• Login
    View Item 
    •   Home
    • Office of Sponsored Research (OSR)
    • KAUST Funded Research
    • Publications Acknowledging KAUST Support
    • View Item
    •   Home
    • Office of Sponsored Research (OSR)
    • KAUST Funded Research
    • Publications Acknowledging KAUST Support
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of KAUSTCommunitiesIssue DateSubmit DateThis CollectionIssue DateSubmit Date

    My Account

    Login

    Quick Links

    Open Access PolicyORCID LibguideTheses and Dissertations LibguideSubmit an Item

    Statistics

    Display statistics

    Short-Term Wind Speed Forecasting for Power System Operations

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Type
    Article
    Authors
    Zhu, Xinxin
    Genton, Marc G. cc
    KAUST Grant Number
    KUS-C1-016-04
    Date
    2012-04-10
    Online Publication Date
    2012-04-10
    Print Publication Date
    2012-04
    Permanent link to this record
    http://hdl.handle.net/10754/599363
    
    Metadata
    Show full item record
    Abstract
    The emphasis on renewable energy and concerns about the environment have led to large-scale wind energy penetration worldwide. However, there are also significant challenges associated with the use of wind energy due to the intermittent and unstable nature of wind. High-quality short-term wind speed forecasting is critical to reliable and secure power system operations. This article begins with an overview of the current status of worldwide wind power developments and future trends. It then reviews some statistical short-term wind speed forecasting models, including traditional time series approaches and more advanced space-time statistical models. It also discusses the evaluation of forecast accuracy, in particular, the need for realistic loss functions. New challenges in wind speed forecasting regarding ramp events and offshore wind farms are also presented. © 2012 The Authors. International Statistical Review © 2012 International Statistical Institute.
    Citation
    Zhu X, Genton MG (2012) Short-Term Wind Speed Forecasting for Power System Operations. International Statistical Review 80: 2–23. Available: http://dx.doi.org/10.1111/j.1751-5823.2011.00168.x.
    Sponsors
    This research was partially supported by NSF grant DMS-1007504 and by Award No. KUS-C1-016-04 made by King Abdullah University of Science and Technology (KAUST). The authors thank the editor, an associate editor, four reviewers, Amanda Hering and Le Xie for valuable comments that have improved this article.
    Publisher
    Wiley
    Journal
    International Statistical Review
    DOI
    10.1111/j.1751-5823.2011.00168.x
    ae974a485f413a2113503eed53cd6c53
    10.1111/j.1751-5823.2011.00168.x
    Scopus Count
    Collections
    Publications Acknowledging KAUST Support

    entitlement

     
    DSpace software copyright © 2002-2023  DuraSpace
    Quick Guide | Contact Us | KAUST University Library
    Open Repository is a service hosted by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items. For anonymous users the allowed maximum amount is 50 search results.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.