基于环境因素与模糊识别的太阳自动跟踪控制策略

摘要

提高太阳自动跟踪控制系统的运行稳定性和跟踪精度，需要考虑外界环境因素对系统的影响及选择适当的跟踪方式。目前，太阳自动跟踪系统普遍采用光电跟踪和程序跟踪相结合的混合跟踪方式，将光强值与光强阈值的差值作为切换跟踪方式的依据。当光强值趋近光强阈值时，会造成跟踪方式频繁的切换，该文针对该问题，以外界光强大小、光强变化和风速大小为特征目标，利用MATLAB中的模糊识别方法归类总结了天气情况和系统运行情况，建立了一种基于环境因素判断的模糊识别系统，通过仿真验证，得到了天气类型和系统的运行情况，仿真结果完全符合推理条件，并与计算所得结果基本一致。该研究为太阳自动跟踪系统的启停和跟踪方式的切换提供了可靠的理论支持，且具有较高的实用性和可行性。%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.