基于遗传算法的直流电机风力发电系统最优励磁控制技术

针对风力发电系统发电机转速波动较频繁，难于同时对电压和频率的稳定性实施控制等特点，结合直流发电机的工作特性，提出了基于直流发电机的风力发电系统控制技术。采用基于遗传算法的最优励磁控制技术对发电机的励磁实施控制，使发电机获得了稳定的输出电压。从理论上分析了直流风力发电系统的可行性及其特点，重点分析和研究了基于遗传算法的直流风力发电机组最优励磁控制技术在稳定输出电压方面的性能，运用Matlab对该系统进行了仿真，并用直流电动机作原动机，通过调节电动机的转速模拟风速变化引起的风力机转速变化。在电力系统动态模拟试验室中进行了大量实验，通过比较和分析获取的数据和仿真结果，进一步验证了该方法的正确性和可行性。

A Genetic Algorithm Based Optimal Excitation Control for Wind Power System Using DC Generator

Wind power generation system exists following features: the rotation speed of wind turbine generator frequently fluctuates and both voltage stability and frequency stability are hardly controlled simultaneously. For this reason, according to the operating characteristics of DC generator, the authors propose a wind power generation scheme in which DC generator is utilized. In the proposed, the genetic algorithm (GA) based optimal excitation control technology is applied to the excitation of DC generator, thus the stable output voltage of DC generator is implemented. The feasibility of utilizing DC wind power generation system as well as its features are analyzed theoretically, and the performance of stabilizing the output voltage of DC wind generator by GA based optimal excitation control is emphatically researched. By use of Matlab software the proposed wind power generation scheme is simulated; besides, taking DC motor as prime mover and by means of adjusting its rotation speed to analog the rotation speed variation of wind turbine caused by wind speed variation, a lot of experiments are performed in power system dynamic simulation laboratory. The correctness and feasibility of the proposed scheme are validated by the comparison of numerical simulation results with the obtained experimental data.