Probabilistic modelling of wind turbine power curves with application of heteroscedastic gaussian process regression

Rogers, T. orcid.org/0000-0002-3433-3247, Gardner, P. orcid.org/0000-0002-1882-9728, Dervilis, N. orcid.org/0000-0002-5712-7323 et al. (4 more authors) (2019) Probabilistic modelling of wind turbine power curves with application of heteroscedastic gaussian process regression. Renewable Energy. ISSN 0960-1481

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2019 The Authors. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Wind turbine; Power curve; Gaussian process; Heteroscedastic; Probabilistic; Bayesian
Dates:
  • Accepted: 30 September 2019
  • Published (online): 12 October 2019
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Funding Information:
FunderGrant number
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/R004900/1
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/R003645/1
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/S001565/1
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/R006768/1
Depositing User: Symplectic Sheffield
Date Deposited: 29 Oct 2019 12:58
Last Modified: 29 Oct 2019 12:58
Status: Published online
Publisher: Elsevier
Refereed: Yes
Identification Number: https://doi.org/10.1016/j.renene.2019.09.145

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