1982
DOI: 10.1109/tpas.1982.317524
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Selective Modal Analysis with Applications to Electric Power Systems, PART I: Heuristic Introduction

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Cited by 357 publications
(144 citation statements)
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“…See [13] and [14] for developments of this idea. Choosing W = V 1 ensures that nv P k=1 p kq = 1 and enables a matrix of participation factors with rows corresponding to z and columns corresponding to eigenvalues f q g nv q=1 to be computed as…”
Section: Local Mean-covariance Coupling Analysismentioning
confidence: 99%
“…See [13] and [14] for developments of this idea. Choosing W = V 1 ensures that nv P k=1 p kq = 1 and enables a matrix of participation factors with rows corresponding to z and columns corresponding to eigenvalues f q g nv q=1 to be computed as…”
Section: Local Mean-covariance Coupling Analysismentioning
confidence: 99%
“…. ., n) denote the imaginary part of mth electro-mechanical modes under different operating conditions and a selective modal analysis method is adopted to identify these modes [21];˛0 and 0 are damping threshold values for pre-contingency condition,˛C and C denote damping threshold values for post-contingency condition.…”
Section: Optimization Modelmentioning
confidence: 99%
“…The concept of participation factor was developed in [11] to measure the degree of participation of a state variable in a mode. Therefore, participation factor p ki can be interpreted as the weight of the participation of ith mode in the kth state component.…”
Section: Calculation Of Eigenvalue Sensitivitiesmentioning
confidence: 99%
“…Therefore, participation factor p ki can be interpreted as the weight of the participation of ith mode in the kth state component. Simply, the participation factors can be seen as right eigenvectors weighted by left eigenvectors [11]. Using the participation values, a participation matrix can be formed as [11].…”
Section: Calculation Of Eigenvalue Sensitivitiesmentioning
confidence: 99%
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