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首页> 外文期刊>Electric power systems research >Multi-objective PSO applied to PI control of DFIG wind turbine under electrical fault conditions
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Multi-objective PSO applied to PI control of DFIG wind turbine under electrical fault conditions

机译：多目标PSO在电故障条件下应用于双馈风力发电机的PI控制

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摘要

Wind generation increase in electric power systems is a general trend in many countries. Variable speed wind turbines (WT) with doubly fed induction generators (DFIG) are commonly used for this purpose. In order to ensure stability and obtain the desired performance when WT are subject to transient disturbances, their control system needs to operate properly. This work aims at tuning the controllers comprising the DFIG control structure enhancing transient performance during electric faults and so contributing to the Low-Voltage Ride-Through (LVRT) capability. To do this, a multi-objective particle swarm optimization algorithm (MOPSO) is proposed applying to the complete dynamic model of the WT (electrical and mechanic parts) and minimizing a set of objective functions (OF) adapted to the electrical network fault problem. Tuning performance is compared with the classical symmetrical optimum method. Simulation results show that the MOPSO and penalization of both electrical and mechanical variables in the OF led to improved mechanical oscillations damping and voltage performance during a fault event, enhancing the LVRT capability even for the more critical condition of the flexible mechanical coupling. The results validate the proposed MOPSO as an effective tool capable of improving the behavior of this type of control for WT.
机译：电力系统中风力的增加是许多国家的普遍趋势。具有双馈感应发电机（DFIG）的变速风力涡轮机（WT）通常用于此目的。当WT受到瞬态干扰时，为了确保稳定性并获得所需的性能，它们的控制系统需要正常运行。这项工作旨在调整包括DFIG控制结构的控制器，以增强电气故障期间的瞬态性能，从而有助于实现低电压穿越（LVRT）能力。为此，提出了一种多目标粒子群优化算法（MOPSO），该算法适用于WT（电气和机械零件）的完整动态模型，并最小化了一组适合电网故障问题的目标函数（OF）。将调谐性能与经典对称最优方法进行了比较。仿真结果表明，在故障事件期间，MOPSO以及OF中电气和机械变量的损失都可以改善故障事件期间的机械振荡阻尼和电压性能，即使在更苛刻的柔性机械耦合条件下，也可以提高LVRT能力。结果证实了提出的MOPSO是一种能够改善WT这类控制行为的有效工具。

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