Internet of Things based real-time electric vehicle load forecasting and charging station recommendation

Fernández, Santiago; Vijayakumar, K.; Ali, Jagabar Sathik Mohamed; Ali, Ziad M.; Aleem, Shady H. E. Abdel

doi:10.1016/j.isatra.2019.08.011

Cited by 118 publications

(54 citation statements)

References 42 publications

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“…Due to a planned increase in electric car fleets globally, intensive research was also directed for the potential usage of IoT technologies for the smart charging of electric vehicles. Real time IoT based forecasting applications were proposed in ( Savari et al., 2020 ) for a more efficient charging process of electric vehicles. The application allowed better scheduling management where the waiting time was minimized, which improved the overall charging economy as well as charging time.…”

Section: Iot Technologies In Sustainable Energy and Environmentmentioning

confidence: 99%

Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future

Nižetić

Šolić

López-de-Ipiña

et al. 2020

Journal of Cleaner Production

640

165

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The rapid development and implementation of smart and IoT (Internet of Things) based technologies have allowed for various possibilities in technological advancements for different aspects of life. The main goal of IoT technologies is to simplify processes in different fields, to ensure a better efficiency of systems (technologies or specific processes) and finally to improve life quality. Sustainability has become a key issue for population where the dynamic development of IoT technologies is bringing different useful benefits, but this fast development must be carefully monitored and evaluated from an environmental point of view to limit the presence of harmful impacts and ensure the smart utilization of limited global resources. Significant research efforts are needed in the previous sense to carefully investigate the pros and cons of IoT technologies. This review editorial is partially directed on the research contributions presented at the 4th International Conference on Smart and Sustainable Technologies held in Split and Bol, Croatia, in 2019 (SpliTech 2019) as well as on recent findings from literature. The SpliTech2019 conference was a valuable event that successfully linked different engineering professions, industrial experts and finally researchers from academia. The focus of the conference was directed towards key conference tracks such as Smart City, Energy/Environment, e-Health and Engineering Modelling. The research presented and discussed at the SpliTech2019 conference helped to understand the complex and intertwined effects of IoT technologies on societies and their potential effects on sustainability in general. Various application areas of IoT technologies were discussed as well as the progress made. Four main topical areas were discussed in the herein editorial, i.e. latest advancements in the further fields: (i) IoT technologies in Sustainable Energy and Environment, (ii) IoT enabled Smart City, (iii) E-health – Ambient assisted living systems (iv) IoT technologies in Transportation and Low Carbon Products. The main outcomes of the review introductory article contributed to the better understanding of current technological progress in IoT application areas as well as the environmental implications linked with the increased application of IoT products.

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Section: Iot Technologies In Sustainable Energy and Environmentmentioning

confidence: 99%

Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future

Nižetić

Šolić

López-de-Ipiña

et al. 2020

Journal of Cleaner Production

640

165

View full text Add to dashboard Cite

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“…Finally the current markets are assessed and the correlation between the public focus and the adoption of Electric Supply equipment is studied. Conclusion of the report ends with a discussion on the methods, operation, planning, impact, economy of the growth of the Plug-in Hybrid Electric Vehicle charging supply equipment and infrastructure [8][9][10][11][12]. The customers should be encouraged to use the fast charging stations not at the high peak hours of the day when large traffic is present.…”

Section: Literature Surveymentioning

confidence: 99%

A two stage battery charger for EV charging applications

Kalyanasundaram¹,

Fernandez²,

Vijayakumar³

et al. 2020

IJEECS

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Electric power generation and consumption are indicating an unprecedented change in recent decades. Electrical power industry and transportation sector lie at the core of this development and hence this change. This change is one of the major causes of polluting environmental and global warming. So, to decrease the dependency on conventional fuels and greenhouse gas emissions, countries around the globe are actively finding alternative energy resources. It will help to develop clean and green energies to build a sustainable society. Simultaneously, energy utilization in the field of transportation is witnessing a change from fossil fuel to electricity-based fuel. Electrified transportation system is a solution to endorse sustainable energy development and addressing environmental pollution, global warming issues. In this paper, an EV battery charger is designed with a two-stage charging model to achieve good efficiency. The design is simulated by using MATLAB simulation and compared with the existing model. The simulation results show that the proposed model is superior to the traditional model.

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“…To maintain the reliability of the power grid, it is crucial to have an accurate forecasting model that predicts the key indicators based on power consumption patterns, such as electric power load. In this regard, there have been a number of studies attempted to forecast the short-term load by using machine learning models [3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…However, this study did not provide a clear conclusion on which dataset and prediction techniques lead to better prediction performance. Beyond the EV load forecast, in Reference [7], the authors proposed a real-time charging station recommendation method for EVs, considering the economic cost and reduced charging time.…”

Section: Introductionmentioning

confidence: 99%

Improving Load Forecasting of Electric Vehicle Charging Stations Through Missing Data Imputation

Lee

Ahn

2020

Energies

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As the penetration of electric vehicles (EVs) accelerates according to eco-friendly policies, the impact of electric vehicle charging demand on a power distribution network is becoming significant for reliable power system operation. In this regard, accurate power demand or load forecasting is of great help not only for unit commitment problem considering demand response but also for long-term power system operation and planning. In this paper, we present a forecasting model of EV charging station load based on long short-term memory (LSTM). Besides, to improve the forecasting accuracy, we devise an imputation method for handling missing values in EV charging data. For the verification of the forecasting model and our imputation approach, performance comparison with several imputation techniques is conducted. The experimental results show that our imputation approach achieves significant improvements in forecasting accuracy on data with a high missing rate. In particular, compared to a strategy without applying imputation, the proposed imputation method results in reduced forecasting errors of up to 9.8%.

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Internet of Things based real-time electric vehicle load forecasting and charging station recommendation

Cited by 118 publications

References 42 publications

Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future

Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future

A two stage battery charger for EV charging applications

Improving Load Forecasting of Electric Vehicle Charging Stations Through Missing Data Imputation

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