Neuron-Adaptive PID Based Speed Control of SCSG Wind Turbine System
In searching for methods to increase the power capacity of wind power generation system, superconducting synchronous generator (SCSG) has appeared to be an attractive candidate to develop large-scale wind turbine due to its high energy density and unprecedented advantages in weight and size. In this...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2014/376259 |
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| _version_ | 1832562457847005184 |
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| author | Shan Zuo Yongduan Song Lei Wang Zheng Zhou |
| author_facet | Shan Zuo Yongduan Song Lei Wang Zheng Zhou |
| author_sort | Shan Zuo |
| collection | DOAJ |
| description | In searching for methods to increase the power capacity of wind power generation system, superconducting synchronous generator (SCSG) has appeared to be an attractive candidate to develop large-scale wind turbine due to its high energy density and unprecedented advantages in weight and size. In this paper, a high-temperature superconducting technology based large-scale wind turbine is considered and its physical structure and characteristics are analyzed. A simple yet effective single neuron-adaptive PID control scheme with Delta learning mechanism is proposed for the speed control of SCSG based wind power system, in which the RBF neural network (NN) is employed to estimate the uncertain but continuous functions. Compared with the conventional PID control method, the simulation results of the proposed approach show a better performance in tracking the wind speed and maintaining a stable tip-speed ratio, therefore, achieving the maximum wind energy utilization. |
| format | Article |
| id | doaj-art-333792887664434d90a723da9e507fd7 |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-333792887664434d90a723da9e507fd72025-02-03T01:22:37ZengWileyAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/376259376259Neuron-Adaptive PID Based Speed Control of SCSG Wind Turbine SystemShan Zuo0Yongduan Song1Lei Wang2Zheng Zhou3Institute of Intelligent System and Renewable Energy Technology, University of Electronic Science and Technology of China, Chengdu 611731, ChinaInstitute of Intelligent System and Renewable Energy Technology, University of Electronic Science and Technology of China, Chengdu 611731, ChinaInstitute of Intelligent System and Renewable Energy Technology, University of Electronic Science and Technology of China, Chengdu 611731, ChinaWeb Science Center, University of Electronic Science and Technology of China, Chengdu 611731, ChinaIn searching for methods to increase the power capacity of wind power generation system, superconducting synchronous generator (SCSG) has appeared to be an attractive candidate to develop large-scale wind turbine due to its high energy density and unprecedented advantages in weight and size. In this paper, a high-temperature superconducting technology based large-scale wind turbine is considered and its physical structure and characteristics are analyzed. A simple yet effective single neuron-adaptive PID control scheme with Delta learning mechanism is proposed for the speed control of SCSG based wind power system, in which the RBF neural network (NN) is employed to estimate the uncertain but continuous functions. Compared with the conventional PID control method, the simulation results of the proposed approach show a better performance in tracking the wind speed and maintaining a stable tip-speed ratio, therefore, achieving the maximum wind energy utilization.http://dx.doi.org/10.1155/2014/376259 |
| spellingShingle | Shan Zuo Yongduan Song Lei Wang Zheng Zhou Neuron-Adaptive PID Based Speed Control of SCSG Wind Turbine System Abstract and Applied Analysis |
| title | Neuron-Adaptive PID Based Speed Control of SCSG Wind Turbine System |
| title_full | Neuron-Adaptive PID Based Speed Control of SCSG Wind Turbine System |
| title_fullStr | Neuron-Adaptive PID Based Speed Control of SCSG Wind Turbine System |
| title_full_unstemmed | Neuron-Adaptive PID Based Speed Control of SCSG Wind Turbine System |
| title_short | Neuron-Adaptive PID Based Speed Control of SCSG Wind Turbine System |
| title_sort | neuron adaptive pid based speed control of scsg wind turbine system |
| url | http://dx.doi.org/10.1155/2014/376259 |
| work_keys_str_mv | AT shanzuo neuronadaptivepidbasedspeedcontrolofscsgwindturbinesystem AT yongduansong neuronadaptivepidbasedspeedcontrolofscsgwindturbinesystem AT leiwang neuronadaptivepidbasedspeedcontrolofscsgwindturbinesystem AT zhengzhou neuronadaptivepidbasedspeedcontrolofscsgwindturbinesystem |