Economic and environmental assessment of solar energy harvesting and vehicle charging strategy for transportation electrification

Rapid electrification of the transportation sector creates both opportunities and challenges for transportation infrastructure owners as they work to reduce greenhouse gas emissions and improve system sustainability. Heavy-duty vehicle (HDV) electrification, in particular, demands major investments in transmission, distribution, and electronic and power infrastructure, along with reliable low or zero-carbon energy supply strategies that maintain operational feasibility, minimize lifecycle environmental impacts, and reduce demand on the power grid. This dissertation investigates sustainable energy harvesting solutions and evaluates alternative charging strategies through integrated life-cycle cost analysis (LCCA) and life-cycle assessment (LCA) frameworks to support effective decision-making for transportation electrification. First, this study develops and applies a comprehensive framework to quantify the techno-economic and environmental performance of photovoltaic noise barriers (PVNBs) as energy-harvesting infrastructure. Multiple design configurations are evaluated across diverse geographic locations, and predictive models are developed for each configuration to enable rapid energy assessment. This analysis is further integrated with a decision-support methodology that incorporates economic feasibility, operational constraints, and social considerations. Together, these components allow agencies to evaluate PVNBs not only as renewable energy assets, but also as multifunctional infrastructure that can provide additional operational and economic value.Second, the dissertation investigates charging strategies for battery electric buses (BEBs) within a major NJ Transit garage by modeling real-world energy consumption using operational data and transit schedules. Strategies to support bus electrification including fleet expansion, and opportunity charging using different technologies, are assessed through LCCA and LCA. The analysis identifies the most economical solution capable of maintaining service-level obligations while reducing long-term economic and environmental impacts. The methodological contribution lies in linking real operational data, complex bus scheduling, and different charging technologies performance to generate long-term cost and environmental outcomes.Finally, the study introduces a comparative systems-level evaluation of electric heavy-duty vehicle (eHDV) charging strategies along a long freight corridor. Dynamic wireless power transfer lane (eRoad) and fast plug-in charging are modeled using traffic data per vehicle class, and their respective speeds and energy consumption. Sensitivity analyses on technology maturity, battery size reduction, and renewable energy integration highlight the conditions under which each strategy becomes economically and environmentally advantageous.Overall, this dissertation provides infrastructure owners in the transportation sector with a suite of data-driven insights and integrated frameworks for evaluating emerging clean transportation technologies. Together, these contributions enhance the ability to pursue resilient, cost-effective, and low-carbon infrastructure strategies, supporting the broader transition to an sustainable electrified transportation system.