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Analiza statystyczna danych oraz prognozy rynkowych cen energii (RCE) w Polsce z wyprzedzeniem do 1 godziny

Piotrowski Paweł, Baranowski Marcin, Bączek Adrian, Niedźwiecki Radosław

Elektro Info

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2023

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nr 4

81--85

PL

W artykule przedstawiono analizę statystyczną danych oraz prognozy rynkowych cen energii (RCE) z wyprzedzeniem do 1 godziny. Sformułowano wnioski końcowe z wykonanych prognoz oraz analiz statystycznych.

EN

The article presents a statistical analysis of data and forecasts of energy prices (RCE) in Poland up to 1 hour ahead. The conclusions have been drawn based on forecasts outcome and statistical analysis.

2

Forecasting European thermal coal spot prices

Krzemień A., Riesgo Fernandez P., Suárez Sánchez A., Sánchez Lasheras F.

Journal of Sustainable Mining

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2015

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Vol. 14, iss. 4

203--210

EN

This paper presents a one-year forecast of European thermal coal spot prices by means of time series analysis, using data from IHS McCloskey NW Europe Steam Coal marker (MCIS). The main purpose was to achieve a good fit for the data using a quick and feasible method and to establish the transformations that better suit this marker, together with an affordable way for its validation. Time series models were selected because the data showed an autocorrelation systematic pattern and also because the number of variables that influence European coal prices is very large, so forecasting coal prices as a dependent variable makes necessary to previously forecast the explanatory variables. A second-order Autoregressive process AR(2) was selected based on the autocorrelation and the partial autocorrelation function. In order to determine if the results obtained are a good fit for the data, the possible drivers that move the European thermal coal spot prices were taken into account, establishing a hypothesis in which they were divided into four categories: (1) energy side drivers, that directly relates coal prices with other energy commodities like oil and natural gas; (2) demand side drivers, that relates coal prices both with the Western World economy and with emerging economies like China, in connection with the demand for electricity in these economies; (3) commodity currency drivers, that have an influence for holders of different commodity currencies in countries that export or import coal; and (4) supply side drivers, involving the production costs, transportation, etc. Finally, in order to analyse the time series model performance a Generalized Regression Neural Network (GRNN) was used and its performance compared against the whole AR(2) process. Empirical results obtained confirmed that there is no statistically significant difference between both methods. The GRNN analysis also allowed pointing out the main drivers that move the European Thermal Coal Spot prices: crude oil, USD/CNY change and supply side drivers.

3

Price forecasting in the balancing mechanism

Mordasiewicz Ł.

Rynek Energii

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2011

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nr 3

153-160

EN

This paper concerns the problems of price forecasting on the balancing market in Poland. There are three types of models presented Moving Weighted Average, econometric model based on OLS method and ARMAX. Generation of "buy" or "sell" signals is the main aim of this paper. Models' outputs have been tested in the proposed trading strategy and results are shown as profits.

PL

Artykuł dotyczy problematyki prognozowania cen na rynku bilansującym w Polsce. Zaprezentowane zostały trzy rodzaje modeli: ważonej średniej kroczącej, model ekonometryczny bazujący na metodzie najmniejszych kwadratów oraz ARMAX. Jako główny cel modeli uważa się generację sygnałów kupna-sprzedaży. Dane wyjściowe z modeli zostały poddane zaproponowanej strategii rynkowej, której to wyniki przedstawiono jako przychody z jej realizacji.