【作者】 刘志平；

【导师】 崔岩；

【作者基本信息】 汕头大学 ， 信号与信息处理， 2009， 硕士

【摘要】 在化石能源日益短缺的今天,不可再生能源——太阳能逐渐在能源消费市场上占据了一定的地位,而且太阳能的使用也越来越普遍。因此对于光伏系统的相关研究也一直是不可再生能源领域的一个重要研究课题。目前,由于对太阳能的利用还不是非常普遍,造成了民用光伏电池的价格偏高,而且电池的转换效率还比较低,只有15%~30%,因此光伏系统的性价比不高。一般而言,在光伏发电系统中,光伏电池占整个系统总成本的57%,蓄电池占30%,最大功率控制器占7%,其它占6%。以上数据表明,为了提高光伏系统的性价比,比较合理的方式是研发使系统转换效率更高的控制器。因此具有最大功率跟踪功能(MPPT)的光伏控制器就是本文所研究的重点内容。本文重点研究了三款不同原理、不同性能的光伏控制器,其光伏系统转换效率是由低到高,在商业上也能满足不同消费层次和不同地域的需求。第一款控制器是在古典控制器的基础上增加了蓄电池的温度补偿功能,其主要特点是能够在不同温度下安全地用光伏电池为蓄电池充电,不必考虑蓄电池会因过度充电而损害的问题。第二款控制器是在使用传统电量增量算法的基础上提出了一种新算法:二阶电导增量比较法。此新算法除了继承传统算法快速反应的能力外,还具有跟踪时间快,精度高的特点。第三款控制器与前一款控制器在原理上具有本质的不同,前一款在控制上属于开环控制系统,而这一款属于闭环控制系统。此款控制器借鉴了人工智能的原理,采用了径向基神经网络算法能够自动识别光伏电池的最大功率输出点,具有反应更快、跟踪时间更短、精度更高的特点,因此将大大增强光伏系统的适用区域。更多还原

【Abstract】 For the growing shortage of fossil fuels at the present day, the non-renewable energy -solar energy gradually occupies a certain position in the energy consumption market, and the use of solar energy is becoming more and more common. Thence, the studies of photovoltaic system are always the significant field of non-renewable energy research. At present, due to the use of solar energy is not very common, that results in high price of photovoltaic cells in civilian, and cell conversion efficiency is still relatively low, only up to from 15% to 30%, so cost-effective of photovoltaic system is not high. Generally speaking, in the photovoltaic power generation system, PV cells account for the total cost of the entire system of 57%, 30% for battery, the maximum power controller takes 7% and 6% for others. The above data show that, in order to improve the cost-effective of photovoltaic system, a more reasonable approach is the study of a higher conversion efficiency controller. Therefore the photovoltaic controller with maximum power point tracking (MPPT) is the focus of the study in this paper.This article focuses on researching photovoltaic controller with three different principles and different properties, and its efficiency of photoelectric conversion is from low to high, it can meet the needs of different geographical levels and consumer of different regions in the business.The first controller is based on the classic controller to increase the function of battery temperature compensation, and its main characteristic is that can be safely used charging from photovoltaic cells to battery at different temperatures, and no need to consider the damage due to excessive charging of the battery.For the second controller, this paper proposes a new algorithm- two-order Incremental Conductance Comparative method, which is based on the use of traditional electricity incremental algorithm. This algorithm not only inherits the rapid reaction capacity of the traditional algorithm, but also has the characteristics of the low tracking time and high precision.The third controller is essentially different from the second one on principle. The second controller belongs to open-loop control system in control, but the third one is a closed-loop control system. This controller applies the principles of artificial intelligence, using a neural network algorithm of radial basis function to automatically identify the PV cells at the maximum power output, and with the characteristics of a faster response, a shorter tracking time, the higher accuracy. Therefore, it will magnify the application region of photovoltaic system.更多还原