Sustainable urban energy dynamics: Integrating renewable energy and electric vehicles in a European context

• Stochastic model simulates EV-grid dynamics on low-RES days in 2035 and 2050. • Four FES scenarios tested with real-world EV charging and usage behaviour. • V2G improves energy balance but cannot fully close future energy gaps. • Falling Short shows 97% of EVs uncharged on low-renewable days by 2050. The rapid adoption of electric vehicles (EVs) presents significant challenges to urban energy networks due to increased demand and potential overloading risks. Integrating renewable energy sources (RES) offers a sustainable solution, reducing carbon emissions while meeting future energy needs. Using Nottingham, UK, as a representative case within a broader European urban energy context, this study investigates the interactions between EVs, RES, and urban energy systems, focusing on supply–demand dynamics under constrained renewable output conditions. A stochastic modelling approach, guided by the Future Energy Scenarios (FES) developed by the National Energy System Operator (NESO), is employed to analyse EV-RES integration under four distinct scenarios — Consumer Transformation, System Transformation, Leading the Way, and Falling Short — projected for 2035 and 2050. Key focus areas include balancing energy supply and demand, managing peak loads, and utilising Vehicle-to-Grid (V2G) technology to address grid stability issues. Results demonstrate the heightened challenges of integrating EVs on days with suboptimal renewable energy generation, where energy shortfalls exacerbate system strain. By 2050, low renewable energy generation days aggravate energy shortfalls, emphasising the importance of V2G. In the most constrained scenario, up to 97 % of EVs remain uncharged or partly charged, demonstrating the risk of severe energy deficits. Conversely, in an ambitious renewable energy scenario, significant renewable utilisation is achieved but is accompanied by challenges such as overgeneration and energy management complexities.