Solar auto-tracking control strategy based on environmental factors and fuzzy identification

doi:10.11975/j.issn.1002-6819.2015.09.030

CORC > 兰州理工大学 > 兰州理工大学 > 机电工程学院

	Solar auto-tracking control strategy based on environmental factors and fuzzy identification
	Wang, Linjun 1,2; Men, Jing 1,2; Xu, Lixiao 1,2; Zhang, Dong 2; Deng, Yu 1,2; Lü, Yaoping 1,2; Chen, Yanjuan 1,2
刊名	Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
	2015-05-01
卷号	31 期号:9 页码:195-200
关键词	Electric power systems Feedback Fuzzy systems Incident solar radiation MATLAB Membership functions Meteorology Photovoltaic cells Photovoltaic effects Solar energy Solar heating Solar power generation Surface discharges System stability Tracking (position) Wind Automatic tracking system Environmental factors Environmental pollutions Fuzzy identification method Fuzzy recognition systems Fuzzy speculative rule Photoelectric sensors Solar thermal power generation
ISSN号	10026819
DOI	10.11975/j.issn.1002-6819.2015.09.030
英文摘要	Exploring and making full use of new energy resources can solve the problem of the energy shortage and environmental pollution, so many people focus on the use of solar energy which has the advantages of cleanliness, reuse, and economy, etc. Solar power, as the ideal use of solar energy, is the generation of electricity from sunlight. Either PV generation system or solar thermal power generation system have great extensive use, the formal usually use solar cells as the device to convert solar energy directly into electricity by the photovoltaic effect, and photovoltaic technology can meet the demand of different uses which need power supply by solar cells in different sizes, The latter has large scale, it focuses the solar energy to boil water and the heat energy is used to provide power. The solar thermal power generation system can be divided into three types: dish solar thermal power generation, groove type thermal power generation, and tower solar thermal power generation. Dish solar thermal power generation has higher efficiency. Considering that the disadvantages of solar energy are ever-changing solar radiation direction and unstable solar energy, dish solar thermal power generation uses an auto-tracking system to improve the utilization ratio of solar energy for an solar automatic tracking system can keep the incident sunlight parallel to the collector. A dish solar thermal power generation system works out of doors, environmental factors have a great influence on the system's running stability and tracking accuracy, and affects the choice of tracking mode. The auto-tracking modes can be classified into: program tracking mode, photoelectric tracking mode, and hybrid tracking mode. Program tracking mode uses a computer to calculate the sun's azimuth and latitude, can work under all-weather condition, and has high adaptability, but it has a cumulative error in the tracking process. The photoelectric mode has higher tracking accuracy for it has feedback information. It works well in the sunny day, but bad weather (especially the rainy and cloudy day) has a serious effect on it. A solar auto-tracking system usually adopts a hybrid tracking mode which is a combination of the program tracking mode and the photoelectric mode. A photoelectric sensor, as the information feedback component of a control system, can modify the cumulative error of the procedure, the tracking system would track reliably in the complicated and changeable weather. These two tracking modes make up for each other, as a result, the tracking system's precision and stability would be further improved and guaranteed. As an auto-tracking system works, the tracking mode changes as the intensity value reaches the intensity threshold, then the controller will choose a tracking mode automatically. Considering that the environmental factors affect the tracking system, this paper mainly analyses intensity, intensity change, and wind speed which have a serious effect on the system's operational stability and tracking accuracy. It uses fuzzy identification method in MATLAB to classify and summarize the weather condition and system's operation, then it builds a fuzzy recognition system based on environmental factors by respectively setting the parameters of input (wind speed, intensity and intensity change) membership function and output (the system's operation condition and weather condition) membership function. In this process, determining the fuzzy reasoning rules is the most important step. Fuzzy reasoning rules based on judgments of environmental factors are obtained from the expert experience and relevant information, and the wrong rules would even lead to wrong simulation. Through the simulation, weather condition and system operation condition are confirmed, and the conclusion suits the qualified condition. This research provides a theoretical support for a system's start-stop and a tracking mode's switch, and it has preferable practicability and good feasibility. And the conclusion not only can apply to the PV system, but also to the solar thermal power generation system. ©, 2015, Chinese Society of Agricultural Engineering. All right reserved.
语种	中文
出版者	Chinese Society of Agricultural Engineering
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/112368]
专题	机电工程学院能源与动力工程学院
作者单位	1.College of Methano-Electronic Engineering, Lanzhou University of Technology, Lanzhou; 730050, China; 2.China Western Energy and Environment Research Center, Lanzhou University of Technology, Lanzhou; 730050, China
推荐引用方式 GB/T 7714	Wang, Linjun,Men, Jing,Xu, Lixiao,et al. Solar auto-tracking control strategy based on environmental factors and fuzzy identification[J]. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering,2015,31(9):195-200.
APA	Wang, Linjun.,Men, Jing.,Xu, Lixiao.,Zhang, Dong.,Deng, Yu.,...&Chen, Yanjuan.(2015).Solar auto-tracking control strategy based on environmental factors and fuzzy identification.Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering,31(9),195-200.
MLA	Wang, Linjun,et al."Solar auto-tracking control strategy based on environmental factors and fuzzy identification".Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering 31.9(2015):195-200.