Abstract
The paper focus on prediction of wind farm power for horizons of 0-10 minutes and not more than one hour using statistical methods. These short term predictions
are relevant for both transmission system operators, wind farm operators and traders. Previous research indicates that for short time horizons the persistence method performs as well as more complex methods. However, these results are based on
accumulated power for an entire wind farm. The contribution in this paper is to develop multi-dimensional linear methods based on measurements of power or wind speed from individual wind turbine in a wind farm. These multi-dimensional methods are compared with the persistence method using real 1 minute average data from the Sheringham Shoal wind farm with 88 turbines. The results show that the use of measurements from individual turbines reduce the prediction errors 5-10% and also improves the prediction error variance estimate compared to the persistence method. We also present convincing examples showing that the predictions follow the wind farm power over a window of an hour.
are relevant for both transmission system operators, wind farm operators and traders. Previous research indicates that for short time horizons the persistence method performs as well as more complex methods. However, these results are based on
accumulated power for an entire wind farm. The contribution in this paper is to develop multi-dimensional linear methods based on measurements of power or wind speed from individual wind turbine in a wind farm. These multi-dimensional methods are compared with the persistence method using real 1 minute average data from the Sheringham Shoal wind farm with 88 turbines. The results show that the use of measurements from individual turbines reduce the prediction errors 5-10% and also improves the prediction error variance estimate compared to the persistence method. We also present convincing examples showing that the predictions follow the wind farm power over a window of an hour.
Original language | English |
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Title of host publication | Proceedings, European Control Conference 2018 |
Number of pages | 8 |
Publisher | IEEE |
Publication date | 29 Nov 2018 |
Pages | 3057-3064 |
ISBN (Print) | 978-1-5386-5303-6 |
ISBN (Electronic) | 978-3-9524-2698-2 |
DOIs | |
Publication status | Published - 29 Nov 2018 |
Event | European Control Conference 2018 - , Cyprus Duration: 12 Jun 2018 → 15 Jun 2018 |
Conference
Conference | European Control Conference 2018 |
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Country/Territory | Cyprus |
Period | 12/06/2018 → 15/06/2018 |