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Comparative Study of the Identification Methods of the Management System of the Day-Ahead Market of Polish Energy Market S.A.

Marlęga Radosław

Studia Informatica : systems and information technology

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2021

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Vol. 1-2(25)

67--86

EN

Nowadays, identification and neural methods are used more and more often in modeling IT forecasting systems in addition to analytical methods. Six characteristic models used to forecast the Day- Ahead Market system functioning as a transaction management system at the Polish Power Exchange (POLPX) and the Nord Pool Spot market have been selected for comparative analysis. The research was preceded by a detailed discussion of modern criteria used to assess the quality of model fitting to the system, namely: effectiveness, efficiency, and robustness. In the literature, there are two main groups of system modeling methods, namely time series modeling methods and identification modeling methods, including neural modeling methods. Modeling usually results in such models as parametric models and artificial neural networks learned neural models of the Day-Ahead Market, as well as time series models, among others. In the comparative analysis, special attention was paid to the accuracy of the obtained models concerning the system. It has been pointed out that the studied solutions used to measure the accuracy of modeling criteria such as accuracy of fit or efficiency, and did not use the modeling efficiency, which is very important in IT forecasting systems for such large markets as the Day-Ahead Market of POLPX. The search for the best market models, including identification models of the Day- Ahead Market operation that can be used in electricity price forecasting is a very important issue both from the point of view of algorithmic solutions and economical solutions.

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Neural modelling of electricity prices quoted on the Day-Ahead Market of TGE S.A. shaped by environmental and economic factors

Ruciński Dariusz

Studia Informatica : systems and information technology

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2020

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Vol. 1-2(24)

25--35

EN

The paper contains the results of research on the impact of the number of factors used to build the Day-Ahead Market model at Polish Power Exchange S.A. Five models with a different number of factors influencing the model were tested. To test the quality of models according to the adopted evaluation criteria, i.e., mean square error and the coefficient of determination for the weighted average prices sold in a given hour of the day, the influence of weather factors, socio-economic factors and energy demand were adopted. The results obtained from the analysis show a relatively high correctness of the simplest of the adopted models, which differs slightly from the best model.

3

Evolutionary algorithm inspired by the methods of quantum computer sciences for the improvement of a neural model of the electric power exchange

Tchórzewski J., Ruciński D.

Information Systems in Management

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2017

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Vol. 6, No. 4

343--355

EN

The work contains results of research on the possibility to improve the neural model of the Electric Power Exchange (polish: Towarowa Giełda Energii Elektrycznej – TGEE) in MATLAB and Simulink environment using evolutionary algorithm inspired by quantum computer science. The developed artificial neural network was trained using data for the Day Ahead Market, assuming the joint volume of supplied and sold electrical energy [MWh] as the input quantities in each hour of the 24-hour day, and average prices [PLN/MWh] as output quantities. The obtained model of the exchange system was improved using the evolutionary algorithm, and further improvement in the accuracy of the model by supplementing the evolutionary algorithm using quantum solutions, related to the initial population, crossover and mutation operators, selection, etc. were proposed.

4

Równowaga Nasha w grach niekooperacyjnych na Rynku Dnia Następnego

Borgosz-Koczwara M., Wyłomańska A.

Energetyka

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2003

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nr 12

808-812

PL

Potraktowano Rynek Dnia Następnego jako grę niekooperacyjną, w której uczestnikami są producenci energii. Zajęto się problemem optymalnej strategii graczy, kierujących się zasadą maksymalizacji zysku. Do analiz wykorzystano techniki używane w teorii gier, a kluczowym rezultatem pracy było znalezienie punktu równowagi Nasha.

EN

A Day Ahead Market as a non co-operative game in which the power generators are the players is considered in the paper. There is solved the problem of optimal strategy for the players consisting in maximisation of their profit. In the analyses the game theory techniques are used. Finding the Nash Equilibrium strategy for the players is the main result analyses.