Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/101686
Title: Very-short term solar power generation forecasting based on trend-additive and seasonal-multiplicative smoothing methodology
Authors: Eroshenko, S.
Khalyasmaa, A.
Valiev, R.
Issue Date: 2018
Publisher: EDP Sciences
Citation: Eroshenko S. Very-short term solar power generation forecasting based on trend-additive and seasonal-multiplicative smoothing methodology / S. Eroshenko, A. Khalyasmaa, R. Valiev. — DOI 10.1051/e3scconf/20185102003 // E3S Web of Conferences. — 2018. — Vol. 51. — P. -.
Abstract: In conditions of development of generating facilities on renewable energy sources, the technology runs up to uncertainty in the operational and short-term planning of the power system operating modes. To date, reliable tools for forecasting the generation of solar power stations are required. This paper considers the methodology of operational forecasting of solar power stations output based on the mathematical apparatus of cubic exponential smoothing with trend and seasonal components. The presented methodology was tested based on the measuring data of a real solar power station. The average forecast error was not more than 10% for days with variable clouds and not more than 3% for clear days, which indicates the effectiveness of the proposed approach. © The Authors, published by EDP Sciences.
Keywords: POWER PLANTS
SOLAR ENERGY
SOLAR POWER GENERATION
EXPONENTIAL SMOOTHING
FORECAST ERRORS
MATHEMATICAL APPARATUS
OPERATING MODES
OPERATIONAL FORECASTING
RENEWABLE ENERGY SOURCE
SHORT TERM PLANNING
SOLAR POWER STATION
FORECASTING
URI: http://hdl.handle.net/10995/101686
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85073871625
PURE ID: 8555025
ISSN: 25550403
DOI: 10.1051/e3scconf/20185102003
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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