【作者】 田野；

【导师】 张建华；

【作者基本信息】 华北电力大学 ， 控制理论与控制工程， 2013， 硕士

【摘要】 能源是关系到国家社会、经济发展全局性的重大战略问题,是我国国民经济、社会生产力持续发展的重要基础,因而节能减排及新能源开发就成为我国当前的战略性新兴产业,而风力发电技术及产业对控制技术提出了越来越高的要求,风力发电控制系统的研究逐渐成为学者们研究的热点。本文首先在分析风力发电各子系统机理模型的基础上,建立了针对不同的风况的风力发电系统整体模型。风力发电系统中,实际风速往往不服从高斯分布。考虑到风速这一特点,本文采用随机分布控制策略,将信息论中熵的概念引入到系统性能指标中,对受随机风速影响的风力发电系统进行了控制器设计。在额定风速以下时,为了实现最大风能捕获的控制目标,给出了基于广义最小熵的最优控制律,所设计控制器实现了风力发电系统风能利用率最大。在额定风速以上时,风力发电系统运行在恒功率区域,此时需要考虑变桨距伺服机构的动作。基于输入输出数据,采用Parzen滑动窗的方法对误差的信息熵、联合熵进行了非参数估计,基于最小熵性能指标得到了最优控制律,并给出了控制算法的实现步骤。仿真结果表明了控制算法的有效性。更多还原

【Abstract】 Energy is a strategically important issue related to the national social and economic overall development, meanwhile, the key foundation for sustaining the national economy and social productivity. Therefore, energy-saving and emission-reduction as well as new energy exploitation have become the strategic emerging industry. Among them, the wind energy conversion technology has aroused general interest in the electrical engineering circles.As far as the wind energy conversion system is concerned, the wind speed is not necessary of Gaussian characteristic in practice. Considering the wind speed as the main disturbance, stochastic distribution control strategy is utilized into the wind energy conversion systems. The information entropy is incorporated into the performance index, and the control design is carried out for the wind energy conversion systems under the influence of the non-Gaussian wind speed. In order to achieve the maximum wind power capture under the rated wind speed, the optimal rotor speed control law is obtained, and the controller can ensure that the wind turbine converters the kinetic energy from the wind into mechanical energy of the wind turbine efficiently.When the wind speed is above the rated wind speed, the wind energy conversion system operates on the constant-power regime. At this time, the action of pitch actuator needs to be considered. Based on the input and output data sequence, Parzen sliding window non-parameter technique is used to estimate the error information entropy and their joint entropy, then we derive the multivariate optimal control algorithm, and the control algorithm implementation procedure is also exhibited. The simulation results verified the effectiveness of the proposed approach.更多还原