Wind forecasting using kriging and vector auto-regressive models for dynamic line rating studies

Fan, Fulin and Bell, Keith and Hill, David and Infield, David; (2015) Wind forecasting using kriging and vector auto-regressive models for dynamic line rating studies. In: 2015 IEEE Eindhoven PowerTech Proceedings. IEEE, NLD, pp. 1-6. (https://doi.org/10.1109/PTC.2015.7232348)

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Abstract

This paper aims to describe methods to forecast wind speeds experienced around overhead lines (OHLs) in order to predict the wind cooling effect and thus the dynamic line ratings (DLRs) of OHLs. The wind speed at a particular OHL span is forecast through a kriging interpolation between the wind speed predictions produced by a vector auto-regressive (VAR) model for a limited number of weather stations at which observations have been obtained. A temporal de-trending method is used to ensure the stationarity of de-trended data from which model parameters are determined. A spatial de-trending method is adopted in a kriging model. The results show that the kriging model performs better than the inverse distance weighting (IDW) method and that the spatial de-trending makes the main contribution to the accuracy of interpolation. Furthermore, the VAR forecasting model is shown to give greater improvement over persistence than a simple auto-regressive (AR) model.

ORCID iDs

Fan, Fulin ORCID logoORCID: https://orcid.org/0000-0003-2450-6877, Bell, Keith ORCID logoORCID: https://orcid.org/0000-0001-9612-7345, Hill, David and Infield, David;
  • Item type:Book Section
    ID code:54266
    Dates:
    Date
    Event
    2 July 2015
    Published
    15 April 2015
    Accepted
    Notes:© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:11 Sep 2015 11:32
    Last modified:20 Nov 2024 01:30
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/54266
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