Comparison of unit addition and fast Fourier transform methods for generation system reliability evaluation

Singh, Chanan; Gubbala, N.

doi:10.1016/0142-0615(95)00055-0

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…The generation model is usually presented in the form of a capacity outage probability table (COPT) which includes the available or unavailable capacity levels and their corresponding probabilities. The COPT has been created using different techniques [6][7]. These approaches can be categorized into two main categories analytical methods and Monte Carlo simulation (MCS) techniques .Analytical approaches require mathematical modeling for the generating units.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Electrical Power Generation Modeling Using Genetic Algorithm

Alabdulwahab¹

2010

IJCA

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Generation system reliability assessment is an important task which can be performed using deterministic or probabilistic techniques. The probabilistic approaches have significant advantages over the deterministic methods. However, more complicated modeling is required by the probabilistic approaches. Power generation model is a basic requirement for this assessment. One form of the generation models is the well known capacity outage probability table (COPT). Different analytical techniques have been used to construct the COPT. These approaches require considerable mathematical modeling of the generating units. The units" models are combined to build the COPT which will add more burdens on the process of creating the COPT. This paper proposes the utilization of the Genetic Algorithm (GA) to sample the states of the COPT without engaging in analytical units modeling. The simple binary representation, "0" and "1" is used to model the states of generating units. The effect of the GA parameters is examined. The proposed technique is proven to be an effective approach to build the generation model. The proposed technique is applied to the RBTS. General TermsModeling, Genetic algorithm application.

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Section: Introductionmentioning

confidence: 99%

Probabilistic Electrical Power Generation Modeling Using Genetic Algorithm

Alabdulwahab¹

2010

IJCA

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Wavelet Transform-Spectral Kurtosis Based Hybrid Technique for Disturbance Detection in a Microgrid

Ray

Foo

Krishnan

et al. 2018

2018 IEEE Power &Amp; Energy Society General Meeting (PESGM)

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Frequency Characterizations of Epoxy/CNTs Composites under Compression at Different Strain Rates

Chang

Jiang

2016

Advanced Composites Letters

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This paper reports the compression behavior of epoxy composites with various carbon nanotubes (CNTs) contents, under quasi-static and high strain rate compression. The compression behaviours of epoxy composites with various CNTs contents under quasi-static and high strain rate compression were compared and analyzed in the frequency domain using the fast Fourier transform (FFT) method. The results show that the compression behavior, amplitude spectrum and phase spectrum of the epoxy/CNTs composite are strain rate sensitive. The epoxy/CNTs composites can absorb higher energy in a specific frequency range.

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Comparison of unit addition and fast Fourier transform methods for generation system reliability evaluation

Cited by 3 publications

References 6 publications

Probabilistic Electrical Power Generation Modeling Using Genetic Algorithm

Probabilistic Electrical Power Generation Modeling Using Genetic Algorithm

Wavelet Transform-Spectral Kurtosis Based Hybrid Technique for Disturbance Detection in a Microgrid

Frequency Characterizations of Epoxy/CNTs Composites under Compression at Different Strain Rates

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