Zhang, L, Ma, L, Li, K orcid.org/0000-0001-6657-0522 et al. (5 more authors) (2016) NARX models for predicting power consumption of a horizontal axis wind turbine. In: Proceedings of the 2016 UKACC 11th International Conference on Control (CONTROL). 2016 UKACC 11th International Conference on Control (CONTROL), 31 Aug - 02 Sep 2016, Belfast, UK. IEEE ISBN 978-1-4673-9891-6
Abstract
Wind prediction is a key technique for seamless integration of large penetration of wind power into the power system. In this study, a nonlinear autoregressive model with exogenous inputs (NARX) is developed to predict the power consumption of a single wind turbine. The training data for the NARX models are collected from a 1.5MW wind turbine of a wind farm located at Northeast of China. The accuracy of models using different independent inputs including wind direction, speed as well as engine room position, is compared. The results show that the resultant NARX models are capable of capturing the dynamic characteristics of wind turbine power consumption, and the modelling accuracy with three inputs is better than of the model using only two inputs.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | Wind turbine; power consumption; wind direction; wind speed; engine room postion; nonlinear autoregressive model with exogenous inputs |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Nov 2019 15:37 |
Last Modified: | 05 Nov 2019 15:37 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/control.2016.7737571 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:153029 |