High-powered charging strategy could help Berlin reduce cost, absorb more renewables

30 September 2022, Anders Hove

Source: AdobeStock/517750156

According to the 2017 Mobility in Germany study, Germany may have over 30% EVs in its overall vehicle stock by 2030. Expanding electric vehicle charging infrastructure is essential to electrifying transport, and larger vehicles such as buses and trucks need more high powered charging (HPC) infrastructure, which requires substantial capital investment. How can those investments meet customer needs at the lowest cost, while also remaining friendly to the grid and helping absorb variable renewable energy, like wind and solar?

To answer these questions, the Reiner Lemoine Institute (RLI) conducted a modeling and stakeholder interview study to determine the best options and layout for Berlin’s future HPC infrastructure. RLI undertook the study under the Sino-German Energy Transition project, as part of a larger effort to compare and contrast EV charging deployment in Germany and China.

In this article, we summarize the results of the analysis for high-power charging in Berlin. In a subsequent article, we will summarize the findings of our study of high-power charging in Shenzhen.

For Berlin, RLI’s analysis shows that depot charging works best for buses and many other fleets, while passenger cars and logistics vehicles will rely on a mix of depot and public charging of various configurations. Optimization of charging can enable a substantial reduction in investment costs while still meeting almost all charging needs.

Berlin’s public bus operator, BVG, aims to decarbonize its entire bus fleet by 2030. BVG prioritizes depot charging at low power levels to reduce peaks in power consumption, and thereby reduces cost for both peak loads and for charging station investments. Not only are low-power chargers cheaper, they also have lower personnel costs. HPC is most relevant for terminal stations (stops at the end of bus lines, as distinct from depots where buses return at night) and HPC at terminals is necessary for achieving full operational capability during the almost 10,000 bus trips per week in Berlin.

Various Berlin-region commercial fleet operators are also converting to electric vehicles through the WELMO facility (Wirtschaftsnahe Elektromobilität), a funding program coordinated by the Senate. Logistic fleets interviewed in this study also favor depot charging as it best fits their utilization patterns. However, several logistics fleet operators report their vehicles are operated by independent subcontractors that cannot rely on depot charging, and instead require public charging options.

Private passenger cars will access HPC under various specific use cases, depending on various degrees of access to residential and workplace charging. Private passenger vehicle HPC also depends on incentives and external factors, such as overall public charging pricing, as well as time-of-use pricing.

HPC load depends on design of charging incentives

Germany classifies charging according to seven use cases displayed below. Use Case 4 represents HPC at urban charging hubs or depots, typically at speeds up to 150 kW. Use Case 5 covers HPC at speeds as high as 350 kW at charging stations along major roads and highways. In contrast, Use Case 6 covers fast charging (DC or AC) at public charging stations at parking lots or shopping centers, while Use Case 7 covers slower public charging, either in parking lots or in on-street parking.

Public and private charging use cases defined by German government

Source: RLI 2022

RLI’s analysis developed two charging scenarios for private vehicle charging customers based on whether charging incentives encourage customers to focus on HPC or on low-power charging. Under the HPC+ scenario, time-of-use pricing and other pricing discounts encourage users to shift charging towards HPC, and under the PrivateCharging+ scenario, incentives encourage charging at home, workplaces, or slow-charging facilities.

Similarly, RLI developed two charging scenarios for public buses. In the first scenario, bus fleets focus on charging overnight at depots, while still charging at terminals when absolutely necessary, such as on longer routes. In the second, bus fleets shift more charging load to HPC at terminals at the ends of their routes, while still charging at depots overnight.

The modeling shows that focusing on HPC versus slow charging results in similar daily charging load curves, but substantially increases the midday charging load in the Berlin region by up to 15%.

Weekly EV charging load for Berlin, depending on charging focus (slow vs HPC)

Source: RLI 2022

Focusing on HPC also substantially increases the demand for HPC charging points. Under the HPC+ scenario, RLI’s model suggests the need for over 4000 ultra-fast chargers up to 350 kW at major highways and roads, versus around 1500 under the scenario where users focus on slow charging. In our view, the investment cost of this scenario would be prohibitively high. However, RLI’s modeling suggests that incorporating reservations and scheduling into HPC infrastructure to postpone roughly 10% of high-power charging events would substantively reduce the need for high-power charging points.

Need for high-power charging points depending on share of charges met with flexible timing

Source: RLI 2022

Adding flexibility also substantially reduces the peak load at HPC stations, from over 150 MW if HPC meets charging demand immediately for every user wishing to charge, versus under 70 MW if 10% of chargers are delayed or shifted to slow chargers. In other words, scheduling or reservation systems could reduce peak load from HPC by over 50%.

