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:
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
Tytuł:
Prediction capabilities of the LSTM and Perceptron models based on the Day-Ahead Market on the Polish Power Exchange S.A.
Autorzy:
Ruciński, Dariusz
Powiązania:
https://bibliotekanauki.pl/articles/27323577.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
shallow networks
deep networks
Day-Ahead Market
MATLAB
Simulink environment
neural modeling
prediction time
electricity prices
Opis:
The main purpose of the research was to examine the properties of models for two kinds of neural networks, a deep learning models in which the Long Short-Term Memory was chosen and shallow neural model in which the Perceptron Neural Network was chosen. The subject of the examination was the Day-Ahead Market system of PPE S.A. The article presents the learning results of both networks and the results of the predictive abilities of the models. The research was conducted based on data published on the Polish Stock Exchange for the 2018 year. The MATLAB environment was chosen as a tool for providing the examinations. The determination index (R2) and the mean square error (MSE) was adopted as the network evaluation criterion for the learning ability and for the prediction ability of both networks.
Źródło:
Studia Informatica : systems and information technology; 2023, 1(28); 69--82
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
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:
Quantum inspiration to build a neural model based on the Day-Ahead Market of the Polish Power Exchange
Autorzy:
Ruciński, Dariusz
Powiązania:
https://bibliotekanauki.pl/articles/2052430.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
Neural Modeling
day-ahead market
Polish power exchange
mean square error
determination index
quantum inspired neural model
Opis:
The article is an attempt of the methodological approach to the proposed quantum-inspired method of neural modeling of prices quoted on the Day-Ahead Market operating at TGE S.A. In the proposed quantum-inspired neural model it was assumed, inter alia, that it is composed of 12 parallel Perceptron ANNs with one hidden layer. Moreover, it was assumed that weights and biases as processing elements are described by density matrices, and the values flowing through the Artificial Neural Network of Signals are represented by qubits. Calculations checking the correctness of the adopted method and model were carried out with the use of linear algebra and vector-matrix calculus in MATLAB and Simulink environments. The obtained research results were compared to the results obtained from the neural model with the use of a comparative model.
Źródło:
Studia Informatica : systems and information technology; 2021, 1-2(25); 23-37
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
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:
Selected aspects of functioning of the day-ahead and intraday markets in the electricity market
Wybrane apsekty funkcjonowania rynku dnia następnego i rynku dnia bieżącego na rynku energii elektrycznej
Autorzy:
Malska, Wiesława
Powiązania:
https://bibliotekanauki.pl/articles/37516660.pdf
Data publikacji:
2022
Wydawca:
Politechnika Rzeszowska im. Ignacego Łukasiewicza. Oficyna Wydawnicza
Tematy:
day-ahead market
intraday market
polish power exchange
volume
price
rynek dnia następnego
rynek dnia bieżącego
towarowa giełda energii
wolumen
kurs
Opis:
The paper presents a statistical analysis of prices and volumes of electricity quoted on the Day-Ahead Market (DAM) and the Intra-Day Market (IDM) of the Polish Power Exchange (POLPX). The analysis was carried out for weighted average hourly prices and volumes of electricity for two selected periods. Data available from the Polish Power Exchange was used. In the face of the energy crisis and the uncertainty caused by war and the limited supply of raw materials used to produce electricity, knowledge of the operation of the DAM and IDM is of significant economic, strategic importance, which is related to the security of electricity supply and its prices. The exchange market in Poland is supervised by the Energy Regulatory Office and the Financial Supervision Commission. During the energy crisis, the role of energy exchanges is increasing, not only in Poland, and knowledge of the functioning of the energy market is also one of the elements of strategic management in the energy sector. The Statistica v.13.3 software was used to analyse the data.
W artykule zaprezentowano analizę statystyczną cen i wolumenu energii elektrycznej notowanych na Rynku Dnia Następnego (RDN) i Rynku Dnia Bieżącego (RDB) Towarowej Giełdy Energii (TGE). Analizę przeprowadzono dla średnioważonych cen godzinowych i wolumenu energii elektrycznej dla dwóch wybranych okresów. Wykorzystano dane dostępne na Towarowej Giełdzie Energii. W obliczu kryzysu energetycznego i niepewności spowodowanej wojną i ograniczoną podażą surowców wykorzystywanych do produkcji energii elektrycznej znajomość funkcjonowania RDN i RDB ma istotne znaczenie ekonomiczne, strategiczne, co wiąże się z bezpieczeństwem dostaw energii elektrycznej oraz jej cenami. Rynek giełdowy w Polsce jest nadzorowany przez Urząd Regulacji Energetyki i Komisję Nadzoru Finansowego. W czasie kryzysu energetycznego zwiększa się rola giełd energii, nie tylko w Polsce, a znajomość funkcjonowania rynku energii jest także jednym z elementów zarządzania strategicznego w energetyce. Do analizy danych wykorzystano program Statistica v.13.3.
Źródło:
Zeszyty Naukowe Politechniki Rzeszowskiej. Elektrotechnika; 2022, 39; 93-112
0209-2662
2300-6358
Pojawia się w:
Zeszyty Naukowe Politechniki Rzeszowskiej. Elektrotechnika
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