Short-Term Wind Speed Forecasting for Power System Operations

Handle URI:
http://hdl.handle.net/10754/599363
Title:
Short-Term Wind Speed Forecasting for Power System Operations
Authors:
Zhu, Xinxin; Genton, Marc G.
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.
Publisher:
Wiley-Blackwell
Journal:
International Statistical Review
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
Apr-2012
DOI:
10.1111/j.1751-5823.2011.00168.x
Type:
Article
ISSN:
0306-7734
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.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorZhu, Xinxinen
dc.contributor.authorGenton, Marc G.en
dc.date.accessioned2016-02-28T06:05:36Zen
dc.date.available2016-02-28T06:05:36Zen
dc.date.issued2012-04en
dc.identifier.citationZhu 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.en
dc.identifier.issn0306-7734en
dc.identifier.doi10.1111/j.1751-5823.2011.00168.xen
dc.identifier.urihttp://hdl.handle.net/10754/599363en
dc.description.abstractThe 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.en
dc.description.sponsorshipThis 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.en
dc.publisherWiley-Blackwellen
dc.subjectEvaluationen
dc.subjectForecastingen
dc.subjectLoss functionen
dc.subjectRamp eventen
dc.subjectSpace-time modelen
dc.subjectStatistical modelen
dc.subjectTime series modelen
dc.subjectWind poweren
dc.subjectWind speeden
dc.titleShort-Term Wind Speed Forecasting for Power System Operationsen
dc.typeArticleen
dc.identifier.journalInternational Statistical Reviewen
dc.contributor.institutionTexas A and M University, College Station, United Statesen
kaust.grant.numberKUS-C1-016-04en
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