Fuzzy-based Static VAR Compensator controller for damping power system disturbances

Arzeha, Nurul Aziah; Mustafa, Mohd Wazir; Idris, Rubia

doi:10.1109/peoco.2012.6230924

Cited by 10 publications

(9 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However the ZN technique of controlling PID is linear in nature. It provides very little robustness to loops and is quite oscillating in nature [18]. As a result it leads to loop instability.…”

Section: B Zeigler Nichols Methodsmentioning

confidence: 99%

“…PID primarily is named after proportional (P), integral (I) and derivative (D) terms. A PID controller is utilized as a feedback that flexibly keeps calculating an error value e(t) repeatedly by finding the difference between the measured variables and desired set point and applies an error rectification based on proportional integral and derivative terms [18]. Finally the three main parameters are used to generate a control signal with reduced error.…”

Section: A Conventional Pidmentioning

confidence: 99%

“…Finally the three main parameters are used to generate a control signal with reduced error. The P, I and D parameters can be mathematically formulated as below in [18]:…”

Section: A Conventional Pidmentioning

confidence: 99%

“…Although PID controller is quite reliable, yet the initial speculation of PID parameters is quite time consuming and it cannot respond to nonlinearities [18]. Hence some versatile tuning methods need to be utilized to effectively tune PID controller for best results.…”

Section: Fig 4 Block Diagram Of Conventional Pid Controllermentioning

confidence: 99%

See 3 more Smart Citations

Application of Flower Pollination Algorithm for Optimally Tuning Zeigler Nichols Parameters for PID Controller to Enhance Transient Stability through SVC

Choudhury,

Rout,

Satpathy

et al. 2019

IJEAT

View full text Add to dashboard Cite

With the evolution of electrical networks, the complexity and non linearity of modern power systems has enhanced exponentially. In order to reduce these potentially harmful oscillations, power system stabilizers (PSS) are introduced in generators of modern power systems. The PSS brings the system back to a stable and balanced state and re-establishes the pre-fault performance of the system after removal of disturbance and restoration of line. However utilization of PSS in certain cases of increased transmission line loading and other significant faults is not very effective and is rather time consuming. These days to acquire better control and quality of power, FACTS devices are being commonly used in large power systems. When SVC, a versatile FACTS device is used simultaneously with PSS, there is not only improvement in power transfer capability and controllability but also a distinct enhancement in power system stability. In order to increase the performance of the conventional PID controller of the PSS, it is tuned with a very simple and quick tuning method called Zeigler Nichols (ZN) which provides very fast elimination to disturbances in power system. However the conventional and ZN based PID controllers are confined only to linear control of power system. To further enhance the dynamic tuning process in order to obtain much faster and better transient as well as dynamic stability, a very adaptable and robust nature inspired technique of Flower Pollination Algorithm (FPA) is used to tune the ZN based PID controller. To realise the system transient stability for the conventional and proposed method, root locus and total harmonic distortion techniques have been adopted. The results ultimately reveal the efficacy and productiveness of FP based ZN- PID in successfully damping out inter area oscillations thus reducing the harmonics and improving overall stability in power systems as compared to other tuning methods

show abstract

Section: B Zeigler Nichols Methodsmentioning

confidence: 99%

Section: A Conventional Pidmentioning

confidence: 99%

“…Finally the three main parameters are used to generate a control signal with reduced error. The P, I and D parameters can be mathematically formulated as below in [18]:…”

Section: A Conventional Pidmentioning

confidence: 99%

Section: Fig 4 Block Diagram Of Conventional Pid Controllermentioning

confidence: 99%

See 2 more Smart Citations

Application of Flower Pollination Algorithm for Optimally Tuning Zeigler Nichols Parameters for PID Controller to Enhance Transient Stability through SVC

Choudhury,

Rout,

Satpathy

et al. 2019

IJEAT

View full text Add to dashboard Cite

show abstract

“…Reference [13] applied the combination of fuzzy and PI controllers to improve transient stability and damping of system fluctuations. Reference [14] proposed an adaptive fuzzy controller for SVCs.…”

Section: Introductionmentioning

confidence: 99%

Implementation of SVC based on grey theory and fuzzy logic to improve LVRT capability of wind distributed generations

Karami¹,

Itami²

2017

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

HVDC Commutation Failure Analysis and Simulation after Removing the Three Phase Short Circuit Fault

Liu

Gao²,

Cheng

et al. 2022

2022 5th International Conference on Energy, Electrical and Power Engineering (CEEPE)

View full text Add to dashboard Cite

Fuzzy-based Static VAR Compensator controller for damping power system disturbances

Cited by 10 publications

References 13 publications

Application of Flower Pollination Algorithm for Optimally Tuning Zeigler Nichols Parameters for PID Controller to Enhance Transient Stability through SVC

Application of Flower Pollination Algorithm for Optimally Tuning Zeigler Nichols Parameters for PID Controller to Enhance Transient Stability through SVC

Implementation of SVC based on grey theory and fuzzy logic to improve LVRT capability of wind distributed generations

HVDC Commutation Failure Analysis and Simulation after Removing the Three Phase Short Circuit Fault

Contact Info

Product

Resources

About