On the evaluation of plug-in electric vehicle data of a campus charging network

Abstract

Abstract-The mass adoption of plug-in electric vehicles (PEVs) requires the deployment of public charging stations. Such facilities are expected to employ distributed generation and storage units to reduce the stress on the grid and boost sustainable transportation. While prior work has made considerable progress in deriving insights for understanding the adverse impacts of PEV chargings and how to alleviate them, a critical issue that affects the accuracy is the lack of real world PEV data. As the dynamics and pertinent design of such charging stations heavily depend on actual customer demand profile, in this paper we present and evaluate the data obtained from a 17 node charging network equipped with Level 2 chargers at a major North American University campus. The data is recorded for 166 weeks starting from late 2011. The result indicates that the majority of the customers use charging lots to extend their driving ranges. Also, the demand profile shows that there is a tremendous opportunity to employ solar generation to fuel the vehicles as there is a correlation between the peak customer demand and solar irradiation. Also, we provided a more detailed data analysis and show how to use this information in designing future sustainable charging facilities.

Energy Management System With PV Power Forecast to Optimally Charge EVs at the Workplace

“…Table IV presents the input parameters of the BEVs, resulting from their respective probability distributions. We can deduce from these results that average energy demand amounts to 17.65 kWh, more than double the average demand according to [21]. Furthermore, we impose identical dynamic tariffs on…”

“…The long time for which BEVs are parked at the workplace offers the possibility to charge these with locally produced PV energy. However, a recent study showed that the average energy transfer at the workplace is 8.53 kWh [21]. Since a 10 kW charger can transfer up to 80 kWh of energy to a BEV during an 8 hour workday, we can conclude that the charger will likely not be fully utilized, which in turn reduces the economic performance of the system.…”

“…The BEV fleet shows large variation in battery capacity, ranging from 22 to 90 kWh [37]. However, workplace charging tends to be used merely to extend the range of the BEV, with an average energy transfer of 8.53 kWh and standard deviation of 6.49 kWh [21]. Realistic initial and final energy content need to be selected for the case studies, which is often done by using a probability function, e.g., uniform [17], [38] or lognormal [39].…”

Analysis of the Barriers to Widespread Adoption of Electric Vehicles in Shenzhen China

“…However, considering the widespread adoption of EVs, the uptake of EVs depends more on charging access placement in the community and working place, rather than public recharging stations [40][41][42]. Second, the research showed that consumer perception of EVs could be a significant barrier to its market penetration [43,44]; however, if consumers can obtain knowledge accurately and experience electric vehicles regularly, the attitudes and willingness toward these types of vehicles will increase significantly. Furthermore, it revealed that EV car manufacturers and governments should further promote the advantages related to EV technology.…”

Techno‐economic feasibility study on electric vehicle and renewable energy integration: A case study

“…13 For example, Birnie, 14 Mouli et al, 15 and Tulpule et al 16 examined the feasibility of using solar PV systems installed on workplaces to charge private-owned EVs. Chowdhury et al, 17 Bayram et al, 18 Esfandyari et al, 19 and Ahmad and Alam 20 investigated the implications for plug-in EVs and renewable energy sources integrated at university campuses. There are studies addressing citywide data to analyze the charging behavior of private EVs owners.…”