Norges Forskningsråd - Kompetansebyggende prosjekt for næringslivet (KSP)
About
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 are 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 realization of X2G.
Results
The grid benefits of vehicle-to-grid in Norway and Denmark: An analysis of home- and public parking potentials
Niels Oliver Nagel, Eirik Ogner Jåstad, Thomas Martinsen
Energy 293 (2024), 130729
https://doi.org/10.1016/j.energy.2024.130729Abstract
This study provides an analysis of the potential benefits of bi-directional charging of electric vehicles (V2G) and its implications for the energy sector using the Balmorel energy system model. We compare results from V2G scenarios to those of smart charging scenarios, specifically focusing on the target year 2040. The study explores specific cases: large-scale adoption of V2G for home charging and small-scale adoption at public airport parking lots. Two market regions, Norway and Denmark, are in focus and shed light on how different energy mixes affect the results. Findings show that large-scale V2G adoption has the potential to significantly affect prices in the analyzed price regions. V2G helps decrease price volatility, reduce peak and valley electricity prices, reduce renewable curtailment, and reduce the cost of operation in the energy system. The spread between charging and discharging prices is highest in the case of small-scale adoption and in regions with less inherent power system flexibility. Large-scale adoption leads to diminishing V2G returns. Also, more inherent power system flexibility competes with V2G. In the flexible Norwegian price regions, V2G may increase average electricity prices, leading to a tradeoff between societal and consumer welfare.Smart charging of electric vehicles based on scheduling theory
Heidi S. Nygård, Ingrid Maria Mørch, Olvar Bergland27th International Conference on Electricity Distribution (CIRED 2023), pp 3889-3893
Abstract
Reducing energy related costs by better timing demand for power is a rapidly growing concept due to increased and more fluctuating energy prices. One way to achieve this is through smart charging of electric vehicles (EVs). In the present work, a python-based program has been developed based on scheduling theory and tailored to the specific objectives of charging at a long-term parking facility. Basic building blocks of the theory were assessed to explore the possibility of combining them into a useful model of the problem. The simulation yields example schedules where charging is restricted to night-time and no more EVs than necessary are charged simultaneously, without compromising the constraint of fully charged vehicles at predefined due dates.Load scheduling and V2G to minimize power demand - exploring potential for airport parking facility, Norway
Thomas Martinsen, Georg Devik, Heidi S. Nygård27th International Conference on Electricity Distribution (CIRED 2023), pp 3324-3327
Abstract
Electrification of transport introduces challenges but also opportunities. The challenges are increased power demand and possibly grid investment causing additional power demand cost for charging. However, electric vehicles are idle for long time periods, particularly at airport parking. This provides opportunities for scheduled charging in order to minimize power charges. We have developed an algorithm giving priority to charging the electric vehicle(s) closest to departure while minimizing monthly average power demand. We are applying the algorithm to data from a parking facility in the Oslo airport vicinity. We explore the potential for reaching the minimum average monthly power demand through scheduling and discuss briefly the cost and benefits of introducing V2G. The results indicate that all EVs may be charged with only a small increase in the monthly average power demand and V2G would not provide further benefits for the parking facility owner with the current power tariff in Norway.The potential for load shifting with flexible EV charging at Oslo Airport Gardermoen
Åshild Grøtan, Thomas Martinsen, Rasmus Gåsemyr Tveitane, Heidi S. Nygård
CIRED Port Workshop 2022: E-mobility and power distribution systems, p. 975-979Abstract
Flexible charging as a load-shifting asset was explored using energy data from a parking facility with electric vehicle (EV) chargers at Oslo Airport Gardermoen (OSL) in Norway. The parking facility is an interesting candidate for flexible charging, as 60% of the charging sessions last for more than 24 hours. We investigated the potential to reduce the building’s peak load using scheduled EV charging. Monte Carlo simulations were used to model load shifting of EV charging based on historical parking data. Several scenarios were simulated, with variations in charging power, volume, duration, and the number of charging sessions. In every scenario the method successfully reduced the building’s highest loads, and in most scenarios the simulation almost completely avoided charging during the peak load hours. Overall, the study shows that there is a large amount of power flexibility in parked EVs at OSL, and that relatively simple distribution methods for charging can reduce the highest loads. Even with a larger number of charging sessions, the method used in this study would lower peak loads, although the uncertainties are greater for these scenarios.
Master's theses
We offer master's theses i this projects for students at MINA and REALTEK, NMBU.
Previous English theses:
Predicting electricity demand using machine learning: Case study of Oslo Airport Gardermoen (Sigurd Grøtan, 2023)
Zero emission airport, OSLO Gardermoen - future energy use and combination of energy carriers (Lenka Ouro Akpo Vrabel, 2023)
Deep reinforcement learning for vehicle-to-grid control of long-term parked EVs: A case study of Oslo airport Gardermoen (Filip Kristoff Ørn, 2022)
Power Peak Shaving: How to Schedule Charging of Electric Vehicles and Organize Mutually Beneficial Vehicle to Grid (V2G) (Ingrid Maria Mørch, 2022)
Importance of drivers and barriers for V2G? (Tamara Nørreskov Aasebøe, 2021)
Previous Norwegian theses:
Utfordringer og muligheter med elbiler og effektivisering i fremtidens energisystem (Marie Eide Roalkvam, 2024)
Simulering av styringsalgoritmer for lastflytting av industrielle varmtvannsberedere på Oslo Lufthavn Gardermoen (Njål Kolberg Olsen, 2023)
Kostnadsutvikling og potensiale for toveis veggladere og V2G-teknologi: En analyse av komponentene og mulig kostandsutviklingen og potensialet for bidrag til strømforsyningen fra elbilparken (Tor Alexander Guldal, 2023)
Utfordringer i distribusjonsnettet ved elektrifisering av veitrafikken (Tomas Løkken, 2023)
Potensial for redusert effektuttak ved ladeplan av elbiler på en langtirdsparkeringsplass: en studie av Gardermoen Parkering (Georg Devik, 2022)
Prediksjon av elektrisitetsbruk i næringsbygg: Casestudie av Oslo Lufthavn Gardermoen (Kjersti Rustad Kvisberg, 2022)
Fleksibilitet i parkerte elbiler ved næringsbygg : en casestudie av Oslo lufthavn Gardemoen (Rasmus Gåsemyr Tveitane, 2021)
Researchers
The project is coordinated by MINA, and is a collaboration between MINA and REALTEK at NMBU.
External partners:
- Statnett
- OsloMet
- Avinor
- Elvia
- lnett
NMBU researchers
Mads Greaker
OsloMet