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EN
The paper presents selected results of research on modelling a system of the POLISH Power Exchange in the MATLAB and Simulink environment. Modelling capabilities of various toolboxes and Matlab language were presented. Special attention was paid to identification modelling using System Identification Toolbox, neural modelling using Neural Network Toolbox and simulation modelling using Simulink. Research experiments were preformed based on the Day Ahead Market quotations. The obtained models of th type in SIT, an artificial neural network (ANN) in NNT and a block diagram in Simulink were subjected to comparative and sensitivity tests. Final results were interpreted.
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EN
In this paper an analysis of the time series on the Day Ahead Market (DAM) of the Polish Power Exchange is presented. In this analysis Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models are used to describe the time series of rates of return of price of electric energy on DAM. This analysis is based on the data from July 2002 to June 2004.
PL
W pracy została przedstawiona analiza szeregów czasowych stóp zwrotu cen energii elektrycznej notowanych na rynku dnia następnego (RDN) Towarowej Giełdy Energii SA od lipca 2002 do czerwca 2004 r. za pomocą modeli GARCH. Celem pracy jest odpowiedź na pytanie, czy modele GARCH efektywnie opisują kształtowanie się cen energii elektrycznej na parkiecie polskiej giełdy energii i czy można je wykorzystywać do modelowania szeregów czasowych stóp zwrotu cen energii elektrycznej.
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