A Novel Charging Load Prediction and Carbon Emission Calculation Method for Electric Vehicle

Wenli Liu, Wensi Liu, Te Han, Weigang Zhao

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    With the continuous development and promotion of the new energy vehicle market, the management of charging loads for new energy vehicles has emerged as one of the focal issues in the energy domain. Rational planning for the layout of charging facilities for these vehicles, combined with effective load management, serves as a crucial approach to foster the sustainable development of the new energy vehicle sector, and also to reduce energy consumption and environmental pollution. This paper proposes a reliable methodology and system for load characteristic analysis and carbon emission computation, tailored to new energy vehicle charging scenarios. Initially, diverse charging scenarios are contemplated, encompassing residential communities, corporate campuses, public parking spaces, and highway service areas. Subsequently, depending on varied dates and meteorological conditions, models characterizing the charging load features of new energy vehicles are sequentially constructed. These models predominantly consist of an evaluation module for the time distribution of electric vehicle charging sessions and a multi-state charging demand assessment module for electric vehicles. Utilizing Monte Carlo simulations, the characteristic load curves for the targeted new energy vehicle charging scenarios are derived. Lastly, based on these characteristic curves, the charging modality, and associated carbon emission factors, the carbon emissions are calculated. The methodology presented here can effectively facilitate a comprehensive analysis and assessment of charging loads for electric vehicles across diverse scenarios, factoring in carbon emissions.

    Original languageEnglish
    Title of host publicationICSMD 2023 - International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9798350318012
    DOIs
    Publication statusPublished - 2023
    Event2023 International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2023 - Xi'an, China
    Duration: 2 Nov 20234 Nov 2023

    Publication series

    NameICSMD 2023 - International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, Proceedings

    Conference

    Conference2023 International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2023
    Country/TerritoryChina
    CityXi'an
    Period2/11/234/11/23

    Keywords

    • carbon emission calculation
    • charging load prediction
    • electric vehicle

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