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Resilience of urban public electric vehicle charging infrastructure to flooding.

ABSTRACT: An adequate charging infrastructure is key to enabling high personal electric vehicle (EV) adoption rates. However, urban flooding-whose frequency and intensity are increasing due to climate change-may be an impediment. Here, we study how geographically-correlated outages due to floods impact public EV charging networks in Greater London. While we find no appreciable impact on the ability of battery EVs to serve typical urban driving behaviors, we observe disproportionate stresses on chargers both near, and surprisingly significantly farther from, the flooded regions. For instance, we find over 50% increase in charger utilization and 260% increase in the distance to the nearest available charger in parts of Greater London over 10 km away. Concerningly, the impact is most concentrated on already-stressed sections of the network, underscoring the infrastructure's vulnerability. Finally, we develop and evaluate four strategies for city planners to enhance the flood resilience of cities' public EV charging networks.

SUBMITTER: Raman G

PROVIDER: S-EPMC9184540 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Resilience of urban public electric vehicle charging infrastructure to flooding.

Raman Gururaghav G Raman Gurupraanesh G Peng Jimmy Chih-Hsien JC

Nature communications 20220609 1

An adequate charging infrastructure is key to enabling high personal electric vehicle (EV) adoption rates. However, urban flooding-whose frequency and intensity are increasing due to climate change-may be an impediment. Here, we study how geographically-correlated outages due to floods impact public EV charging networks in Greater London. While we find no appreciable impact on the ability of battery EVs to serve typical urban driving behaviors, we observe disproportionate stresses on chargers bo ...[more]

PMID: 35680877

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Project description:Electric vehicles (EVs) are the future of the automobile industry, as they produce zero emissions and address environmental and health concerns caused by traditional fuel-poared vehicles. As more people shift towards EVs, the demand for power consumption forecasting is increasing to manage the charging stations effectively. Predicting power consumption can help optimize operations, prevent grid overloading, and power outages, and assist companies in estimating the number of charging stations required to meet demand. The paper uses three time series models to predict the electricity demand for charging stations, and the SARIMA (Seasonal Auto Regressive Integrated Moving Average) model outperforms the ARMA (Auto Regressive Moving Average) and ARIMA (Auto Regressive Integrated Moving Average) models, with the least RMSE (Root Mean Squared Error), MAE (Mean Absolute Error) and MAPE (Mean Absolute Percentage Error) scores in forecasting power demand and revenue. The data used for validation consists of charging activities over a four-year period from public charging outlets in Colorado, six months of charging data from ChargeMOD's public charging terminals in Kerala, India. Power usage is also forecasted based on wheels of vehicles, and finally, a plan subscription data from the same source is utilized to anticipate income, that helps companies develop pricing strategies to maximize profits while remaining competitive. Utility firms and charging networks may use accurate power consumption forecasts for a variety of purposes, such as power scheduling and determining the expected energy requirements for charging stations. Ultimately, precise power consumption forecasting can assist in the effective planning and design of EV charging infrastructure. The main aim of this study is to create a good time series model which can estimate the electric vehicle charging stations usage of power and verify if the firm has a good income along with some accuracy measures. The results show that SARIMA model plays a vital role in providing us with accurate information. According to the data and study here, four wheelers use more power than two and three wheelers. Also, DC charging facility uses more electricity than AC charging stations. These results can be used to determine the cost to operate the EVs and its subscriptions.

Dataset Information

Resilience of urban public electric vehicle charging infrastructure to flooding.

Publications

Resilience of urban public electric vehicle charging infrastructure to flooding.

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