dc.contributor.author |
Narayana, M |
|
dc.contributor.author |
Sunderland, KM |
|
dc.contributor.author |
Putrus, G |
|
dc.contributor.author |
Conlon, MF |
|
dc.date.accessioned |
2023-03-17T08:02:20Z |
|
dc.date.available |
2023-03-17T08:02:20Z |
|
dc.date.issued |
2017 |
|
dc.identifier.citation |
Narayana, M., Sunderland, K. M., Putrus, G., & Conlon, M. F. (2017). Adaptive linear prediction for optimal control of wind turbines. Renewable Energy, 113, 895–906. https://doi.org/10.1016/j.renene.2017.06.041 |
en_US |
dc.identifier.issn |
0960-1481 |
en_US |
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/20767 |
|
dc.description.abstract |
In order to obtain maximum power output of a Wind Energy Conversion
System (WECS), the rotor speed needs to be optimised for a particular wind speed.
However, due to inherent inertia, the rotor of a WECS cannot react instantaneously
according to wind speed variations. As a consequence, the performance of the system
and consequently the wind energy conversion capability of the rotor are negatively
affected. This study considers the use of a time series Adaptive Linear Prediction (ALP)
technique as a means to improve the performance and conversion efficiency of wind4 turbines. The ALP technique is introduced as a real time control reference to improve
optimal control of wind turbines. In this study, a wind turbine emulator is developed to
evaluate the performance of the predictive control strategy. In this regard, the ALP
reference control method was applied as a means to control the torque/speed of the
emulator. The results show that the employment of a predictive technique increases
energy yield by almost 5%. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
IEEE |
en_US |
dc.subject |
Wind energy conversion systems |
en_US |
dc.subject |
Wind turbine |
en_US |
dc.subject |
Linear adaptive prediction |
en_US |
dc.subject |
Power mapping technique |
en_US |
dc.subject |
Wind speed sensor technique |
en_US |
dc.subject |
Wind speed estimation |
en_US |
dc.title |
Adaptive linear prediction for optimal control of wind turbines |
en_US |
dc.type |
Article-Full-text |
en_US |
dc.identifier.year |
2017 |
en_US |
dc.identifier.journal |
Renewable Energy |
en_US |
dc.identifier.volume |
113 |
en_US |
dc.identifier.database |
ScienceDirect |
en_US |
dc.identifier.pgnos |
895-906 |
en_US |
dc.identifier.doi |
10.1016/j.renene.2017.06.041 |
en_US |