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Proceedings Paper

Online single-factor measured active nodal load forecasting in an electric power system
Author(s): Pavlo O. Chernenko; Sviatoslav Yu. Shevchenko; Andrzej Smolarz; Gaini Karnakova; Miergul Kozhambardiyeva; Aigul Iskakova
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Paper Abstract

Two techniques for online nodal load (NL) forecasting using preliminary classification of training set data are proposed. In the first one, a pattern recognition method, the rate evaluation algorithm (REM), is applied to measured load values of the previous day to classify load diagram that is being forecasted. Diagrams from resulting class are used to calculate load predictions. In the second technique, measured load values of a diagram from training set, which is the closest to the one being predicted, are used as estimates of predicted load values. Online NL forecasting using the mentioned above methods has been conducted. The corresponding mean square errors are given.

Paper Details

Date Published: 7 August 2017
PDF: 7 pages
Proc. SPIE 10445, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2017, 1044560 (7 August 2017); doi: 10.1117/12.2280887
Show Author Affiliations
Pavlo O. Chernenko, Institute of Electrodynamics (Ukraine)
Sviatoslav Yu. Shevchenko, National Univ. of Food Technologies (Ukraine)
Andrzej Smolarz, Lublin Univ. of Technology (Poland)
Gaini Karnakova, M.Kh. Dulaty Taraz State Univ. (Kazakhstan)
Miergul Kozhambardiyeva, Almaty Univ. of Power Engineering and Telecommunications (Kazakhstan)
Aigul Iskakova, Kazakh National Research Technical Univ. after K. I. Satpaev (Kazakhstan)


Published in SPIE Proceedings Vol. 10445:
Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2017
Ryszard S. Romaniuk; Maciej Linczuk, Editor(s)

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