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Wyszukujesz frazę "day-ahead electricity market" wg kryterium: Temat

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    Wyświetlanie 1-5 z 5
    Tytuł:
    Portfolio management of a small RES utility with a structural vector autoregressive model of electricity markets in Germany
    Autorzy:
    Maciejowska, Katarzyna
    Powiązania:
    https://bibliotekanauki.pl/articles/2204084.pdf
    Data publikacji:
    2022
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    intraday electricity market
    day-ahead electricity market
    structural vector autoregressive model
    probabilistic forecasting
    trading strategy
    Opis:
    Electricity producers and traders are exposed to various risks, among which price and volume risk play very important roles. This research considers portfolio-building strategies that enable the proportion of electricity traded in different electricity markets (day-ahead and intraday) to be chosen dynamically. Two types of approaches are considered: a simple strategy, which assumes that these proportions are fixed, and a data-driven strategy, in which the ratios fluctuate. To explore the market information, a structural vector autoregressive model is applied, which allows one to estimate the relationship between the variables of interest and simulate their future distribution. The approach is evaluated using data from the electricity market in Germany. The outcomes indicate that data-driven strategies increase revenue and reduce trading risk. These financial gains may encourage energy traders to apply advanced statistical methods in their portfolio-building process.
    Źródło:
    Operations Research and Decisions; 2022, 32, 4; 75--90
    2081-8858
    2391-6060
    Pojawia się w:
    Operations Research and Decisions
    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:
    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:
    Quantum-inspired method of neural modeling of the day-ahead market of the Polish electricity exchange
    Autorzy:
    Tchórzewski, Jerzy
    Ruciński, Dariusz
    Powiązania:
    https://bibliotekanauki.pl/articles/2183468.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    artificial neural networks
    day-ahead market
    dequantization with ANN
    neural modeling
    quantum inspired method
    quantum computing
    Polish Electricity Exchange
    system quantization
    Opis:
    The paper presents selected elements of a modelling methodology involving quantization, quantum calculations and dequantization on the example of the neural model of the Day-Ahead Market of the Polish Electricity Exchange. Based on the fundamental assumptions of quantum computing, a new method has been proposed here of converting the real numbers in decimal notation into quantum mixed numbers using the probability modules of quantum mixed number and the principle of superposition, along with a new method of quantum calculations using linear algebra and vectormatrix calculus, and the Artificial Neural Network was taught accordingly. Dequantization of quantum mixed numbers to real numbers in decimal notation using the new method of dequantization has been proposed as well. The operation of the methods introduced was shown on numerical examples.
    Źródło:
    Control and Cybernetics; 2021, 50, 3; 383--399
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
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