Maximum power tracking method of shipborne wind power generation system based on sliding mode optimization and neural control
ObjectiveThis study aims to solve the problems of poor tracking stability and low rapidity of traditional maximum power tracking algorithms in shipborne wind power generation systems.MethodsOn the basis of systematically analyzing the characteristics of the synthetic wind field of ship motion, an op...
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| Format: | Article |
| Language: | English |
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Editorial Office of Chinese Journal of Ship Research
2022-12-01
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| Series: | Zhongguo Jianchuan Yanjiu |
| Subjects: | |
| Online Access: | http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.02961 |
| _version_ | 1828061875679526912 |
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| author | Yucheng LIU Ning WANG |
| author_facet | Yucheng LIU Ning WANG |
| author_sort | Yucheng LIU |
| collection | DOAJ |
| description | ObjectiveThis study aims to solve the problems of poor tracking stability and low rapidity of traditional maximum power tracking algorithms in shipborne wind power generation systems.MethodsOn the basis of systematically analyzing the characteristics of the synthetic wind field of ship motion, an optimal mechanical angular velocity tracking control strategy based on single neuron proportional integral (SNPI) is proposed to improve the tracking speed of wind turbine restart. At the same time, the power sliding mode extremum seeking (PSMES) algorithm is used to replace the tip speed ratio (TSR) method which relies on accurate wind speed measurement to achieve the rapid optimization of mechanical angular velocity and cope with the maximum power search under frequent restarts of the power generation system. ResultsThe simulation results show that using the maximum power tracking strategy of mechanical angular velocity PSMES optimization and SNPI control, compared with the traditional algorithm, improves rapidity performance by more than 50% while also enhancing stability performance. ConclusionThe proposed maximum power tracking algorithm has obvious advantages in both rapidity and stability. |
| first_indexed | 2024-04-10T22:20:39Z |
| format | Article |
| id | doaj.art-32f47db009054574bcc5936aa7ab034c |
| institution | Directory Open Access Journal |
| issn | 1673-3185 |
| language | English |
| last_indexed | 2024-04-10T22:20:39Z |
| publishDate | 2022-12-01 |
| publisher | Editorial Office of Chinese Journal of Ship Research |
| record_format | Article |
| series | Zhongguo Jianchuan Yanjiu |
| spelling | doaj.art-32f47db009054574bcc5936aa7ab034c2023-01-18T03:09:50ZengEditorial Office of Chinese Journal of Ship ResearchZhongguo Jianchuan Yanjiu1673-31852022-12-0117Supp112212810.19693/j.issn.1673-3185.02961ZG2961Maximum power tracking method of shipborne wind power generation system based on sliding mode optimization and neural controlYucheng LIU0Ning WANG1Marine Electrical Engineering College, Dalian Maritime University, Dalian 116026, ChinaMarine Engineering College, Dalian Maritime University, Dalian 116026, ChinaObjectiveThis study aims to solve the problems of poor tracking stability and low rapidity of traditional maximum power tracking algorithms in shipborne wind power generation systems.MethodsOn the basis of systematically analyzing the characteristics of the synthetic wind field of ship motion, an optimal mechanical angular velocity tracking control strategy based on single neuron proportional integral (SNPI) is proposed to improve the tracking speed of wind turbine restart. At the same time, the power sliding mode extremum seeking (PSMES) algorithm is used to replace the tip speed ratio (TSR) method which relies on accurate wind speed measurement to achieve the rapid optimization of mechanical angular velocity and cope with the maximum power search under frequent restarts of the power generation system. ResultsThe simulation results show that using the maximum power tracking strategy of mechanical angular velocity PSMES optimization and SNPI control, compared with the traditional algorithm, improves rapidity performance by more than 50% while also enhancing stability performance. ConclusionThe proposed maximum power tracking algorithm has obvious advantages in both rapidity and stability.http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.02961shipborne wind power generation systemmaximum power trackingsingle neuron proportional integralsliding mode extremum seeking control |
| spellingShingle | Yucheng LIU Ning WANG Maximum power tracking method of shipborne wind power generation system based on sliding mode optimization and neural control Zhongguo Jianchuan Yanjiu shipborne wind power generation system maximum power tracking single neuron proportional integral sliding mode extremum seeking control |
| title | Maximum power tracking method of shipborne wind power generation system based on sliding mode optimization and neural control |
| title_full | Maximum power tracking method of shipborne wind power generation system based on sliding mode optimization and neural control |
| title_fullStr | Maximum power tracking method of shipborne wind power generation system based on sliding mode optimization and neural control |
| title_full_unstemmed | Maximum power tracking method of shipborne wind power generation system based on sliding mode optimization and neural control |
| title_short | Maximum power tracking method of shipborne wind power generation system based on sliding mode optimization and neural control |
| title_sort | maximum power tracking method of shipborne wind power generation system based on sliding mode optimization and neural control |
| topic | shipborne wind power generation system maximum power tracking single neuron proportional integral sliding mode extremum seeking control |
| url | http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.02961 |
| work_keys_str_mv | AT yuchengliu maximumpowertrackingmethodofshipbornewindpowergenerationsystembasedonslidingmodeoptimizationandneuralcontrol AT ningwang maximumpowertrackingmethodofshipbornewindpowergenerationsystembasedonslidingmodeoptimizationandneuralcontrol |