Neural Models of Demands for Electricity - Prediction and Risk Assessment

• Autorzy: Protasiewicz J. , Szczepaniak P. S.

Warianty tytułu

PL

Neuronowe modele zapotrzebowania na energie˛ elektryczna˛ - prognozowanie i ocena ryzyka

• Języki publikacji: EN

Abstrakty

EN

Two neural systems for forecasting the electricity demand by the group of retail consumers are presented along with two methods for risk assessment of demand prediction models. The first forecasting system is composed of series-connected local neural predictors in the form of multilayer perceptron (MLP) networks. The system is mainly formed on the basis of expert knowledge and statistical tests. The second forecasting system has two levels. The first contains a neural classifier and the second consists of a set of local neural predictors. The classifier is built on the basis of a self-organising neural network (SOM). MLP or radial basis function (RBF) networks are used as predictors. Finally, two methods for assessing the risk of forecasting models are proposed. These consider financial risk measures such as value at risk (VaR) and conditional value at risk (CVaR). Possible economic losses posed by the application of predictions from a forecasting model are calculated using these risk measures. The risk analysis facilitates the selection of the forecasting model that generates the smallest risk of losses when selling energy contracts. The proposed methods are tested using data from the Polish electricity market.

PL

W pracy zostały przedstawione dwa neuronowe systemy przeznaczone do prognozowania zapotrzebowania na energię elektryczną grupy konsumentów detalicznych. Ponadto zaprenzetowano dwie metody oceny ryzyka modeli prognozowania.

Słowa kluczowe

EN

electricity market; neural networks; prediction models

PL

rynek energii elektrycznej; sieci neuronowe; model prognozowania

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2012
• Tom: R. 88, nr 6
• Strony: 272--279
• Opis fizyczny: Bibliogr. 25 poz., tab.

Twórcy

autor

Protasiewicz J.

autor

Szczepaniak P. S.

• Information Processing Institute, Laboratory of Intelligent Information Systems,

Bibliografia

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