Neural Network Compensation Control for Output Power Optimization of Wind Energy Conversion System Based on Data-Driven Control
Due to the uncertainty of wind and because wind energy conversion systems (WECSs) have strong nonlinear characteristics, accurate model of the WECS is difficult to be built. To solve this problem, data-driven control technology is selected and data-driven controller for the WECS is designed based on...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
|
| Series: | Journal of Control Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2012/736586 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832548484995088384 |
|---|---|
| author | T. Li A. J. Feng L. Zhao |
| author_facet | T. Li A. J. Feng L. Zhao |
| author_sort | T. Li |
| collection | DOAJ |
| description | Due to the uncertainty of wind and because wind energy conversion systems (WECSs) have strong nonlinear characteristics, accurate model of the WECS is difficult to be built. To solve this problem, data-driven control technology is selected and data-driven controller for the WECS is designed based on the Markov model. The neural networks are designed to optimize the output of the system based on the data-driven control system model. In order to improve the efficiency of the neural network training, three different learning rules are compared. Analysis results and SCADA data of the wind farm are compared, and it is shown that the method effectively reduces fluctuations of the generator speed, the safety of the wind turbines can be enhanced, the accuracy of the WECS output is improved, and more wind energy is captured. |
| format | Article |
| id | doaj-art-a7dff03a7a1e451c87ad2a13947731c5 |
| institution | Kabale University |
| issn | 1687-5249 1687-5257 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Control Science and Engineering |
| spelling | doaj-art-a7dff03a7a1e451c87ad2a13947731c52025-02-03T06:14:00ZengWileyJournal of Control Science and Engineering1687-52491687-52572012-01-01201210.1155/2012/736586736586Neural Network Compensation Control for Output Power Optimization of Wind Energy Conversion System Based on Data-Driven ControlT. Li0A. J. Feng1L. Zhao2Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education, Jiangnan University, Wuxi 214122, ChinaKey Laboratory of Advanced Process Control for Light Industry of Ministry of Education, Jiangnan University, Wuxi 214122, ChinaDepartment of Mechanical and Electrical Engineering, Shan Dong Water Polytechnic, Rizhao 276826, ChinaDue to the uncertainty of wind and because wind energy conversion systems (WECSs) have strong nonlinear characteristics, accurate model of the WECS is difficult to be built. To solve this problem, data-driven control technology is selected and data-driven controller for the WECS is designed based on the Markov model. The neural networks are designed to optimize the output of the system based on the data-driven control system model. In order to improve the efficiency of the neural network training, three different learning rules are compared. Analysis results and SCADA data of the wind farm are compared, and it is shown that the method effectively reduces fluctuations of the generator speed, the safety of the wind turbines can be enhanced, the accuracy of the WECS output is improved, and more wind energy is captured.http://dx.doi.org/10.1155/2012/736586 |
| spellingShingle | T. Li A. J. Feng L. Zhao Neural Network Compensation Control for Output Power Optimization of Wind Energy Conversion System Based on Data-Driven Control Journal of Control Science and Engineering |
| title | Neural Network Compensation Control for Output Power Optimization of Wind Energy Conversion System Based on Data-Driven Control |
| title_full | Neural Network Compensation Control for Output Power Optimization of Wind Energy Conversion System Based on Data-Driven Control |
| title_fullStr | Neural Network Compensation Control for Output Power Optimization of Wind Energy Conversion System Based on Data-Driven Control |
| title_full_unstemmed | Neural Network Compensation Control for Output Power Optimization of Wind Energy Conversion System Based on Data-Driven Control |
| title_short | Neural Network Compensation Control for Output Power Optimization of Wind Energy Conversion System Based on Data-Driven Control |
| title_sort | neural network compensation control for output power optimization of wind energy conversion system based on data driven control |
| url | http://dx.doi.org/10.1155/2012/736586 |
| work_keys_str_mv | AT tli neuralnetworkcompensationcontrolforoutputpoweroptimizationofwindenergyconversionsystembasedondatadrivencontrol AT ajfeng neuralnetworkcompensationcontrolforoutputpoweroptimizationofwindenergyconversionsystembasedondatadrivencontrol AT lzhao neuralnetworkcompensationcontrolforoutputpoweroptimizationofwindenergyconversionsystembasedondatadrivencontrol |