Power-system stabilizer (PSS) design by probabilistic sensitivity indexes (PSIs)

Chung, C.Y.; Wang, K.W.; Tse, C.T.; Niu, Rong

doi:10.1109/tpwrs.2002.800914

Cited by 61 publications

(36 citation statements)

References 17 publications

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“…Meanwhile, the load states corresponding to the interval damping ratios are obtained. When the weakest damping ratio is at the upper limit, the active and reactive power of load 3,4,7,8,15,16,18,25,26, 27 are at their upper limits, while the active power of load 12, 20, 24, 28, 29 are not at their interval limits. …”

Section: Calculation Of Interval Damping Ratio Under Uncertain Load Imentioning

confidence: 99%

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Calculation of interval damping ratio under uncertain load in power system

Xing¹,

Chen²,

Wu³

2012

Bulletin of the Polish Academy of Sciences: Technical Sciences

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Abstract. The problem of small-signal stability considering load uncertainty in power system is investigated. Firstly, this paper shows attempts to create a nonlinear optimization model for solving the upper and lower limits of the oscillation mode's damping ratio under an interval load. Then, the effective successive linear programming (SLP) method is proposed to solve this problem. By using this method, the interval damping ratio and corresponding load states at its interval limits are obtained. Calculation results can be used to evaluate the influence of load variation on a certain mode and give useful information for improvement. Finally, the proposed method is validated on two test systems.

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Section: Calculation Of Interval Damping Ratio Under Uncertain Load Imentioning

confidence: 99%

“…K.W. Wang and others [6][7][8][9] studied the probabilistic eigenvalue analysis method when the load is uncertain. In their studies, assuming normal distribution, normal operation values of load powers are used as the corresponding means.…”

Section: Introductionmentioning

confidence: 99%

Calculation of interval damping ratio under uncertain load in power system

Xing¹,

Chen²,

Wu³

2012

Bulletin of the Polish Academy of Sciences: Technical Sciences

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“…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]. Shu Liu et al [24] proposed a nonlinear analysis framework based on normal form (NF) theory and center manifold reduction to determine the most effective selection of generating units to be equipped with power system stabilizers.…”

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

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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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“…To consider a wide range of operating conditions, conventional eigenanalysis has been extended to probabilistic environment and probabilistic damping controller design has been developed for the conventional PSS [16,17]. With nodal voltages regarded as basic random variables and determined by probabilistic load flow calculation, the probabilistic distribution of each eigenvalue was obtained from the probabilistic attributes of the nodal voltages, and described by its expectation and variance under the assumption of a normal distribution.…”

Section: Introductionmentioning

confidence: 99%

“…In this approach, probabilistic sensitivity indices (PSIs) are proposed to facilitate 'robust' PSS siting [16]. Further, a coordinated synthesis model of PSS parameters is developed and a quasi-Newton nonlinear programming is used to solve the probabilistic PSS design problem [17]. In addition, the differential evolution (DE) method in evolutionary computation (EC) has been applied in Reference [18] to alleviate the problem of initial conditions dependence and the problem of local minimum trapping, which exist in conventional nonlinear optimization methods.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic power system stabilizer design with consideration of optimal siting using recursive Genetic Algorithm

Wang

Chung

Wong

et al. 2010

Int Trans Elec Energy Syst

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SUMMARYThis paper proposes an approach for the probabilistic power system stabilizer (PSS) design problem with consideration of optimal siting of the PSSs under multiple operating conditions. The design problem is first formulated as a combinational optimization problem which contains discrete and continuous variables. The paper then develops a recursive Genetic Algorithm (GA) to solve the design problem. An integer-binary mixed coding scheme and a partially matched crossover (PMX) operator are applied for the recursive GA for performance enhancement. The effectiveness of the proposed recursive GA approach for probabilistic PSS design scheme is demonstrated on two test systems.

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Power-system stabilizer (PSS) design by probabilistic sensitivity indexes (PSIs)

Cited by 61 publications

References 17 publications

Calculation of interval damping ratio under uncertain load in power system

Calculation of interval damping ratio under uncertain load in power system

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

Probabilistic power system stabilizer design with consideration of optimal siting using recursive Genetic Algorithm

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