Peak charging load from HPC depending on percentage of flexible load

Source: RLI 2022

Charging from renewables has high potential

Berlin currently has limited renewable energy production, but by 2030 Berlin’s overall region, including Brandenburg, is likely to have substantial wind and solar production, given Germany’s renewable energy goals. The Berlin area has a total rooftop solar potential of 8.9 GW of PV. EV charging could play a role in absorbing renewable energy, but this depends on how vehicles charge. HPC could be even more critical: On one hand, HPC charging loads are even more variable, posing a greater challenge for the grid. On the other, fleets that access HPC could respond well to incentives to favor charging from renewables.

In June 2022 the German parliament amended the existing Energy Industry Act by providing incentives to integrate EVs, as well as heat pumps, into the electricity grid. The law calls for new incentives to reduce costs for consumers that make their EV charging facilities available to grid operators for storage and balancing. The law does not specify the incentives in detail, the actual design and implementation is currently under development by the grid regulator, BNetzA.

RLI’s analysis of wind and solar in the Berlin region suggests that smart charging of buses could help increase the percentage of charging electricity from clean energy. HPC load is likely to concentrate in the midday, at times when the Berlin region will likely have excess wind and solar output in both winter and summer. Indeed, excess renewable output is far larger than the load from high-power charging.

However, the demand for charging in the early evening implies the region would still need energy storage capacity to enable full charging from renewables—especially on days with low wind output.

The graph below displays an approximation of the excess renewable output (renewable output after subtracting local load, excluding charging loads) in the Berlin region in winter and summer in 2030, compared to the charging load from HPC under two scenarios. In the first scenario (green curve), busses mainly (but not exclusively) charge in depots overnight, and private passenger cars mainly (but not exclusively) charge at private chargers, either at home or work. In the second scenario (red curve), due to various pricing incentives, private passenger vehicles have a greater tendency to charge at public HPC stations, while buses shift some charging away from depots and towards opportunity charging at terminals on their routes. Therefore, the second scenario features higher midday charging load and lower nighttime load for both private passenger vehicles and buses.

Excess renewable energy output and charging loads in Berlin region in 2030 average week


Source: RLI 2022

As the chart shows, excess renewable output is an order of magnitude higher than the peak charging load in the Berlin region, under either of the two charging scenarios. However, renewable output curves suggest that on several days in both winter and summer the excess renewable output in the region would fall below zero in the early evening on five days out of a typical week.

This shortfall in renewable energy output could be met by standalone energy storage, operated centrally to support the grid; by storage located at charging stations; or via vehicle-to-grid (V2G) technology. This study did not explicitly model V2G, but the graph suggests that maximizing the use of midday renewable energy for charging would require shifting charging loads from evening to midday, and therefore increasing the overall size of the grid connection for charging infrastructure. This is the opposite of present practices, where charging providers typically adopt storage to reduce charging load peaks at midday by shifting load to off-peak hours.   


There are three important takeaways from this analysis:

  • First, optimizing investment costs while meeting charging needs will require greater attention to smart charging through pricing incentives, reservation functions on charging apps, and scheduling for fleets. Such incentives are important for both private and fleet owners. While private owners may be less responsive to scheduling incentives, the larger load from private vehicle charging makes this a critical factor for reducing public charging investment needs.
  • Second, there is a big difference between charging practices aimed at reducing peak charging loads versus absorbing more renewable energy. In the Berlin region, HPC could play a role in absorbing midday excess renewable energy production, but concentrating more charging load at midday would require more investment in distribution capacity. Balancing these extra costs will be a complex exercise.
  • Third, energy storage will be required to absorb midday surplus renewable energy in the Berlin region for use in the early evening. Central storage at or near renewable energy production sites are one potential option. Storage sited at charging locations could facilitate evening charging from renewables. Fleet vehicles in some cases could provide V2G services.

Finally, while this analysis focuses on modeling, sector coupling also requires greater stakeholder involvement and coordination across sectors that currently are relatively independent. This will be the focus of our next analysis, looking at the lessons of Shenzhen for Berlin and other cities adopting EV charging infrastructure.

To implement the analysis on high power charging, the GIZ-implemented Sino-German Energy Transition project cooperated with two research partners: The China Society of Automotive Engineers (SAE) supported with stakeholder interviews and modeling usage scenarios to investigate the integration of RE and development pathways of HPC infrastructure in Shenzhen. The Reiner Lemoine Institute (RLI) examined HPC development and future charging scenarios in Berlin. The research is carried out under the framework of the Sino-German Energy Transition Project commissioned by the German Federal Ministry for Economic Affairs and Climate Action (BMWK), implemented by GIZ.