Optimized planning and assessment considering multi-horizon techno-economic and environmental trade-offs: Evaluation of solar-powered EV charging infrastructure hubs for university campuses

• A techno-economic optimization and planning approach for solar-powered electric vehicles. • In addition to techno-economic optimization, environmental analysis is performed. • Proposed vehicle to grid and grid to vehicle approach for energy management. • A hybrid electric bike is designed as a benchmark to reduce dependence on fossil fuels. • Sensitivity analysis for selecting the best hybrid configurations based on different projected lifetimes. Pakistan’s transport sector accounts for 60% of the country’s fuel imports, with the National Electric Vehicle Policy (NEVP) aiming for 5.15 million EVs by 2030, which will add 6.34 TWh of grid demand. However, there is a lack of validated frameworks for scalable, renewable-integrated charging infrastructure amid high renewable energy costs and grid limitations. This study fills that gap by developing Pakistan’s first 75-bus PV-BESS-V2G system for the NUST campus, combining MATLAB stochastic EV load modeling (SOC 0.20–0.95, 500 Monte Carlo simulations, campus-specific plug-in/out patterns) with HOMER Pro optimization using actual IESCO loads (119,040 kWh/day) and irradiance (7.072 kWh/m2/day peak). Hardware validation includes a prototype hybrid electric bike with C-rate tested V2G capabilities; network analysis confirms 0.996p.u. voltage stability up to 300 EVs; sensitivity analysis considers a 25-year horizon. The optimal 100-EV setup results in an LCOE of $0.03/kWh, NPC of $9.93 million, and a 43% reduction in CO 2 emissions. This presents a scalable blueprint for NEVP’s rollout of 3000 stations, potentially saving 1 billion liters of oil imports by 2030.