<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The purpose of the work, presented in this article, was to obtain a price model for the Day-Ahead Market of the Polish Power Exchange (PPE). The resulting proposed models are based on Artificial Neural Networks (ANN), and the involved suggested improvement concerns the proper selection of both the type of network and the factors used in model construction. The article also proposes a new approach to the ANN with the implemented quantum learning model. The purpose of the research was to analyze factors, which exert influence on the quality of the model, like weather or economic factors, or the type of neural network used. The model determines the relationship between the price and the volume of electricity for a given hour of the day.</p>
<p>The mean square error and the coefficient of determination were used to measure the quality of the obtained models. The results from the experiments performed indicate the possibility of developing improved models of the Day-Ahead Market.</p>
</abstract>

The purpose of the work, presented in this article, was to obtain a price model for the Day-Ahead Market of the Polish Power Exchange (PPE). The resulting proposed models are based on Artificial Neural Networks (ANN), and the involved suggested improvement concerns the proper selection of both the type of network and the factors used in model construction. The article also proposes a new approach to the ANN with the implemented quantum learning model. The purpose of the research was to analyze factors, which exert influence on the quality of the model, like weather or economic factors, or the type of neural network used. The model determines the relationship between the price and the volume of electricity for a given hour of the day.
The mean square error and the coefficient of determination were used to measure the quality of the obtained models. The results from the experiments performed indicate the possibility of developing improved models of the Day-Ahead Market.

Neural modeling of prices on the Day-Ahead Market at the Polish Power Exchange supported by an evolutionary algorithm and inspired by quantum computing

University of Natural Sciences and Humanities

Control and Cybernetics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The purpose of the work, presented in this article, was to obtain a price model for the Day-Ahead Market of the Polish Power Exchange (PPE). The resulting...

Neural modeling of prices on the Day-Ahead Market at the Polish Power Exchange supported by an evolutionary algorithm and inspired by quantum computing

Online veröffentlicht: 24. Feb. 2024

Seitenbereich: 557 - 583

Eingereicht: 01. Okt. 2022

Akzeptiert: 01. Dez. 2022

DOI: https://doi.org/10.2478/candc-2022-0029

Schlüsselwörter
Polish Power Exchange, Day Ahead Market, modeling of energy market, quantum inspired neural network

© 2022 Dariusz Ruciński, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Neural modeling of prices on the Day-Ahead Market at the Polish Power Exchange supported by an evolutionary algorithm and inspired by quantum computing

Online veröffentlicht: 24. Feb. 2024

Seitenbereich: 557 - 583

Eingereicht: 01. Okt. 2022

Akzeptiert: 01. Dez. 2022

DOI: https://doi.org/10.2478/candc-2022-0029

SchlüsselwörterPolish Power Exchange, Day Ahead Market, modeling of energy market, quantum inspired neural network

© 2022 Dariusz Ruciński, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Polish Power Exchange, Day Ahead Market, modeling of energy market, quantum inspired neural network