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BFA optimization for voltage and frequency control of a stand-alone wind generation unit

机译:用于独立风力发电机组的电压和频率控制的BFA优化

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摘要

A developed control strategy for autonomous wind generation unit is presented. Optimization techniques based on bacteria foraging algorithm and genetic algorithms are used to tune the proposed control parameters. The proposed system mainly consists of induction generator driven by wind turbine, synchronous machine, consumer load, discrete dump load, and gate turn-off thyristor-based power electronics converter. Two control loops are used in this study; the first is to regulate the load bus voltage based on the excitation control of the synchronous machine. The second one simultaneously controls the dump load to absorb excessive power generation, and in turn, regulates the frequency of the proposed power system. The proposed system is tested for turbulent change in wind speed and step change in consumer load. The complete system is modeled and simulated using MATLAB/SIMULINK software package. The performance of the optimized control system is compared with the conventional PID control system. The simulation results show that the optimized control system has good performance as less settling time and less overshoot compared with the case of conventional PID controller.
机译:提出了一种自主风力发电机组的控制策略。利用基于细菌觅食算法和遗传算法的优化技术对提出的控制参数进行了优化。拟议的系统主要由风力发电机驱动的感应发电机,同步电机,用户负载,离散卸载负载以及基于可控硅的栅极关断功率电子转换器组成。在这项研究中使用了两个控制回路。首先是基于同步电机的励磁控制来调节负载母线电压。第二种方法同时控制卸载负载以吸收过多的发电量,进而调节所提出的电力系统的频率。对提议的系统进行了风速湍流变化和用户负载阶跃变化测试。使用MATLAB / SIMULINK软件包对整个系统进行建模和仿真。将优化控制系统的性能与常规PID控制系统进行比较。仿真结果表明,与传统的PID控制器相比,优化后的控制系统具有更佳的建立时间和更少的过冲性能。

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