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1

The impact of the size of the training set on the predictive abilities of neural models on the example of the Day-Ahead Market System of TGE S.A.

Ruciński Dariusz

Studia Informatica : systems and information technology

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2022

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Vol. 1(26)

5--22

EN

The main object of the research was to examine the acceptable time horizon that could be predicted by previously learned models of the Day-Ahead Market (DAM) TGE S.A. system. The article contains the results of research on the predicting ability of different ANN models of the DAM TGE S.A. The research was conducted based on data covering the operation of the Polish stock exchange in the period from 2002 to 2019 (the first half of the year). The research was carried out based on the learned ANN models of the DAM system. Data were taken for examination covering the time from 2002 to 2019 (1st half of the year) and was divided into a different period, i.e., a month, a quarter, and a half-year., year, etc. The MSE, MAE, MAPE, and R2 were adopted as the criteria for assessing the ability of individual models to predict electricity prices. The research was carried out by successively expanding forecasting periods in a rolling manner. For example, for a half-year, prediction time intervals were increased from one week to month, two months, quarter, half-year, etc. results for a model representing a given period. A lot of interesting research results were obtained.

2

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

Ruciński Dariusz

Control and Cybernetics

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2022

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Vol. 51, No. 4

557--583

EN

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.

3

Cluster analysis as a preliminary problem in neural modelling of the Polish Power Exchange

Tchórzewski Jerzy, Jezierski Jakub

Information Systems in Management

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2019

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Vol. 8, No. 1

69--81

EN

The work focuses on cluster analysis as a preliminary problem in neural model- ling based on the data quoted on the Day Ahead Market of the Polish Power Ex- change as a subsystem of the system of Towarowa Giełda Energii S.A. [Polish Pow- er Exchange]. The paper contains the results of literature research related to cluster analysis methods, description of possible applications of artificial neural networks SOM for mapping information on the volume of electrical power sold and prices ob- tained, description of possible applications of MATLAB and Simulink environment, and especially Neural Network Toolbox for mapping knowledge, and cluster analy- sis performed for selected data.

4

Funkcjonowanie wielu wyznaczonych operatorów na krajowym rynku energii elektrycznej

Krupiński S., Juszczuk M., Smolira K., Paska J.

Rynek Energii

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2018

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Nr 5

73--82

PL

Na podstawie Rozporządzenia Komisji Europejskiej (UE) 2015/1222 CACM ustanawiającego wytyczne dotyczące alokacji zdolności przesyłowych i zarządzania ograniczeniami przesyłowymi dopuszczono możliwość funkcjonowania wielu Wyznaczonych Operatorów Rynku Energii (NEMO – ang. Nominated Energy Market Operator) na krajowych ryn-kach energii elektrycznej. Celem uregulowania działania wielu NEMO w polskiej strefie cenowej oraz zapewnienia niezbęd-nych danych i finansowania mechanizmów łączenia rynków przez odpowiednie NEMO, PSE na podstawie art. 45 i 57 Rozporządzenia CACM przygotowały oraz przedłożyły do zatwierdzenia Prezesowi URE „Warunki dotyczące alokacji międzyobszarowych zdolności przesyłowych i innych niezbędnych mechanizmów umożliwiających działanie więcej niż jednego NEMO w Polsce” (MNA). W artykule przedstawiono: zasady funkcjonowania krajowego rynku energii elektrycznej w warunkach obecności wielu NEMO, z perspektywy OSP; ogólny proces zachodzący w ramach fazy pre-coupling, coupling i postcoupling; zasady oraz architekturę procesów zachodzących na rynku bilansującym.

EN

Pursuant to the Regulation of the European Commission (EU) 2015/1222 CACM of 24 July 2015 laying down guidelines on capacity allocation and congestion management, the possibility of functioning of many Nominated Energy Market Operator (NEMO) on domestic electricity markets was accepted. The aim of regulating the operation of many NEMOs in the Polish price zone and providing the necessary data and financing mechanisms of combining the markets by the appropriate NEMO, Polish Power Grid Company on the basis of art. 45 and 57 of the CACM Regulation prepared and submitted to the President of Polish NRA for approval "Conditions regarding the allocation of inter-area transmission capacities and other necessary mechanisms enabling the operation of more than one NEMO in Poland" (MNA). The article present: principles for the functioning of the national electricity market in the presence of many NEMOs, from the perspective of the TSO; the general process taking place in the pre-coupling, coupling and post-coupling phase; principles and architecture of processes taking place on the balancing market.

5

Capabilities of MATLAB and Simulink related to modelling of Polish power exchange

Tchórzewski J.

Information Systems in Management

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2016

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Vol. 5, No. 3

424--435

EN

The paper presents selected results of research on modelling a system of the POLISH Power Exchange in the MATLAB and Simulink environment. Modelling capabilities of various toolboxes and Matlab language were presented. Special attention was paid to identification modelling using System Identification Toolbox, neural modelling using Neural Network Toolbox and simulation modelling using Simulink. Research experiments were preformed based on the Day Ahead Market quotations. The obtained models of th type in SIT, an artificial neural network (ANN) in NNT and a block diagram in Simulink were subjected to comparative and sensitivity tests. Final results were interpreted.