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http://elar.urfu.ru/handle/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://elar.urfu.ru/handle/10995/101686 |
Access: | info:eu-repo/semantics/openAccess |
SCOPUS ID: | 85073871625 |
WOS ID: | 000454427500012 |
PURE ID: | 8555025 |
ISSN: | 25550403 |
DOI: | 10.1051/e3scconf/20185102003 |
Appears in Collections: | Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC |
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2-s2.0-85073871625.pdf | 1,45 MB | Adobe PDF | View/Open |
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