The power coefficients of DC electric rolling stock in the regenerative braking mode
DOI:
https://doi.org/10.15802/etr.v0i11.83777Keywords:
regenerative braking, power factor, stochastic process, electric locomotiveAbstract
The need to estimate not only the quality of recovered electricity, but also the energy performance of electric rolling stock, as a generator of energy, is not debated. At the same time the indexes as a power factor λ and a reactive power coefficient tgφ are not studied enough. The complexity of this task is constrained primarily by a random (stochastic) nature of the voltage and current in the regenerative braking mode. The paper covers a dispersion method for studying λ and tg, which is based on the correlation theory of stochastic processes. The results of numerical calculations of λ and tgφ are performed and analyzed for the VL11M6 and VL8 electric locomotives, as well as for the EPL2T multiple-unit train, which operate in the Prydniprovsk railway. It was established, that the time dependences of λ(t) and (tgφ)(t) are stochastic processes with sharply changing characteristics. These dependences have stationary character in the separate phases of regenerative braking. In case of a total time of trip they have a non-stationary character. The results of probabilistic and statistical analyses show that the statistical distributions of tgφ are close to the Gaussian’s Law. At the same time the distributions of random quantity of λ follow to a normal asymmetrical law with the dispersion function. The root-mean-square deviations of λ(t) and tgφ(t) have significant values, therefore the coefficients of λ are less than the normative values of 0,92…0,95 in the most phases of regenerative braking. The values of tgφ exceed the allowable limit of 0,25. Analysis of the statistical distributions of λ and tgφ for all types of electric rolling stock confirms an idea, that the coefficient tgφ characterizes the "quality" of energy processes in a DC power system with greater precision than power coefficient λ.
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