Szczegóły publikacji
Opis bibliograficzny
Forecasting the Nysa Kłodzka flow rate in order to predict the available flow for a run-off-river (ROR) power plant / Jakub JURASZ, Marcin Wdowikowski // E3S Web of Conferences [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2267-1242. — 2017 — vol. 14 art. no. 01019, s. 1–10. — Wymagania systemowe: Adobe Reader. — Tryb dostępu: http://www.e3s-conferences.org/articles/e3sconf/pdf/2017/02/e... [2017-04-14]. — Bibliogr. s. 9–10, Abstr. — Publikacja dostępna online od: 2017-03-15. — Toż w wersji drukowanej. — Energy and fuels 2016 : Kraków, 21–23 September 2016
Autorzy (2)
- AGHJurasz Jakub
- Wdowikowski Marcin
Dane bibliometryczne
| ID BaDAP | 105303 |
|---|---|
| Data dodania do BaDAP | 2017-05-08 |
| DOI | 10.1051/e3sconf/20171401019 |
| Rok publikacji | 2017 |
| Typ publikacji | referat w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | E3S Web of Conferences |
Abstract
Hydroelectricity is generally perceived as a stable and predictable power source. However ROR power plant without reservoir energy output is mainly driven by changing flow rate. This study applies artificial neural networks to create flow rate forecasts with one hour lead time. Forecasting models were built for Nysa Kłodzka catchment which possesses significant potential for new hydropower plants development as well as leads to frequent floods. The best of the obtained model gives satisfactory results both in terms of root mean square error (0.6379 m3/s) as well as Nash-Sutcliffe performance indicator (0.9978). Obtained results were compared with currently used forecasting models and were proven to be superior.
