PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Price Prediction of the Electric Energy - Regression versus Neural Approach

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper, two models for price prediction of the day ahead market are presented and evaluated. The work consists of two parts. The first part includes short description the day ahead market of electric energy exchange. In the second one, the regression and neural models applied. As an example, the polish power exchange market is used.
Rocznik
Strony
7--17
Opis fizyczny
Bibliogr. 19 poz.
Twórcy
  • 1Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447 Warsaw, Poland
Bibliografia
  • [1]Beltratti A., et al. (1996): Neural Networks for Economic and Financial Modelling. Int. Thomson Computer Press, London.
  • [2]Brockwell P. J., Davis R. A. (1996): Introduction to Time Series and Forecasting, Springer-Verlag, New York.
  • [3]Brockwell P. J., Davis R. A. (1996): Time Series: Theory and Methods, Springer- Verlag, New York.
  • [4]Charytoniuk W., Chen M. (2000): Very Short-Term Load Forecasting Using Artificial Neural Networks, IEEE Transaction on Power Systems, vol.15, no.1, pp. 263-268, February.
  • [5]Ding A. A. (1999):, Neural Network Prediction with Noisy Predictors, IEEE Transaction on Neural Networks, vol.10, no.5, pp. 1196-1203, September.
  • [6]Draper N. R., Smith H.(1998): Applied Regression Analysis, John Wiley and Sons, New York.
  • [7]Drezga I., Rahman S. (1999): Short-Term Load Forecasting with Local ANN Predictors, IEEE Transaction on Power Systems, vol.14, no.3, pp. 845-849, August.
  • [8]Genevieve B. Orr, Muller K. R. (1998): Neural Networks: Tricks of the Trade, Springer-Verlag.
  • [9]Haykin S. (1994): Neural Networks. A comprehensive Foundation. Macmilan Publishing Company, New York.
  • [10]Hippert H.S., Pedreira C.E., Souza R.C. (2001): Neural Network for Short-Term Load Forecasting: A Review and Evaluation". IEEE Transaction on Power Systems, vol. 16, no.1, February.
  • [11]Malko J. (1995): Wybrane zagadnienia prognozowania w elektroenergetyce. Prognozowanie zapotrzebowania energii i mocy elektrycznej. (Selected prognostic problems in power industry) (in Polish), Oficyna Wydawnicza Politechniki Wrocławskiej, Wrocław.
  • [12]Masters T. (1995): Neural, Novel and Hybrid Algorithms for Time Series Prediction. John Wiley & Sons, New York.
  • [13]Montgomery D.C. (1998): Introduction to Linear Regression Analysis. John Wiley and Sons, New York.
  • [14]Mori H., Yuihara A. (2001): Deterministic annealing Clustering for ANN-Based short-Term Load Forecasting, IEEE Transaction on Power Systems, vol.16, no.3, pp. 545-551, August.
  • [15]Piotrowski P., (2002): Neural Networks With Genetic Algorithms for the Monthly Electric Energy Consumption and Peak Power Middle-Term Forecasting. Journal of Applied Computer Science, Techn. Univ. Lodz, vol. 10, no.1, pp.105-115.
  • [16]Senju T., Takara H., Uezato K., Funabashi T. (2002): One-Hour-Ahead Load Forecasting Using Neural Network. IEEE Transaction on Power Systems, vol.1, no.1, pp. 113-118, February.
  • [17]Szkuta B. R., Snanbria L. A., Dillon T.S. (1999): Electricity Price Short-Term Forecasting Using Artificial Neural Networks. IEEE Transaction on Power Systems, vol. 14, no.3, pp. 851-857, August.
  • [18]Zieliński J. S. (2002): AI in Power Systems. In: Artificial Intelligence in Control and Management (in Polish), Lodz, Poland.
  • [19]Zirilli J.S. (1997): Financial Prediction using Neural Networks. Int. Thomson Computer Press, London.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-LOD5-0011-0001
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.