Electric-drive operation in compressor stations for gas-transport systems is considered. Principles of organization and synthesis for regression control algorithms are proposed, so as to ensure that the gas-pumping equipment and the systems for air cooling of the gas will be unaffected by stochastic perturbations. Analysis of the resulting models of a frequency-controlled electric drive by means of experiment-design theory shows that the control algorithms are adequate and effective. The conclusions are: (1) Experimental data for the operation of electric drives in a compressor station indicate that stochastic technological and metereological factors are continuously acting on the system. The variation coefficient for random loading of the frequency-controlled electric drive is 0.4 to 0.9, and the corresponding energy is greatest in the frequency spectrum 0.01 Hz to 4.0 Hz. (2) Principles have been developed for statistical formalization of the perturbations, on the basis of regression analysis and experiment-design theory. An applied method has been theoretically elaborated for calculating the regression control algorithms of frequency-controlled electric drives with perturbations of the second kind. Models for the control system of the frequency-controlled fan drive in the gas-cooling system that are unaffected by assorted external perturbations have been derived. Linearized and nonlinear multifactorial regression algorithms have been calculated for the control of the frequency-controlled electric drives in a GATs-50- 4-M3 fan with VASO16-14-24 electric motors, within a 2AVG-75s gas-cooling system. (3) Analysis of the regression algorithms and the results of correlation, covariation, and dispersion analysis on the basis of MathCAD software shows that all the models and control algorithms obtained are adequate for invariant systems.


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    Title :

    Electric drive systems in compressor stations with stochastic perturbations


    Additional title:

    Elektrische Antriebe in Gas-Kompressorstationen mit stochastischen Parameterabweichungen


    Contributors:

    Published in:

    Publication date :

    2013


    Size :

    6 Seiten, 4 Bilder, 6 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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