The three-point approximations for a distribution function of uncertain parameter to estimate technical and economic indicators relevant for stochastic modeling

Kostiuk V.O., Cand. Sci. (Eng.)
Institute of General Energy of the National Academy of Sciences of Ukraine, 172 Antonovycha St., Kyiv, 03680, Ukraine
Language: Ukrainian
Source: Problemy zahal`noi enerhetyky - The Problems of General Energy, 2016, 2(45):26-33
https://doi.org/10.15407/pge2016.02.026
Section: Mathematical modeling of energy facilities and systems
UDC: [519.245+519.65]:620.92+621.31
Received: 14.04.2016
Published: 10.06.2016
Abstract: Simulation accuracy increase of a wide class of physicalobjects with uncertain technical and economic parameters, performed with deterministic and stochastic models (DSM), relevant for solving economic and mathematical problems and probabilistic methods use (Monte Carlo method points); for power systems in particular.
Standard functions of stochastic (uncertain) model parameters representation have been analyzed using the three-point estimate approach for distribution of probable values. Synthetic asymmetrical probability density function based on the standard normal distribution, which is suitable to draw the forecast and/or statistical distribution of possible values of modelled parameters for an energy facility, and the analytical records for the computation of the distribution moments. Variant and comparative price calculations has been completed using various probabilistic methods to indicate higher attainable accuracy of numerical modeling results provided the three-point approximation technique model is applied to estimate the model parameters.
Keywords: simulation in power systems, accuracy of estimate, stochastic parameter, three-point approximation, variance and factor analysis.
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