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    Wyświetlanie 1-5 z 5
    Tytuł:
    Simulation of the impact of the degree and type of shading on generation of electrical energy by the PV system in MATLAB&SIMULINK environment
    Autorzy:
    Jarmuda, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/97511.pdf
    Data publikacji:
    2015
    Wydawca:
    Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
    Tematy:
    PV system
    poor shading effect
    strong shading effect
    bypass diodes
    MATLAB environment
    Opis:
    In the study the method of modelling of the photovoltaic system (PV) in MATLAB & SIMULINK environment was presented along with test results of the impact of shading on the value of energy output from the photovoltaic system. The PV system model constructed of five parallel connected photovoltaic panels of TPSM6U type was proposed. Simulation tests were conducted considering the effect of poor and strong shading of panels causing differences in the density of the radiation power (irradiance) for individual panels and the PV system. The values of electrical energy generated by individual PV panels and the whole photovoltaic system were determined for the purposes of the actual forces. Optional switching on and off of the bypass diodes was considered in the photovoltaic panels. The tests were developed and final conclusions were formulated.
    Źródło:
    Computer Applications in Electrical Engineering; 2015, 13; 454-468
    1508-4248
    Pojawia się w:
    Computer Applications in Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Systemic Evolutionary Algorithm inspired by the methods of quantum computing to improve the accuracy of the model on the neuronal motion the end of the robot arm PR–02
    Autorzy:
    Wołynka, Ł.
    Tchórzewski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/97323.pdf
    Data publikacji:
    2016
    Wydawca:
    Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
    Tematy:
    Evolution algorithms
    Quantum computing
    Modeling systems
    Robot PR–02
    Artificial Neural Networks
    Environment MATLAB and Simulink
    Opis:
    The article contains selected results of research on the design Systemic Evolutionary Algorithm inspired by quantum informatics methods and description how to implement it in Matlab language in order to use for improve parameters neural model on example robot robot PR–02 arm motion. Initial population was based on weights matrix of artificial neural network. Randomly selected population of individual chromosomes in both the initial and in the following parent population have been converted to binary values, and these to quantum values by using created for this purpose quatization() function. Quantum gene value was determined on the basis of stonger pure state represented by different chromosomes, to which dequantization() function was used. Selection of individuals was conducted based on the model of neural robot PR–02 motion implemented in Matlab language using calculationsNeuralNetworks() function.
    Źródło:
    Computer Applications in Electrical Engineering; 2016, 14; 297-312
    1508-4248
    Pojawia się w:
    Computer Applications in Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Design and research on artificial neural networks as electrical power system development models based on IEEE RTS data
    Autorzy:
    Tchórzewski, J.
    Pytel, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/97683.pdf
    Data publikacji:
    2015
    Wydawca:
    Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
    Tematy:
    artificial neural network
    IEEE RTS data
    electrical power system
    MATLAB and Simulink environment
    testing sensitivity
    simulation studies
    Opis:
    The paper presents selected results of research on the design of artificial neural networks and training them using the electrical power system development model (EPS or EP system) based on IEEE RTS 96 test data, i.a. creation of training and test files, development of architecture of the artificial neural network, selection of parameters of the network, selection of appropriate training and testing method, etc. As a result of the development and training an ANN, the following EP system development models were obtained, which were examined for sensitivity to changes of the number of hidden layers, number of neurons in a layer, activation function, training method, etc. Subsequently, simulation models for studying fitness of the obtained models to the real systems. Interesting results were obtained, e.g. the method of the neural modelling of the system, the optimal architecture of the ANN that is a model of the system, possibilities and directions to improve a neural model of the system, etc.
    Źródło:
    Computer Applications in Electrical Engineering; 2015, 13; 231-244
    1508-4248
    Pojawia się w:
    Computer Applications in Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The use of the MATLAB & SIMULINK environment to simulate the operation of a PV panel with an actual input function
    Autorzy:
    Jarmuda, T.
    Mikulski, S.
    Nawrowski, R.
    Tomczewski, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/97441.pdf
    Data publikacji:
    2014
    Wydawca:
    Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
    Tematy:
    photovoltaic cell
    modelling
    PV panels
    MATLAB
    environment
    Opis:
    The paper presents a method of modelling photovoltaic (PV) cells in the MATLAB & SIMULINK environment. A two-diode photovoltaic cell structure was developed, featuring series resistance. Measurements of a PV panel were carried out to determine the value of series resistance, open circuit voltage, and short-circuit current. The model suggested was used to operate the ST-STP020S-12/Cb panel with an actual input function (measurements of solar radiation power density of the south-east area of Poland in 2011). Simulation experiments were conducted of the system modelled to determine current changes, power changes, electric energy production, voltage-current characteristics, and to come up with results and draw final conclusions.
    Źródło:
    Computer Applications in Electrical Engineering; 2014, 12; 497-510
    1508-4248
    Pojawia się w:
    Computer Applications in Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Systemic Evolutionary Algorithm inspired by methods of Quantum computer sciences for the improvement of the accuracy of neural models in electrical engineering and electrical power engineering
    Autorzy:
    Tchórzewski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/97692.pdf
    Data publikacji:
    2016
    Wydawca:
    Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
    Tematy:
    Evolutionary Algorithms
    Quantum computer science
    Quantum mixed number
    Systems modelling
    Robot PR–02
    Artificial Neural Networks
    MATLAB and Simulink environment
    Electric Power Exchange
    Opis:
    The work contains selected results of research on the application of quantum computer science to a systemic evolutionary algorithm for the purpose of improving accuracy of neural models in electrical engineering and electrical power engineering. Artificial neural networks are used in neural modeling, which networks are designed and taught models of systems using available numerical data. Parameters of neural networks, and especially, elements of weight matrices, biases as well as parameters of activation functions may be improved using evolutionary algorithms. It seems that applying solutions offered by quantum computer science to systemic evolutionary algorithm, and especially, as regards creation of quantum initial population, quantum crossover and mutation operators as well as selection, considerably improves the accuracy of modelling, which was verified in MATLAB and Simulink environment using selected examples such as RP–02 robot’s arm movement, the development of the Polish Electrical Power Exchange (polish: TGEE) system, etc.
    Źródło:
    Computer Applications in Electrical Engineering; 2016, 14; 280-296
    1508-4248
    Pojawia się w:
    Computer Applications in Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

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