Power System Stabilizer Based on Adaptive Control Techniques

Ghosh, Arnab; Ledwich, Gerard; Malik, O.P.; Hope, G.S.

doi:10.1109/tpas.1984.318503

Cited by 199 publications

(44 citation statements)

References 9 publications

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“…Previous studies [19,20] have demonstrated that the acceptable coefficients value of σ α k and σ ξ k in Formula (3) can be selected from the range of 3-4. This is because, as the local power grids become more closely linked, the frequency of the low-frequency oscillation gets lower.…”

Section: Stability Analysis Of Power System Based On Probability Eigementioning

confidence: 99%

“…The saturated robust power system stabilizer has been designed in the studies of Hisham, M.S and You, R [17,18] by considering the uncertainties of the power system. Zhang, Y et al [19,20] proposed an adaptive power system stabilizer based on adaptive control techniques. Under the assumption of normal distribution, the conventional eigenvalue sensitivity analysis was extended to a probabilistic environment, and two probabilistic indexes derived from the sensitivities of eigenvalue expectations and variances were introduced to the PSS site and parameter selection by Chung, C.Y et al in [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Model of Power System Stabilizer Adapting to Multi-Operating Conditions of Local Power Grid and Parameter Tuning

Hu¹,

Ji²,

Jin

et al. 2018

Sustainability

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Abstract:The rapid development of the modern power grid has resulted in significant changes to the dynamic characteristics of regional power grids. Moreover, the operating conditions of power grids are increasingly complex, and uncertainty factors are on the rise, which makes it difficult for a conventional power system stabilizer (PSS) to provide enough damping for the power system. To solve the problem where the conventional model and parameter-tuning method of a PSS cannot adapt to the multi-operating conditions of the modern power system, a new emergency control model of PSS (E-PSS) that can adapt to the multi-operating conditions of the local power grid and a method of parameter tuning based on probabilistic eigenvalue are proposed in this paper. An emergency control channel is also installed on the PSS2B. The conventional channel is used to control the system under normal operating conditions, which ensures that the system meets the conditions of dynamic stability in 99% of operating conditions, and the emergency control is adopted immediately in extreme conditions. Through the process of parameter tuning, the adaptability of the PSS to multi-operating conditions and damping coupling are both considered. Finally, it is verified that the emergency control model of the PSS and the parameter tuning method are effective and robust by a series of simulations based on MATLAB and its Power system analysis toolbox (PSAT). The rapidity of the emergency control can guarantee its effectiveness.

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Section: Stability Analysis Of Power System Based On Probability Eigementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Model of Power System Stabilizer Adapting to Multi-Operating Conditions of Local Power Grid and Parameter Tuning

Hu¹,

Ji²,

Jin

et al. 2018

Sustainability

View full text Add to dashboard Cite

show abstract

“…Alternative control techniques including self-tuning regulators, pole placement, robust control, and pole shifting have been investigated for the design of power system stabilizers (Ghosh, Ledwich, Malik, & Hoper, 1984;Chen, Malik, Hope, Qin, & Xu, 1993;Soliman, Elshafei, Shaltout, & Morsi, 2000;Wang, Hill, Middleton, & Gao, 1994). Adaptive control techniques are introduced to automate the tuning of power system stabilizers in Ghosh et al (1984).…”

Section: Introductionmentioning

confidence: 99%

“…Adaptive control techniques are introduced to automate the tuning of power system stabilizers in Ghosh et al (1984). The implementation of an adaptive power system stabilizer faces some technical difficulties.…”

Section: Introductionmentioning

confidence: 99%

A variable-structure adaptive fuzzy-logic stabilizer for single and multi-machine power systems

El-Shafei

El-Metwally

Shaltout

2005

Control Engineering Practice

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“…From the seventies, developments in digital technology have made possible to implement new controllers using adaptive control techniques [7]- [10]. These stabilizers provide better dynamic performance over a wide range of operating conditions, but they suffer from the major drawback of requiring parameter model identification, state observation and feedback gain calculations in realtime.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Power System Stabilizer Using ANFIS and Genetic Algorithms

Fraile-Ardanuy

Zufiria²

2005

Computational Intelligence and Bioinspired Systems

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Abstract. This paper presents an adaptive Power System Stabilizer (PSS) using an Adaptive Network Based Fuzzy Inference System (AN-FIS) and Genetic Algorithms (GAs). Firstly, genetic algorithms are used to tune a conventional PSS on a wide range of operating conditions and then, the relationship between these operating points and the PSS parameters is learned by the ANFIS. The ANFIS optimally selectes the classical PSS parameters based on machine loading conditions. The proposed stabilizer has been tested by performing nonlinear simulations using a synchronous machine-infinite bus model. The results show the robustness and the capability of the stabilizer to enhance system damping over a wide range of operating conditions and system parameter variations.

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Power System Stabilizer Based on Adaptive Control Techniques

Cited by 199 publications

References 9 publications

Model of Power System Stabilizer Adapting to Multi-Operating Conditions of Local Power Grid and Parameter Tuning

Model of Power System Stabilizer Adapting to Multi-Operating Conditions of Local Power Grid and Parameter Tuning

A variable-structure adaptive fuzzy-logic stabilizer for single and multi-machine power systems

Adaptive Power System Stabilizer Using ANFIS and Genetic Algorithms

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