Open Access
| Issue |
E3S Web Conf.
Volume 185, 2020
2020 International Conference on Energy, Environment and Bioengineering (ICEEB 2020)
|
|
|---|---|---|
| Article Number | 01056 | |
| Number of page(s) | 5 | |
| Section | Energy Engineering and Power System | |
| DOI | https://doi.org/10.1051/e3sconf/202018501056 | |
| Published online | 01 September 2020 | |
- Hui Qi, Quancheng Pan. No-load grid-connection control and experimental study of doubly-fed wind power simulation system [J]. Electrical automation, 2008, 40(6): 34–37. [Google Scholar]
- Haofeng Wu, Xiangdong Wang, Shujiang Li. A new method of maximum wind energy capture for fuzzy control wind turbine [J]. Electronic design engineering, 2017,25 (18): 147–151. [Google Scholar]
- Wenjuan Zhang. Fuzzy control of no-load grid-connected doubly-fed wind power generation with self-adjusting factor [J]. Machinery and electronics, 2008, 36(5): 52–55. [Google Scholar]
- Dongdong Zhang, Shunjie Han, Jiawen Yu, et al. Grid-connected operation control and simulation of doubly-fed wind turbine [J]. Science and technology innovation and application, 2008, 236(16): 16–18. [Google Scholar]
- Yanling Lv, Xi Feng, Bo Zhu, et al. Study on BP neural network connection strategy of doubly-fed wind turbine [J]. Journal of Harbin university of science and technology, 2017,22 (5): 40–45. [Google Scholar]
- Zhichao Yu, Shuai Liu, du Calvin. Study on grid-connected control of wind power generation based on neural network [J]. Electronic technology,8, 347 (8):93–95+99. [Google Scholar]
- Huiqin Li, Ying Sun, Junjie Wang. Improved association mining algorithm based on fuzzy partition clustering [J]. Microelectronics and computers, 2008, 35(3): 130–134. [Google Scholar]
- Yu Fu. Association rule optimization algorithm based on fuzzy clustering [J]. Computer nerd, 2017,57 (5): 121–123. [Google Scholar]
- Liang Diao, Dan Wang, Lei Guo, et al. Neural network integrated sliding mode control for no-load grid-connection of doubly-fed generators [J]. Journal of solar energy, 2017,38 (12): 15–19. [Google Scholar]
- Jinhui Zeng, Zhifeng Sun, lei min, et al. The improved PR controller is applied to doubly-fed wind power generation system [J]. Power electronics technology, 203, 53(02): 93–96. [Google Scholar]
- Jianfeng Dai, Yi Tang, Linan Qui, et al. Research on coordinated optimal control of solar thermal and wind power generation [J]. Computer simulation, 2017,34 (10): 73–77. [Google Scholar]
- Zhaoyan Xuan, Zhenyu Ma, Huicheng Jing, et al. Overview of control strategies for grid-connected inverter in small wind power generation [J]. Electrical transmission, 2017,47 (9): 44–49. [Google Scholar]
- Jianfeng Yang, Yang Gao, Yuzhong Niu, et al. PIR grid-connected control of three-level wind power system under unbalanced grid [J]. Science and technology bulletin, 2018, (3): 115–119. [Google Scholar]
- Weihua Jiang, ma Chao Li, Xianfeng Zheng. Study on three-level grid-connected wind power generation system based on sliding mode control [J]. Power capacitors and reactive power compensation, 2017,38 (3): 162–166. [Google Scholar]
- Linjing Hu, Peipei Li, Aoyu Ton, et al. Research on reactive power support of mmc-hvdc grid-connected wind power system [J]. Power capacitors and reactive power compensation, 2008,39(2): 119–124. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.