风光互补发电系统中最大功率跟踪控制策略研究

发布时间：2018-03-06 04:07

本文选题：风光互补发电系统　切入点：Boost电路　出处：《兰州理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：由于风光互补发电系统会受到海拔、风速、空气湿度、光照强度等自然条件的制约和影响,所以系统的输出功率会不稳定。当自然条件变化时,风光互补发电系统的输出功率也会随之变化。本文根据风光互补发电系统的输出特性,研究了基于几何平均数的同时跟踪控制策略和基于BP神经网络预测值的分时跟踪控制策略。这两种控制策略都可以实现用一个DC-DC电路跟踪控制风力和光伏发电系统的输出功率,较传统的独立控制策略,可以省去若干变流器。简化结构,降低成本。首先,介绍了风力发电系统、光伏发电系统、风光互补发电系统及DC-DC电路的拓扑结构和各个系统的主要组成单元。搭建了上述各系统的仿真模型并分析了各系统的输出特性。给出了逆变器在风光互补发电系统中需要达到的基本要求和主要参数。然后,采用模糊控制法跟踪控制风力和光伏发电系统的输出功率。通过采集相邻时刻风力和光伏发电系统的输出功率及占空比变化,计算出下一时刻的电压占空比。再利用几何平均数求出两个占空比的平均值,用此平均数调整风光互补发电系统的输出电压,从而保证风光互补发电系统工作在最大功率点。该控制策略在单个发电系统输出功率发生变化时的控制效果并不理想,功率损失较大;但在风力和光伏发电系统的输出功率同时变化时,该策略所造成的功率损失较小。接着,通过BP神经网络对风速和光照强度的变化进行预测。以预测值为依据,对风力发电系统和光伏发电系统进行分时跟踪。通过分析风力和光伏发电系统的仿真结果,给出了风光互补发电系统切换跟踪目标的最小判定值。从而降低了系统切换跟踪目标的频率,减少了功率损失,保证系统的稳定输出。该控制策略在只有单个发电系统输出功率发生变化时的控制效果较好;而在风力和光伏发电系统的输出功率同时变化时,分时跟踪控制策略所造成的功率损失较大。通过对比上述两种方法的优缺点,给出了一种将上述两种策略相结合的控制方法,该方法可以在不同的天气条件下改变控制策略或切换跟踪对象。有效地提高了发电效率,降低功率损耗。最后,建立了风光互补发电系统的Matlab/Simulink仿真模型。通过对仿真结果的分析可知,在风速和光照强度的正常变化范围内,所设计的控制策略可以使风光互补发电系统快速作出相应,切换跟踪目标,实现了对风力和光伏发电系统的功率跟踪控制,从而保证风光互补发电系统工作在最大功率点。
[Abstract]:The output power of the system will be unstable because of the influence of natural conditions such as altitude, wind speed, air humidity, intensity of illumination and so on. When the natural conditions change, the output power of the system will be unstable. The output power of the wind-wind complementary power generation system will also change with it. In this paper, according to the output characteristics of the wind-wind complementary power generation system, The simultaneous tracking control strategy based on geometric mean and the time-sharing tracking control strategy based on BP neural network prediction value are studied. Both of these two control strategies can track and control the output power of wind and photovoltaic systems with a single DC-DC circuit. Compared with the traditional independent control strategy, some converters can be saved. The structure is simplified and the cost is reduced. Firstly, the wind power system and photovoltaic system are introduced. The topology structure and the main components of each system of wind and wind complementary generation system and DC-DC circuit are established. The simulation model of each system is built and the output characteristics of each system are analyzed. The inverter in the wind and wind complementary generation system is given. Basic requirements and main parameters to be met in the system. Then, The fuzzy control method is used to track and control the output power of the wind and photovoltaic power generation system, and the output power and duty cycle of the wind power and photovoltaic power generation system are collected at adjacent times. Calculate the duty cycle of the next moment. Then calculate the average value of the two duty cycles by using the geometric average, and then adjust the output voltage of the solar complementary generation system with this average. The control effect of the control strategy is not ideal when the output power of a single generation system changes, and the power loss is large. However, when the output power of wind power and photovoltaic system changes simultaneously, the power loss caused by this strategy is relatively small. Then, the variation of wind speed and light intensity is predicted by BP neural network. The time-sharing tracking of wind power system and photovoltaic system is carried out, and the simulation results of wind power system and photovoltaic system are analyzed. In this paper, the minimum decision value of the switching and tracking target in the solar complementary generation system is given, which reduces the frequency of the system switching and tracking target, and reduces the power loss. The control strategy is effective when only the output power of a single generation system changes, but when the output power of wind power and photovoltaic system changes simultaneously, The power loss caused by time-sharing tracking control strategy is great. By comparing the advantages and disadvantages of the two methods, a control method combining the two strategies is presented. This method can change the control strategy or switch the tracking object under different weather conditions. It can effectively improve the generation efficiency and reduce the power loss. Finally, The Matlab/Simulink simulation model of wind-wind complementary power generation system is established. Through the analysis of the simulation results, it can be seen that in the normal range of wind speed and light intensity, the designed control strategy can make the wind-wind complementary power generation system make corresponding quickly. The power tracking control of wind and photovoltaic power generation system is realized by switching the tracking target, thus ensuring that the wind-to-wind complementary power generation system works at the maximum power point.
【学位授予单位】：兰州理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM61

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