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Tytuł:
BIAVERAGE AND MULIMODALITY IN INVESTIGATING DISTRIBUTION OF ELECTRICITY PRICES
Autorzy:
Baszczyńska, Aleksandra
Pekasiewicz, Dorota
Powiązania:
https://bibliotekanauki.pl/articles/655941.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
kernel estimation
Hartigan test
dip statistic
biaverage
one-day-ahead market
Opis:
In the paper chosen statistical methods concerning analysis of random variable distributions are presented. Investigating modality of distribution is one of the most interesting and important stages in random variable analysis. Among others, the following methods can be used: kernel density estimation, the Hartigan test of unimodality and the biavarage. The example showing application of these methods from the one-day-ahead market of electricity is presented.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2014, 3, 302
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A methodology of identification and metaidentification research on the example of Day Ahead Market System
Autorzy:
Marlęga, Radosław
Powiązania:
https://bibliotekanauki.pl/articles/2201618.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
Day Ahead Market System
identification
MATLAB and Simulink environment
methodology
metaidentification
Opis:
The paper contains selected research results in the field of identification and metaidentification of the Day Ahead Market system of TGE S.A. Due to the proposed new approach to identification, a methodology for conducting research has been developed, which requires eight stages. Then, both the tasks and research objectives as well as the form of research occurring at all stages of research in order to meet the distinguished specific objectives and the general purpose of the research were shown in detail. Then an example of both identification and metaidentification of Day Ahead Market systems was shown. The obtained models and metamodels confirm the need and possibility of conducting this type of research at TGE S.A.
Źródło:
Studia Informatica : systems and information technology; 2022, 2(27); 109--137
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Neural modeling of prices on the Day-Ahead Market at the Polish Power Exchange supported by an evolutionary algorithm and inspired by quantum computing
Autorzy:
Ruciński, Dariusz
Powiązania:
https://bibliotekanauki.pl/articles/31342753.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
Polish Power Exchange
Day Ahead Market
modeling of energy market
quantum inspired neural network
Opis:
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.
Źródło:
Control and Cybernetics; 2022, 51, 4; 557-583
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
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.
Autorzy:
Ruciński, Dariusz
Powiązania:
https://bibliotekanauki.pl/articles/2175162.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
Day Ahead Market
MATLAB environment
Simulink environment
neural modeling
prediction time
electricity prices
Opis:
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.
Źródło:
Studia Informatica : systems and information technology; 2022, 1(26); 5--22
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Neural modelling of electricity prices quoted on the Day-Ahead Market of TGE S.A. shaped by environmental and economic factors
Autorzy:
Ruciński, Dariusz
Powiązania:
https://bibliotekanauki.pl/articles/2052267.pdf
Data publikacji:
2020
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
Polish Power Exchange
day ahead market
DAM
artificial neural network
system modelling
MATLAB
Opis:
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.
Źródło:
Studia Informatica : systems and information technology; 2020, 1-2(24); 25-35
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Correction of the parametric model of the Day-Ahead Market system using the Artificial Neural Network
Autorzy:
Marlęga, Radosław
Powiązania:
https://bibliotekanauki.pl/articles/2175158.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
artificial neural network
day-ahead market
modeling
simulation
comparative research
model sensitivity testing
Opis:
The paper shows that it is possible to correct the identification model of the Day-Ahead Market system by employing the Perceptron Artificial Neural Network. First, a simulation model of the DAM system at the POLPX has been built, and then it has been shown how the model can be corrected so that the weighted average electricity prices obtained are close enough to the exchange-quoted ones. Next, simulation, comparative and sensitivity studies of the model were carried out for forecast data for four characteristic hours: 6, 12, 18, and 24 of the following year. Many interesting research results were obtained, including a result of sensitivity testing it was shown that the obtained models can be used in forecasting studies.
Źródło:
Studia Informatica : systems and information technology; 2022, 1(26); 85--105
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial Neural Network based on mathematical models used in quantum computing
Autorzy:
Ruciński, Dariusz
Powiązania:
https://bibliotekanauki.pl/articles/2201614.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
neural modeling
Day-Ahead Market
Polish Power Exchange
Hilbert space
quantum inspired neural network
Opis:
The article is a proposition of a new approach to building a neural model based on the system of Day-Ahead Market operating at TGE S.A. The reason for the proposed method is an attempt to find a better model for the DAM system. The proposed methodology is based on using mathematical models used in quantum computing. All calculations performed on learning the Artificial Neuron Network are based on operations described in Hilbert space. The main idea of calculations is to replace the data from the decimal system into the quantum state in Hilbert space and perform learning operations for a neural model of the DAM system in a special manner which relay on the teaching model for each position of the quantum register for all data. The obtained results were compared to the “classical” neural model with the use of a comparative model.
Źródło:
Studia Informatica : systems and information technology; 2022, 2(27); 27--48
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evolutionary algorithm inspired by the methods of quantum computer sciences for the improvement of a neural model of the electric power exchange
Autorzy:
Tchórzewski, J.
Ruciński, D.
Powiązania:
https://bibliotekanauki.pl/articles/94729.pdf
Data publikacji:
2017
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Tematy:
Artificial Neural Network
Matlab language
modelling
quantum computation
Polish Power Exchange
day ahead market
Opis:
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.
Źródło:
Information Systems in Management; 2017, 6, 4; 343-355
2084-5537
2544-1728
Pojawia się w:
Information Systems in Management
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Capabilities of MATLAB and Simulink related to modelling of Polish power exchange
Autorzy:
Tchórzewski, J.
Powiązania:
https://bibliotekanauki.pl/articles/94981.pdf
Data publikacji:
2016
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Tematy:
artificial neural network
identification
MATLAB
Simulink
environment
Polish Power Exchange
simulation
Day Ahead Market
Opis:
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.
Źródło:
Information Systems in Management; 2016, 5, 3; 424-435
2084-5537
2544-1728
Pojawia się w:
Information Systems in Management
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hourly identification and simulation of the TGE S.A. Day-Ahead Market system
Autorzy:
Marlęga, Radosław
Tchórzewski, Jerzy R.
Powiązania:
https://bibliotekanauki.pl/articles/31342745.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
equations of state
control system
Day-Ahead Market
identification
Polish Electricity Exchange
simulation
state space
Opis:
The paper presents selected research results concerning the identification and simulation of the TGE S.A. Day-Ahead Market (DAM) system of the day for electricity delivered and sold, listed for the following hours: 5:01-6:00, 11:01-12:00, 17:01-18:00 and 23:01-24:00 in 2019, which were obtained in the MATLAB and Simulink environment using the System Identification Toolbox. As a result of identification, four respective discrete parametric arx models were obtained, which were then subject to quality assessment. Then, a simulation model was built in the Simulink environment, which was used for simulation tests and for assessing the sensitivity of the model created using the data from 2019 as the basis and the data from 2020 for verification. The obtained results confirm the correctness of both the performed discrete parametric identification and the possibility of testing the quality of the model and its sensitivity with the use of the DAM system model in the MATLAB and Simulink environment.
Źródło:
Control and Cybernetics; 2022, 51, 4; 523-555
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-10 z 22

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