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.