• Title/Summary/Keyword: nonlinear two-machine five-bus system

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Stabilization of nonlinear two-generator five-bus power systems using fuzzy control (퍼지제어를 이용한 비선형 2기 5모선 전력계통의 안정화)

  • Moon, Un-Chul
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.1
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    • pp.42-49
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    • 2000
  • This paper presents the application of a FARMA controller to stabilization of nonlinear Two-Generator Five-Bus power Systems. The control rules and the membership functions of the FARMA controller are generated automatically without using any plant model high complexity and severe nonlinearity of power systems are introduced and two-Machine Five -Bus Power system stabilization problem is formulated. The simulation results demonstrate the effectiveness and application possibility of the FARMA controller to the control problem of high order and nonlinear plants.

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Frequency Stabilization of a Nonlinear Two-Generator Five-Bus Power System using Adaptive Fuzzy Control (퍼지 적응 제어를 이용한 전력게통 주파수 안정화의 비선형 2기 5모선 모의 적용)

  • Moon, Un-Chul
    • Journal of KIISE:Software and Applications
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    • v.27 no.9
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    • pp.952-960
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    • 2000
  • 본 논문에서는 퍼지 자동회귀 이동평균 (Fuzzy Auto-Regressive Moving Average, FARMA)제어기를 전력계통의 비선형 2기 5모선 (Two Machine - Five Bus)모형의 주파수 안정화에 적용한 결과를 제시한다 퍼지 자동회귀 이동 평균 제어기는 기존의 전문가에 의존하였던 퍼지제어 규칙을 실시간으로 형성해 나가는 구조이다. 복잡성, 비선형성 등 전력계통의 일반적인 특징들을 기술하고, 그 특징을 표현할 수 있는 비선형 2기5모선 모형을 제시한다. 제시된 모형을 바탕으로 기존 제어 방식과의 성능 비교를 실시하였고, 이를 통하여 FARMA 제어기의 우수성을 확인하였다.

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TCSC Nonlinear Adaptive Damping Controller Design Based on RBF Neural Network to Enhance Power System Stability

  • Yao, Wei;Fang, Jiakun;Zhao, Ping;Liu, Shilin;Wen, Jinyu;Wang, Shaorong
    • Journal of Electrical Engineering and Technology
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    • v.8 no.2
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    • pp.252-261
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    • 2013
  • In this paper, a nonlinear adaptive damping controller based on radial basis function neural network (RBFNN), which can infinitely approximate to nonlinear system, is proposed for thyristor controlled series capacitor (TCSC). The proposed TCSC adaptive damping controller can not only have the characteristics of the conventional PID, but adjust the parameters of PID controller online using identified Jacobian information from RBFNN. Hence, it has strong adaptability to the variation of the system operating condition. The effectiveness of the proposed controller is tested on a two-machine five-bus power system and a four-machine two-area power system under different operating conditions in comparison with the lead-lag damping controller tuned by evolutionary algorithm (EA). Simulation results show that the proposed damping controller achieves good robust performance for damping the low frequency oscillations under different operating conditions and is superior to the lead-lag damping controller tuned by EA.