• Login
    View Item 
    •   Shocker Open Access Repository Home
    • Engineering
    • Electrical Engineering and Computer Science
    • EECS Faculty Scholarship
    • EECS Research Publications
    • View Item
    •   Shocker Open Access Repository Home
    • Engineering
    • Electrical Engineering and Computer Science
    • EECS Faculty Scholarship
    • EECS Research Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Solar power prediction in different forecasting horizons using machine learning and time series techniques

    Date
    2021-07-01
    Author
    Pun, Kesh B.
    Basnet, Saurav Man Singh
    Jewell, Ward T.
    Metadata
    Show full item record
    Citation
    Pun, K., Basnet, S. M. S., & Jewell, W. (2021). Solar power prediction in different forecasting horizons using machine learning and time series techniques. Paper presented at the 2021 IEEE Conference on Technologies for Sustainability, SusTech 2021, doi:10.1109/SusTech51236.2021.9467464
    Abstract
    Solar power generation is highly intermittent, nonlinear, and variable in nature. The increase in penetration level of solar energy resources poses technical challenges. An accurate forecasting model is crucial to minimizing these technical issues. Therefore, choosing the right forecasting technique for the right forecasting horizon is vital. In this study, the performance analysis of machine learning and time series forecasting techniques for various forecasting horizons has been investigated. Its accuracy, root mean square error (RMSE), and mean absolute error (MAE) have been compared to other techniques.
    Description
    Click on the DOI link to access this conference paper at the publishers website (may not be free).
    URI
    https://doi.org/10.1109/SusTech51236.2021.9467464
    https://soar.wichita.edu/handle/10057/22136
    Collections
    • EECS Research Publications

    Browse

    All of Shocker Open Access RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsBy TypeThis CollectionBy Issue DateAuthorsTitlesSubjectsBy Type

    My Account

    LoginRegister

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    DSpace software copyright © 2002-2023  DuraSpace
    DSpace Express is a service operated by 
    Atmire NV