Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "day ahead market" wg kryterium: Temat

  Lista filtrów
Wyrównaj
Wyświetlanie 1-15 z 22
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:
Analysis of data quoted on the Day-Ahead Market of TGE S.A. using Statistics and Machine Learning Toolbox
Autorzy:
Tchórzewski, Jerzy
Longota, Bartłomiej
Powiązania:
https://bibliotekanauki.pl/articles/2201615.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
artificial neural network
cluster analysis
Day-Ahead Market
k-means method
Matlab and Simulink environment
Statistics and Machine Learning Toolbox
Ward’s method
Opis:
The publication contains the results of research in the field of cluster analysis carried out using data quoted on the Day-Ahead Market of TGE S.A. Two methods were used in the analysis, one hierarchical known as the Ward’s method, and the other non-hierarchical - the k-means method. Many interesting research results have been obtained, which are illustrated, among others, in in the form of dendrograms, silhouette graphs and graphs in the form of clusters. Data on the volume and the volumeweighted average price of electricity were examined for various types of quotations: fixing 1, fixing 2 and continuous quotations. The research was carried out in the MATLAB and Simulink environments using a library called Machine and Statistics Learning Toolbox. Selected test results were interpreted.
Źródło:
Studia Informatica : systems and information technology; 2022, 2(27); 49--74
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Applications of VaR and CVaR Methods on Energy Market in Poland
Zastosowanie metod VaR oraz CVaR na rynku energii w Polsce
Autorzy:
Ganczarek, Alicja
Powiązania:
https://bibliotekanauki.pl/articles/905673.pdf
Data publikacji:
2006
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
Day Ahead Market
Balance Market
futures market
risk measures
Value-at-Risk
Conditional-Value-at-Risk
variance-covariance
Monte Carlo simulation
historical simulation
GED distribution
Opis:
This article presents downside risk measures such as: Value-at-Risk - VaR and Conditional Value-at-Risk - CVaR. We establish them with three of the known methods. The electric energy is an article of real tame, which we can not store up and this influences on changes of price. The downside risk measures are more effective than the measures of volatility for estimate risk on electric energy market. The aim this article is the choice of VaR and CVaR methods, that are the most effective for future risk on the Polish energy market. In this investigation we use the logarithmic rate of return of prices from the Polish Power Exchange, Balance Market (BM) from October to December 2002 and their simulation distributions.
Podejmując decyzje związane z przyszłością, podejmujemy ryzyko. Ocena ryzyka jest oceną subiektywną i w głównej mierze zależy od preferencji inwestorów. Niemniej jednak, aby ocenić ewentualne przyszłe ryzyko, należy go zmierzyć. Jest wiele różnych miar służących do jego pomiaru. W artykule skupiliśmy się nad kwantylowymi miarami zagrożenia Value-at-Risk - VaR oraz Conditional Value-at-Risk - CVaR. Będziemy te miary wyznaczać trzema znanymi metodami. Energia elektryczna jest towarem czasu rzeczywistego, którego się nie magazynuje, co w znacznym stopniu wpływa na kształtowanie się jej cen. Miary najgorszych realizacji spośród możliwych są efektywniejsze w przypadku oszacowania ryzyka na rynku energii niż miary przeciętne. Celem referatu jest wybór takiej spośród metod wyznaczania VaR oraz CVaR, aby najprecyzyjniej oszacować ewentualne przyszłe ryzyko straty na polskim rynku energii. Wyniki badań oparte są na logarytmicznych stopach zwrotu cen zanotowanych na Towarowej Giełdzie Energii oraz Rynku Bilansującym (RB) w okresie od 1 października do końca 2002 r., oraz na symulowanych rozkładach tych stóp zwrotu.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2006, 196
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
APT Model for Electricity Prices on the Day Ahead Market of the Polish Power Exchange
Model APT dla ceny energii elektrycznej na RDN Giełdy Energii SA
Autorzy:
Ganczarek, Alicja
Powiązania:
https://bibliotekanauki.pl/articles/904695.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
The Day Ahead Market
Arbitrage Pricing Theory
factors analysis
the principal components
eigenvalue
eigenvector
the graph analysis method
the optimum choice method proposed by Z. Hellwig
Opis:
W pracy przedstawiliśmy model zależności zmiany ceny energii elektrycznej od czynników makroekonomicznych, takich jak zmiany: kursu dolara, kursu marki, inflacji, bezrobocia, cen produkcji w górnictwie, kopalnictwie oraz przetwórstwie przemysłowym, wydobyciu węgla kamiennego oraz czynników pogodowych. Przedmiotem badań jest empiryczna weryfikacja modelu ceny na RDN Giełdy Energii SA w 2001 r. z wykorzystaniem metody głównych składowych. Otrzymane wyniki skonfrontowaliśmy z wynikami uzyskanymi dla modelu APT, w którym do doboru składowych modelu zastosowaliśmy metodę analizy grafów i metodę optymalnego wyboru predyktant zaproponowanych przez Z. Hellwiga. Celem tej pracy jest wyłonienie modelu efektywniej opisującego kształtowanie się cen na RDN.
