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Design of a power system stabilizer using adaptive-neuro fuzzy logic for a multi-machine system having dynamic loads

机译:具有自适应负载的多机系统基于自适应神经模糊逻辑的电力系统稳定器设计

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This paper attempts to show how a fuzzy logic controller (FLC) is used for the design of a power system stabilizer (PSS) for a multi-machine interconnected power system. It has also been addressed how a fuzzy logic-PSS has been optimized by using an adaptive neuro-fuzzy inference system (ANFIS) based technique. The design objective of the PSS is to supply an external damping torque to an automatic voltage regulator (AVR) of a synchronous generator without affecting the synchronizing torque. The PSS is designed based on the use of FLC by Mamdani and Takagi-Sugeno (T-S) methods for comparison purposes. The designed controllers are tested on a test system having a dynamic load. The simulation results by MATLAB/SIMULINK demonstrate the effectiveness of the ANFIS-PSS over FLC-PSS to control the low frequency electromechanical oscillation of interconnected power systems under severe disturbances with dynamic loads.
机译:本文试图说明如何将模糊逻辑控制器(FLC)用于多机互连电力系统的电力系统稳定器(PSS)的设计。还已经解决了如何通过使用基于自适应神经模糊推理系统(ANFIS)的技术来优化模糊逻辑PSS。 PSS的设计目标是在不影响同步扭矩的情况下,向同步发电机的自动电压调节器(AVR)提供外部阻尼扭矩。 PSS是基于Mamdani和Takagi-Sugeno(T-S)方法使用FLC进行比较而设计的。设计的控制器在具有动态负载的测试系统上进行测试。 MATLAB / SIMULINK的仿真结果表明,在动态负载严重干扰下,ANFIS-PSS优于FLC-PSS可以控制互连电力系统的低频机电振荡。

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