ENERGIFORSKNING-ENERGIFORSKNING

In the project "Network balancing from large parking facilities and commercial buildings", we investigate whether energy storage in the batteries in parked electric cars and management of energy use in buildings can contribute to a more flexible and thus economical use of energy. The technology for extracting electricity from the electric car's batteries and delivering it to the grid works, but the V2G charger is significantly more expensive than a normal charger. We have therefore implemented two steps in our model calculations where we first utilize the potential for managing electricity use and then use the electric car's batteries. We find that this reduces costs. The calculations also indicate that the marginal benefit of increasing the number of V2G chargers from the perspective of the owner of large parking facilities decreases. We have compared flexibility from V2G with other flexibility that can be offered in the northern European power system with the Balmorel energy system model. The number of V2G chargers required in 2040 if they alone are to cover the need for flexibility in the network is significantly more than those that can be available at airports. V2G chargers in households are potentially many more and calculations suggest that only a small proportion of these are sufficient to cover the need for flexibility. Furthermore, the analyzes show that the need is somewhat greater in countries without hydropower, e.g. Denmark. The high cost of the V2G charger will be a significant barrier. Analyzes show that the cost of V2G chargers will decrease with more manufacturers, but this requires a significant part of the market for chargers and it may take many years before the cost approaches that of ordinary chargers. We use Oslo Airport Gardermoen (OSL) as a case. At airports, it is predictable how long the car owners want to leave the car parked and thus how long the electric car batteries are available. As there are always new car owners who park their cars, we can disregard battery wear. We have 4 V2G chargers installed in car park P10 at Gardermoen. We manage the charging and discharging of cars participating in the project from NMBU in Ås. We set up a charging cycle where the car(s) are charged and discharged to complement other uses of electricity and collect data. We also collect data on the use of electricity for heating hot water at OSL. Analyzes show that the water heaters have great potential for moving loads. This will result in a significant reduction in electricity bills, of which the reduction of power peaks and thus the reduction of the power tariff in the network rental will account for the largest share of the savings. In order to use the electric car's battery to reduce power peaks and thus optimize cost reduction, we have used machine learning and found which data and algorithms give the best results. OSL is critical infrastructure and management of - and data collection from the chargers therefore required secure communication. A VPN tunnel was established between NMBU and Avinor's systems at OSL. Together with access to control codes for the V2G charger, assistance from the manufacturer of the V2G charger and IT expertise at NMBU and Avinor have been crucial. The data collection has now been extended beyond the NeX2G project and is linked to the EU project BatCat.

NeX2G is a Collaborative and Knowledge-building Project that will meet societal and industry-related challenges (KSPK). The project will investigate the potential magnitude and economic sustainability of flexibility available to the energy system from long-term parking of electrical vehicles (EVs) and commercial building assets. We will use Oslo airport Gardermoen as a case and work with real time data as basis for detailed and aggregated analysis. Airports are interesting because future power demand will increase substantially and they will in the future have a large pool of parked EVs. Five bidirectional EV chargers will be installed at the airport together with devices to collect real time data on operation and control of chargers and selected building assets. Machine learning algorithms will be used to predict the flexibility based on the collected data and experience with seamless exchange of energy, grid and flexibility services collected. Use of EVs as energy storage requires robust technical solutions, marketplace development, visualization of benefits and possibly policy incentives. Moreover, the comparison of economic benefits for the owner (Avinor) with the socioeconomic benefits and need for policy is crucial for the realisation of X2G.