PL EN


2016 | 5 | 2 | 215-226
Article title

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

Content
Title variants
Languages of publication
EN
Abstracts
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.
Year
Volume
5
Issue
2
Pages
215-226
Physical description
Dates
published
2016
Contributors
  • Department of Computer Science, Siedlce University of Natural Sciences and Humanities
  • Department of Computer Science, Siedlce University of Natural Sciences and Humanities
References
  • Fijorek K., Mróz K., Niedziela K., Fijorek D. (2010), Prognozowanie cen energii elektrycznej na Rynku Dnia Następnego metodami data minig. Rynek Energii nr 12.
  • Mynarski S. (1993), Analiza rynku. Systemy i mechanizmy. Wyd. AE. Kraków.
  • Malko J. (2003), Black-out, czyli zdarzenia katastrofalne w krytycznych systemach infrastrukturalnych, Wokół Energetyki vol.6 tom 5.
  • Li J., Li J. (2008) Next-Day Electricity Price Forecasting Based on Support Vector Machines and Data Mining Technology. Proceedings of the 27th Chinese Control Conference, Kunming, Yunnan, China.
  • Mielczarski W. (2000), Rynki energii elektrycznej. Wybrane aspekty techniczne i ekonomiczne, ARE, Warszawa.
  • Osowski S. (2000), Sieci neuronowe do przetwarzania informacji, PW, Warszawa.
  • Rutkowska D., Piliński M., Rutkowski L. (1997), Sieci neuronowe, algorytmy genetyczne i systemy rozmyte, PWN, Warszawa.
  • Senjyu T., Takara H., Uezato K., and Funabashi T. (2002) One-Hour-Ahead Load Forecasting Using Neural Network, IEEE Trans. on Power Systems, vol. 17, no. 1, pp. 113-118.
  • Stankovic A. M., Saric A. T., and Milosevic M., (2003) Identification of Nonparametric Dynamic Power System Equivalents with Artificial Neural Networks, IEEE Transactions on Power Systems, vol. 18, no. 4, pp. 1478-1486.
  • Tadeusiewicz R. (1993), Sieci neuronowe. AOW RM, Warszawa.
  • Tchórzewski J. (2013) Rozwój systemu elektroenergetycznego w ujęciu teorii sterowania i systemów. OW PWr. Wrocław.
  • Tchórzewski J. (2009), Identification of the Electrical Energy Stock Exchange and creating knowledge maps using MATLAB environment with SIT and NNT Toolboxes, Energy Market, 2009. EEM 2009. 6th International Conference on the European. IEEE Xplore Digital Library.
  • Tchórzewski J. Ruciński D. (2016), Neural Modeling Safe Development of the Electricity Stock Exchange Using Quotations of Day-Ahead Market, Wolters Kluwer, Warszawa.
  • Wierzchoń S., Kłopotek M. (2015), Cluster analysis. IPI PAN. Warszawa.
  • Żurada J., Barski M., Jędruch W. (1996), Sztuczne sieci neuronowe. Podstawy teorii i zastosowania, PWN, Warszawa.
  • http://www.mathworks.com/help/nnet
Document Type
Publication order reference
Identifiers
ISSN
2084-5537
YADDA identifier
bwmeta1.element.desklight-4c489270-c3cb-42fe-8515-32f78b4d7c49
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.