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NEURAL MODELING OF THE ELECTRIC POWER STOCK MARKET IN USAGE OF MATLAB AND SIMULINK TOOLS FOR THE DAY AHEAD MARKET DATA

100%
Ruciński D., Tchórzewski J.
Information Systems in Management
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2016
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vol. 5
|
issue 2
215-226
EN
The work contains selected results of the modelling of neural Electric Power Ex-change (EPE) in Poland. For modelling EPE system, artificial neural network (ANN) was constructed. ANN was learned and tested using of the next day market data. Generated neural model was used for simulation tests and susceptibility tests. Suitable model was implemented in Simulink. As a result of simulation tests and susceptibility testing a lot of interesting research results were obtained.
2
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IDENTIFICATION MODELING OF POLISH ELECTRIC POWER EXCHANGE

88%
Marlęga R., Tchórzewski J.
Information Systems in Management
|
2016
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vol. 5
|
issue 2
195-204
EN
This paper contains selected results of identification modeling of Polish Electric Power Exchange (EPE). In order to obtain EPE system model it was performed identification based on figures of EPE’s Day-Ahead Market. During performing identification process, parametric arx model in System Identification Toolbox environment was utilized. Generated EPE parametric model has been further used for performing simulation tests and realization of susceptibility testing. Suitable models were implemented in Simulink software. As a result of simulation and susceptibility testing, many interesting findings has been delivered.
3
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CAPABILITIES OF MATLAB AND SIMULINK RELATED TO MODELLING OF POLISH POWER EXCHANGE

75%
Tchórzewski J.
Information Systems in Management
|
2016
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vol. 5
|
issue 3
424-435
EN
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.
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