In this paper we presented the model of the dependence of the electricity price on macroeconomic factors such as changes in the dollar price, the Deutsche mark price, the rate of inflation, the rate of unemployment, price changes in the mining industry, the production of the manufacturing sector, the output of the mining industry and weather conditions. The aim of this article was the empirical verification of the price model on the Day Ahead Market (DAM) of the Polish Power Exchange in 2001 based on the principal components method. The results were compared with the results for the APT model, selected by means of the graph analysis method and the optimum choice method proposed by Z. Hellwig. The aim of this work was to choose the best model for the description of price trends on the DAM.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2005, 194
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
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:
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:
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:
Cluster analysis as a preliminary problem in neural modelling of the Polish Power Exchange
Autorzy:
Tchórzewski, Jerzy
Jezierski, Jakub
Powiązania:
https://bibliotekanauki.pl/articles/94965.pdf
Data publikacji:
2019
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Tematy:
artificial self-organizing neural networks
business intelligence
cluster analysis
neural modelling
Day Ahead Market
Polish Power Exchange
Opis:
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.
Źródło:
Information Systems in Management; 2019, 8, 1; 69-81
2084-5537
2544-1728
Pojawia się w:
Information Systems in Management
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparative Study of the Identification Methods of the Management System of the Day-Ahead Market of Polish Energy Market S.A.
Autorzy:
Marlęga, Radosław
Powiązania:
https://bibliotekanauki.pl/articles/2052421.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
artificial neural network
business intelligence
day ahead market
Identification methods
information system in management
parametrical model
Polish Energy Market
Opis:
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.
Źródło:
Studia Informatica : systems and information technology; 2021, 1-2(25); 67-86
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:
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:
GARCH Models of Time Series on DAM
Modele GARCH szeregów czasowych na RDN
Autorzy:
Ganczarek, Alicja
Powiązania:
https://bibliotekanauki.pl/articles/906890.pdf
Data publikacji:
2007
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
Polish Power Exchange
Day Ahead Market
Balance Market
Autoregressive Conditional Heteroscedasticity
Generalized Autoregressive Conditional Heteroscedasticity
Maximum Likelihood Method
Akaike's information criterion
Schwarz’s consistent criterion
Hannan-Quinn’s consistent criterion
Rissanen’s stochastic complexity criteria
Opis:
In this paper an analysis of the time series on the Day Ahead Market (DAM) of the Polish Power Exchange is presented. In this analysis Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models are used to describe the time series of rates of return of price of electric energy on DAM. This analysis is based on the data from July 2002 to June 2004.
W pracy została przedstawiona analiza szeregów czasowych stóp zwrotu cen energii elektrycznej notowanych na rynku dnia następnego (RDN) Towarowej Giełdy Energii SA od lipca 2002 do czerwca 2004 r. za pomocą modeli GARCH. Celem pracy jest odpowiedź na pytanie, czy modele GARCH efektywnie opisują kształtowanie się cen energii elektrycznej na parkiecie polskiej giełdy energii i czy można je wykorzystywać do modelowania szeregów czasowych stóp zwrotu cen energii elektrycznej.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2007, 206
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
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
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:
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
Wyświetlanie 1-15 z 22

Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies