as VPPs, and analyzed the potential of parked vehicles to absorb excess electricity from the grid when energy supply is high and demand elsewhere low, and to feed electricity back into the grid by discharging when supply is low and demand high. What we found was that such VPPs can be both ecologically advantageous, through reductions in wind power curtailment, and beneficial to consumers by reducing energy expenses. Crucially, however, they can also be profitable for fleet owners, by charging cars when low demand drives spot electricity prices down, and selling the same power back to the grid at times when high demand drives prices up.

Individual Mobility vs. Grid Balancing – A Dilemma

But while this may sound like a license to print money, there are a number of specific challenges that must be addressed if we are to best utilize the EV fleet.

To utilize the EV fleet to its best potential while not putting in jeopardy the core business of providing mobility to people, a careful and real-time evaluation of current and future electricity and mobility demand is required. As an individual vehicle can either be used for mobility or as part of a VPP bad operational decision making may lead to a situation where mobility demand cannot be fulfilled or vice versa. For fleet operators this culminates in a complex dilemma of which market (energy or mobility) to allocate individual vehicles to.

State-of-the-art AI-powered prediction tools can help manage this dilemma. The spatio-temporal prediction of mobility demand is a key challenge. In the end the main purpose of a fleet is to ensure mobility for its users. Any failure to do so will negatively impact service level, user satisfaction and ultimately revenue generated from mobility. It follows that the fleet operator requires accurate forecasts of how many vehicles exactly will need be available for rental in a certain area. On top of that accurate information on the number of vehicles connected at charging stations and their cumulative free battery capacity is required. Additionally, relative certainty on future electricity prices is required to make informed trade-off decisions.

The particular challenge of this mixed usage strategy is the continuous and real-time evaluation of two parallel and mutually exclusive market opportunities for the fleet. Fleet operators need to make decisions between making an EV available for use, where the location within the city matters - drivers want cars to be near their place of departure or arrival – and discharging it to the grid. In the latter case location matters less, as vehicles can discharge from any capable charging point in the distribution grid. It is a balancing act in which incentives may help, such as providing free driving minutes to encourage drivers quite literally to go the extra mile to seek out charging points

Our research focuses on the development of automated decision tools that leverage machine learning and mathematical programming and enable an effective and robust management of the above described trade-off while maximizing service level.

Factors of Effectiveness and the Importance of the Local Context

The effectiveness of our VPP strategy is dependent on a number of factors. One big issue is infrastructure. We need charging stations to be located where there is highest demand for EVs, as these stations form a critical element of the whole virtual power plant. The location might be city dependent, environment dependent, or even seasonally dependent, but it requires careful planning. And of course, the charging points need to be bidirectional so that they can not only charge but also discharge a battery.

While charging infrastructure availability is a core requirement, consistent usage of that infrastructure is also key. This means an element of behavioral change is required on the part of the EV user. In the cases we studied there was no incentive for the drivers to park the cars after use near to one of the charging stations. To benefit fully, that behavioral aspect needs to be in place – you want to have the cars available for usage, but also for discharging. They need to be parked and connected to the grid at the right time; otherwise they cannot take advantage of energy trading.

Specifications, performance and cost of battery technologies also play a crucial role. We examine the impact of various price trajectories and find that future battery technology can boost profit potential of VPPs considerably. Finally, local factors play a crucial role, and have a direct impact on the EV fleet’s potential use as VPPs. Physical properties and culture both play a big role, as the success of a VPP depends on what percentage of sustainable resources a location has in its energy mix, and on the rate of energy taxes. It is also dependent on the willingness of people to share vehicles – this is much higher in Europe generally than it is in the United States.

The Future of Fleet-based VPPs – Doing Well by Going Good

Fleet-based VPPs constitute a profitable secondary revenue stream for fleet operators and are a promising way of increasing fleet utilization. While the core business (and profit pool for that matter) remains firmly centered on the provision of mobility services, state-of-the-art forecasting and optimization methods enable operators to profitably tap into new business opportunities arising from virtual power planting. A well-managed fleet can become something we call “doing well by doing good”. The fleet owner is doing good by providing a service to society: changing high volatility in the grid to a high level of energy independence to create balancing capacity. But at the same time, they are doing well for their company’s pocket by creating a second business model with an alternative income stream.

In a follow-up study we have evaluated the potential of fleet-based VPPs in the ancillary services market for frequency control. We show a considerable further increase in net profit.

To see the potential benefits of electric vehicles as virtual power plants yourself, visit our Power TAC website ( This is the world’s largest free, open-source smart grid platform, which you can use to test this and a range of other sustainability scenarios.


  • Kahlen, M., Schroer, K., Ketter, W., Gupta, A., Smart Markets for Real-Time Allocation of Multi-Product Resources: The Case of Shared Electric Vehicles (September 1, 2019), verfügbar online unter
  • Kahlen, M. T., Ketter, W., and Dalen, J. Van. 2018. “Electric Vehicle Virtual Power Plant Dilemma : Grid Balancing Versus Customer Mobility,” Production and Operations Management (27:11), pp 2054-2070, verfügbar online unter
  • Power TAC (

Prof. Dr. Wolfgang Ketter is chaired professor for Information Systems for Sustainable Society at the university of Cologne. His research focuses on the use of AI, market design and large-scale simulation in the service of sustainability in energy and mobility. He is co-director of the Institute of Energy Economics at the University of Cologne, Fellow of the World Economic Forum Global Future Council on Mobility and a regular adviser to the German government. You can keep up-to-date with Prof. Ketter’s research via Twitter @wolfketter.

Karsten Schroer is Doctoral Researcher at Professor Ketter’s Chair for Information Systems for Sustainable Society. His particular research interests lie in the design of data-driven decision support applications and smart mechanisms that leverage machine learning and mathematical programming methods to facilitate a more sustainable energy and mobility ecosystem. Karsten Schroer holds a degree in Mechanical Engineering from the University of Cambridge. He regularly shares research updates via Twitter @KarstenSchroer.

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