scholarly journals Application of Prony analysis to the determination of modal content and equivalent models for measured power system response

1991 ◽  
Vol 6 (3) ◽  
pp. 1062-1068 ◽  
Author(s):  
J.F. Hauer
Keyword(s):  
Power System ◽  
System Response ◽  
Equivalent Models ◽  
Measured Power ◽  
Prony Analysis

scholarly journals Initial results in Prony analysis of power system response signals

1990 ◽  
Vol 5 (1) ◽  
pp. 80-89 ◽  
Author(s):  
J.F. Hauer ◽  
C.J. Demeure ◽  
L.L. Scharf
Keyword(s):  
Power System ◽  
System Response ◽  
Initial Results ◽  
Prony Analysis

MAPE - An Alternative Fitness Metric for Prony Analysis of Power System Signals

2018 ◽  
Vol 19 (6) ◽  
Author(s):  
Krishna Rao ◽  
K.N Shubhanga
Keyword(s):  
Power System ◽  
New England ◽  
Case Studies ◽  
Processing Time ◽  
Signal To Noise Ratio ◽  
Estimation Error ◽  
Percentage Error ◽  
System Response ◽  
Minimum Number ◽  
Prony Analysis

Abstract Phasor Measurement Units have facilitated tracking of oscillations in power system response signals. This has provided an impetus for identifying unstable component modes directly from oscillatory signals. Prony analysis, the earliest method proposed for this purpose, throws up some trivial modes. These not only distract the analyzer but also prolong processing time thereby delaying corrective action. Hence the fitness metric chosen should serve to minimize the number of trivial modes. The conventional fitness metric is Signal-to-Noise Ratio (SNR), which is actually Signal-to- Estimation error Ratio (SER). This paper proposes that Mean Absolute Percentage Error (MAPE) can also serve well as a fitness metric. It is shown through case studies carried out on well-known four-machine power system that there are a few cases where MAPE performs better than SER while in some instances SER works better. This inference is verified even in the presence of measurement noise. Hence a novel fitness metric is proposed combining MAPE with SER. Case studies on simulated signals obtained from New England-power system prove that this novel metric can achieve considerable reduction in processing time. Besides, an exponential binary search has been suggested for determining the optimal model order in minimum number of iterations.

Optimal Robust Fixture Configuration Design Using Computer Experiment

Manufacturing ◽  
2003 ◽  
Author(s):  
L. Shelley Xie ◽  
Agus Sudjianto
Keyword(s):  
Evaluation Method ◽  
Robustness Analysis ◽  
Optimal Solution ◽  
Computer Experiment ◽  
System Response ◽  
New Approach ◽  
New Information ◽  
Reliability Method ◽  
Fixture Configuration

A new FEA based design approach of optimal robust fixture configuration is proposed in this paper, which employs a surrogate model through computer experiment to significantly reduce the intensive computing effort involving numerous FEA system response evaluations. The effects of the fixture variability to the workpiece performance variability are assessed through an efficient robustness evaluation method, First Order Reliability Method (FORM), based on the surrogate computer model. Not restricted to primary datum surface, this new approach enables simultaneous determination of robust locator/clamp locations and clamping forces for a deformable workpiece and thus captures interaction between locating and clamping. The effectiveness of this approach is illustrated though an application example. The results of robustness analysis reveal new information and suggest that the optimal solution resulted from deterministic optimization may not be the best solution when the design is subjected to variability.

scholarly journals A GENETIC BASED TECHNIQUE FOR THE DETERMINATION OF POWER SYSTEM TOPOLOGICAL OBSERVABILITY

2014 ◽  
pp. 16-21
Author(s):  
S. Vazquez-Rodriguez ◽  
R. J. Duro
Keyword(s):  
Genetic Algorithms ◽  
Power Systems ◽  
Power System ◽  
Spanning Tree ◽  
Point Of View ◽  
Genetic Operators ◽  
Building Process ◽  
Phenotype Transformation

In this paper we have addressed the problem of observability of power systems from the point of view of topological observability and using genetic algorithms for its determination. The objective is to find a way to determine if a system is observable by establishing if a spanning tree of the system that verifies certain properties with regards to the use of available measurements can be obtained. To this end we have developed a genotype-phenotype transformation scheme for genetic algorithms that permits using very simple genetic operators over integer based chromosomes which after a building process can become very complex trees. The procedure was successfully applied to standard benchmark systems and we present some results for one of them.

Galerkin Scheme-Based Determination of Survival Probability of Oscillators With Fractional Derivative Elements

2016 ◽  
Vol 83 (12) ◽  
Author(s):  
Pol D. Spanos ◽  
Alberto Di Matteo ◽  
Yezeng Cheng ◽  
Antonina Pirrotta ◽  
Jie Li
Keyword(s):  
Fractional Derivative ◽  
Survival Probability ◽  
Stochastic Averaging ◽  
Kolmogorov Equation ◽  
System Response ◽  
Statistical Linearization ◽  
Van Der Pol ◽  
Galerkin Scheme ◽  
Confluent Hypergeometric Functions

In this paper, an approximate semi-analytical approach is developed for determining the first-passage probability of randomly excited linear and lightly nonlinear oscillators endowed with fractional derivative elements. The amplitude of the system response is modeled as one-dimensional Markovian process by employing a combination of the stochastic averaging and the statistical linearization techniques. This leads to a backward Kolmogorov equation which governs the evolution of the survival probability of the oscillator. Next, an approximate solution of this equation is sought by resorting to a Galerkin scheme. Specifically, a convenient set of confluent hypergeometric functions, related to the corresponding linear oscillator with integer-order derivatives, is used as orthogonal basis for this scheme. Applications to the standard viscous linear and to nonlinear (Van der Pol and Duffing) oscillators are presented. Comparisons with pertinent Monte Carlo simulations demonstrate the reliability of the proposed approximate analytical solution.

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