Multi-objective long-term expansion planning of electric vehicle infrastructures integrated with wind and solar units under the uncertain environment considering demand side management: A real test case

Jirdehi, Mehdi Ahmadi; Tabar, Vahid Sohrabi

doi:10.1016/j.scs.2023.104632

Cited by 15 publications

(1 citation statement)

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“…Shen et al (2022) [3] worked on the use pattern of EVs and load forecasting. Jirdehi et Tabar (2023) [4] optimized EV infrastructures integrated with renewable energies and implemented a demand-side strategy considering uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Integrated Photovoltaics Potential for Passenger Cars: A Focus on the Sensitivity to Electrical Architecture Losses

et al. 2023

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Vehicle integrated photovoltaics (VIPV) are among the identified solutions to reduce the environmental impacts of the transport sector. The model developed here simulates the VIPV system. It considers various usage patterns and vehicle types, several characteristics of the photovoltaic system and all the losses that may decrease energy yield. Focusing on a passenger car, simulations indicate the order of influence of the parameters on the outputs of the model: geographic locality, shading, thresholds due to extra-consumption needed to charge the vehicle’s battery from the photovoltaic (PV) system and occurrence of recharge with the grid. With technology projections for 2030, with 30% shading, VIPV will cover a distance of up to 1444 km per year. This represents up to 12% of the driven mileage. For the best month, it can reach up to 14 km/day. For average Europe and realistic conditions, VIPV cover 648 km per year. Life cycle assessment (LCA) of a solarized passenger car shows a negative balance for a low-carbon electricity mix and average solar irradiance. In favorable conditions, the carbon footprint is up to 489 kg of CO2-equivalent avoided emissions on a 13-year lifespan. Beyond the focus on km and LCA, VIPV may provide useful functions in non-interconnected zones and for resilience in disaster areas.

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Section: Introductionmentioning

confidence: 99%