2018 International Conference on System Science and Engineering (ICSSE) 2018
DOI: 10.1109/icsse.2018.8520210
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ANFIS Damping Controller Design for SSSC to Improve Dynamic Stability of a Grid Connected Wind Power Systems

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Cited by 10 publications
(9 citation statements)
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“…Adaptive neural fuzzy inference system (ANFIS) based damping controller is used for a nonlinear system model with the time domain system model. SSSC controlled using the ANFIS controller proved to be effective in damping oscillations [93]. SSR or SSO reduction using the FACTS devices are discussed in the literature [94] which compares the performance of both SVC and thyristor-controlled series capacitor (TCSC) in damping.…”
Section: Facts Based Oscillation Reductionmentioning
confidence: 99%
“…Adaptive neural fuzzy inference system (ANFIS) based damping controller is used for a nonlinear system model with the time domain system model. SSSC controlled using the ANFIS controller proved to be effective in damping oscillations [93]. SSR or SSO reduction using the FACTS devices are discussed in the literature [94] which compares the performance of both SVC and thyristor-controlled series capacitor (TCSC) in damping.…”
Section: Facts Based Oscillation Reductionmentioning
confidence: 99%
“…The simplified model is presented in Figure 2 [15]. The wind farm is an association of several wind turbines in series, each one is constitued of a double feed asynchronous machine, 850kW / 690V wound rotor sized for an air density of 1.225 kg / m 3 with a rotation speed between 14.6 and 30.8 rpm [16][17][18].…”
Section: Scherbius Dfig Wind Systemmentioning
confidence: 99%
“…In addition to that, the Kalman filter is used to estimate the sub‐synchronous components present in the system and apply the genetic algorithm to optimise the controller parameters of a static series synchronous compensator (SSSC) in [79]. A controller based on an artificial neural network and fuzzy logic to enhance the performance of an SSSC is presented in [80]. A coordinated control strategy to eliminate SSO in multi‐generator setup is proposed in [81] for estimating non‐measurable state variables.…”
Section: Sso In Wfs Based On Type 3 Wtgsmentioning
confidence: 99%