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Keywords

Perceptron Artificial Neural Network
Radial Artificial Neural Network
Recursive Artificial Neural Network
neural model quality
Day-Ahead Market
Polish Power Exchange
Mean square error
determination index

Abstract

The work contains the results of the Day-Ahead Market modeling research at Polish Power Exchange taking into account the numerical data on the supplied and sold electricity in selected time intervals from the entire period of its operation (from July 2002 to June 2019). Market modeling was carried out based on three Artificial Neural Network models, ie: Perceptron Artificial Neural Network, Recursive Artificial Neural Network, and Radial Artificial Neural Network. The examined period of the Day-Ahead Market operation on the Polish Power Exchange was divided into sub-periods of various lengths, from one month, a quarter, a half a year to the entire period of the market's operation. As a result of neural modeling, 1,191 models of the Market system were obtained, which were assessed according to the criterion of the least error MSE and the determination index R2.

https://doi.org/10.34739/si.2019.23.05
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