Is charging electric vehicles with variable tariffs worthwhile? Attractiveness for electric vehicle drivers and business model potential for electricity providers and aggregators
Attractiveness for electric vehicle drivers and business model potential for electricity providers and aggregators
Spot market-optimized charging of electric vehicles (EV) supports the integration of renewable electricity generation into the energy system. At the same time, it offers drivers the opportunity to save charging costs by shifting charging processes. But is the use case attractive for them? Although charging costs can be saved by shifting charging processes to times of favorable electricity prices, this also limits the flexibility of vehicle use and increases the risk of being exposed to extremely high prices on the spot market.
Whether spot market-optimized charging is attractive for electric vehicle drivers strongly influences the potential for associated business models for electricity suppliers and aggregators. This includes offering variable electricity tariffs and marketing aggregated vehicle flexibility.
FfE has therefore examined this issue in the paper “Attractiveness and Business Model Potential of the Spot Market Optimized Charging of Electric Vehicles”.
How is the attractiveness of the use case measured?
The methodology consists of three steps. Assuming that financial factors are a main motivator for using variable electricity tariffs, the first step was to conduct a literature review on acceptance studies for variable electricity tariffs and calculate an average value. This value indicates the minimum annual savings required for households to use a variable electricity tariff.
In the second step, the FfE model eFLAME was used to simulate the annual savings potential of charging with variable tariffs. Specifically, Time-of-Use (ToU) and dynamic tariffs were examined with electricity prices from 2021 and 2022.
In the third step, a revenue margin was calculated from the difference between the simulated charge cost savings and the required savings based on the acceptance studies. In case of a positive revenue margin spot market-optimized charging is worthwhile for electric vehicle drivers; they save more money than they expect. A positive revenue margin also indicates a proportionate scope for economic business models for electricity suppliers and aggregators. In contrast, a negative revenue margin indicates that the perception of the negative effects of variable electricity tariffs, a restriction on flexibility and an increased price risk, cannot be covered by the charge cost savings.
Table 1 shows the examined acceptance studies. On average, respondents expect to save €183.3 per year when using a variable electricity tariff. Investments in technical equipment, such as a wallbox, a smart meter or an energy management system, were not considered.
| Authors | Method | Target grup | Sample size | Type of tariff | Required charge cost reduction Study | Required charge cost reduction Converted [€ / a]a |
| Dütschke und Paetz (2013) | Field experiment with test residents | consumers already familiar with dynamic pricing programs | 4 | ToU & dynamic | 50 – 150b | 50 – 150b |
| Ensslen et al. (2014) | Survey | French and German EV drivers and respondents without EV experience | 70 | Two-level smart charging tariff | 28,5 %a | 252,1a |
| Will und Schuller (2016) | Survey | Early adopters of EV technology | 237 | Discount on monthly base price | 21,4 % | 189,3 |
| Hinterstocker et al. (2018) | Survey | Residential electricity customers | 130 | ToU | 110 | 110 |
| Scherrer et al. (2019) | Survey | EV drivers (early adopters) | 432 | Variable tariff in general | 30 % | 265,3 |
| a Average household electricity price 32.16 ct/kWh, annual vehicle energy consumption 2,750 kWh b Smart charging service provider controls charging process. | ||||||
Table 1: Overview of acceptance studies and required annual cost savings to use a variable tariff
Table 2 compares the simulated revenue potential from charging with a variable electricity tariff according to spot market prices. To illustrate the range of results, the minimum and maximum values are shown in addition to the average value. With a dynamic tariff, optimized charging can achieve average savings of €197.5 per EV in 2021 and €421.6 per EV. The savings with a ToU-tariff are significantly lower at €68.7 in 2021 and €122.8 in 2022.
| Jahr | Tarif | Min | Ersparnis € Max. | Ersparnis € Durchschnitt |
| 2021 | statisch variabel | 4,3 | 194,5 | 69,7 |
| 2021 | dynamisch | 30,6 | 386,3 | 197,5 |
| 2022 | statisch variabel | 7,6 | 343,5 | 122,8 |
| 2022 | dynamisch | 54 | 813,1 | 421,6 |
Table 2: Simulated Charge Cost Savings
The higher savings potential using a dynamic tariff can be explained by a better possibility of load shifting in times with low price signals. The more dynamic the tariff, the higher the price risk for electricity customers.
In the final step, the revenue margin was calculated by subtracting the required compensation for electric vehicle drivers from the simulated savings potential from charging with a variable tariff. For a dynamic tariff, the average revenue margin is €14.2 per year in 2021 and €238.3 per year in 2022. For a ToU tariff, the revenue margin is negative with €-113.6 per year in 2021 and €-60.5 per year in 2022.
The results show that charging electric vehicles with a dynamic tariff is attractive, while this is not the case for a ToU tariff. The business model potential for electricity suppliers and aggregators is higher for customers who use a dynamic tariff, as the revenue margin enables a higher revenue share in this case.
The content described was developed by FfE in the “Trade-EVs II” project funded by the German Federal Ministry for Economic Affairs and Climate Protection (BMWK) and presented at the 8th Electric Vehicle Conference in Edinburgh (EVC 23) (funding reference: 01MV20006E).
Further Information:
- Trade-EVs II – Trade of Renewable, Aggregated and Distributed Energy by Elektric Vehicles
- eFlame – electric Flexibility assessment modeling environment
- Use Cases, Players & Target Groups: Into the Future of Controlled Charging with SAP, EWS, and Nextmove
- What is an Aggregator in Trade-EVs II?
Literatur:
Dütschke, E., Paetz, A.-G., 2013. Dynamic electricity pricing – Which programs do consumers prefer? Energy Policy, 59, 226-234.
Ensslen, A., Ringler, P., Jochem, P., Keles, D., Fichtner, W., 2014. About business model specifications of a smart charging manager to integrate electric vehicles into the German electricity market, 14th IAEE European Conference. Rom, Italien.
Will, C., Schuller, A., 2016. Understanding user acceptance factors of electric vehicle smart charging. Transportation Research Part C 71.
Hinterstocker, M., Beck, F., von Roon, S., 2018. Effects of Variable Electricity Rates on the Behavior of Residential Customers, 12th International Renewable Energy Storage Conference. Düsseldorf, Deutschland.
Scherrer, A., Burghard, U., Wietschel, M., Dütschke, E., 2019. Early Adopter von E-Fahrzeugen: Ladeleistungen, Eigenerzeugung und Einstellungen zum Lademanagement. Energiewirtschaftliche Tagesfragen 69. 11, 23-26.
