Assessing flexibility from electric vehicles using an open-source energy system model: trade-offs between smart charging, vehicle-to-grid and an extensive charging infrastructure
Arven Syla, David Parra, M. Patel
Abstract
The introduction of electric vehicles (EVs) is a key strategy to decarbonise the transport sector. However, the electrification of transport increases electricity demand, thus burdening electricity grids. EVs can also provide flexibility to the energy system to enable renewable energy through smart charging, vehicle-to-grid (V2G), and an extensive charging infrastructure with more charging opportunities away from home. This study analyses the complementarity among these three strategies by extending GRIMSEL, an open-source energy optimization model of Switzerland's energy system with its neighbouring countries. Our results show that implementing any flexibility option enables PV, reduces stationary battery installations, while also reducing overall system costs. Specifically, smart charging increases optimal PV capacity by 6 % and reduces storage needs by 19 %. Interestingly, V2G operates strategically by providing electricity during peak periods, and reducing battery storage needs between 21 and 37 % on average. Additionally, an extensive charging infrastructure including commercial, at work, and public charging, reduces the need for additional PV and battery storage by 12 % and 66 %, respectively, i.e. delivering congestion relieve. Overall, a combination of flexibility options can reduce overall system costs by up to 29 %. Policymakers and energy stakeholders may use these insights to tailor solutions depending on their specific policy targets. • Open-source energy model expanded to assess trade-offs among EV flexibility options. • Smart charging increases optimal installed PV (6 %) and reduces battery storage (19 %). • V2G acts strategically by reducing battery storage needs (21–37 %). • Extensive (distributed) charging infrastructure reduces storage needs by up to 66 %. • Flexibility options reduce overall system (21 %) and electricity costs (133–105 €/MWh).