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nr nr 4
343-355
EN
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. (original abstract)
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nr nr 4
294-308
EN
This work contains selected results of research on modelling identification of Polish Power Exchange (TGEE) on the example of the figures quoted on the Day Ahead Market (DAM) on TGEE in Poland. In order to obtain a model of the TGEE system on the beginning it was conducted to identify the figures for the period 01.01.2013-31.12.2015 obtaining discrete parametric model arx in MATLAB and Simulink environments using System Identification Toolbox (SIT). The resultant model was converted to a continuous parametric model, and that one on a continuous model in the state space. On the basis of obtained equations of state and outputs, there was interpreted a state variables and parameters of the selected model, i.e. selected elements of the matrix A and matrix B. Research continues. (original abstract)
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