Aplikasi Fuzzy Type-2 PSS untuk Perbaikan Stabilitas Dinamik Pembangkit Listrik Tenaga Mikro Hidro dan Diesel

Nrartha, I Made Ari; Ginarsa, I Made; Sultan, Sultan; Muljono, Agung Budi; Warindi, Warindi

doi:10.29303/jstl.v7i2.272

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…In this session, the Lombok Island Power Plant [23,24] with a simplified model [25] is taken as an example of ANFIS power system stabilizer (PSS). The one-line diagram of the hybrid power system for small signal stability is depicted in 5-8.…”

Section: Anfis-pss For Stability Maintain In Hybrid Power Systemmentioning

confidence: 99%

Application of adaptive neuro-fuzzy inference system control in power systems

I. Made,

I. Made Ari,

Agung Budi

et al. 2024

Adaptive Neuro-Fuzzy Inference System as a Universal Estimator

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An adaptive neuro-fuzzy inference system (ANFIS) is developed by combining neural-networks and fuzzy system. The ANFIS model uses the advantages possessed by the properties of neural networks and its decision making is based on fuzzy inference. The ANFIS parameters are obtained and updated by training processes. The ANFIS consists of two inputs (by Gaussian or other membership function) and an output (with constant or linear membership function). The ANFIS control is implemented by building a power system stabilizer (PSS) in power systems. The PSS function is to produce an additional stabilizing signal on the reactive mode of the generator. Training data are obtained from the systems that controlled by a conventional PSS with various conditions. The training process is carried out repeatedly until the appropriate ANFIS parameters are found. Next, the PSS based on ANFIS is applied to replace the conventional PSS on a single machine and hybrid power plants. Peak overshoot and settling time of the power systems are smaller and shorter. The ANFIS PSS makes the power system stability improve significantly in small-signal studies.

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Section: Anfis-pss For Stability Maintain In Hybrid Power Systemmentioning

confidence: 99%

Application of adaptive neuro-fuzzy inference system control in power systems

I. Made,

I. Made Ari,

Agung Budi

et al. 2024

Adaptive Neuro-Fuzzy Inference System as a Universal Estimator

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show abstract

“…The Interval type-2 fuzzy is a linguistic model that is used in wide range such as power system stabilizer to improve stability of single machine [15], multi machine [16] and large-scale PS [17]. The IT2F also is used for micro-hydro and diesel PS on Lombok System [18]. Type-2 fuzzy PSS is tuned using sliding surface approach to damp rotor oscillation on wide-area system.…”

Section: Introductionmentioning

confidence: 99%

Interval Fuzzy-PSS Using Gauss-2 Membership Function to Enhance Small-Signal Stability

Ginarsa¹,

Nrartha²,

Muljono³

et al. 2022

Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Mechanical and E

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Interval type-2 fuzzy (IT2F) model develops to substitute conventional control in power system (PS). The PS is operated to serve the consumer according to load demand. Load fluctuation on the PS is a real situation and can't be avoided. The load fluctuation causes rotor oscillation on machine. Moreover, instability problem can occur if this oscillation is not quickly to damp. The IT2F-based algorithm is developed to replace conventional power system stabilizer (PSS) function. The IT2F is implemented in this research because it simple and not need exactly calculation of plant model. A single machine and multi-machine power systems are applied to assess the performance of the IT2F-PSS. This IT2F-PSS is constructed by two inputs and an output. Three membership functions (MF) Gauss-2 type are used for respective inputs. Five MFs constant type are used for output. The values of fuzzy parameter are tuned properly based on the knowledge and experience the fuzzy developer. Simulations on the case studies provide enhancement the response of rotors speed and angle. The IT2F-PSS responses are assessed on peak overshoot and settling time.

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Aplikasi Fuzzy Type-2 PSS untuk Perbaikan Stabilitas Dinamik Pembangkit Listrik Tenaga Mikro Hidro dan Diesel

Cited by 2 publications

References 6 publications

Application of adaptive neuro-fuzzy inference system control in power systems

Application of adaptive neuro-fuzzy inference system control in power systems

Interval Fuzzy-PSS Using Gauss-2 Membership Function to Enhance Small-Signal Stability

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