Decarbonising UK road-transport requires motorway service areas (MSAs) to supply increasing and diverse energy demands from battery electric vehicles (BEVs), fuel cell electric vehicles (FCEVs), and site facilities. Local renewable generation, sector coupling, and storage can reduce costs, emissions, and grid dependence, yet existing studies often simplify transport-driven demand and rarely integrate traffic uncertainty and extreme operating conditions into energy system planning. This study proposes a transport-driven integrated energy system (IES) planning framework for MSAs. A queue-aware traffic-to-energy modelling approach is first developed, where BEV and FCEV energy demands are generated through a Markov behavioural model integrated with queueing theory. Based on the simulated transport-driven energy demands, a risk-averse planning framework is established that jointly considers grid reinforcement and on-site energy infrastructure expansion. Traffic demand uncertainty is embedded through empirical chance constraints, and compound stress scenarios are evaluated using a Conditional Value-at-Risk (CVaR) formulation. The framework is applied to three representative UK MSAs—Moto Exeter, Moto Rugby, and Moto Trowell—under different transport decarbonisation pathways. Results show that the IES reduces total annualised system cost by 28.8% on average (5.0–68.4% across scenarios) while lowering carbon emissions. Under compound stress conditions, the IES also improves supply resilience, reducing electricity shortages by 34.9% and eliminating hydrogen shortages in the representative Rugby case. • A queue-aware traffic-to-energy modelling framework for motorway service areas. • Integrated electricity–hydrogen planning for transport-driven energy systems. • Empirical chance constraints capture stochastic BEV and FCEV energy demand. • CVaR-based stress scenarios evaluate energy supply resilience. • Integrated systems reduce cost and improve reliability across UK MSAs.
Yang et al. (Fri,) studied this question.