Pregled bibliografske jedinice broj: 698043
Comparison of static and adaptive models for short-term residential natural gas forecasting in Croatia
Comparison of static and adaptive models for short-term residential natural gas forecasting in Croatia // Applied energy, 129 (2014), 94-103 doi:10.1016/j.apenergy.2014.04.102 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 698043 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Comparison of static and adaptive models for short-term residential natural gas forecasting in Croatia
Autori
Potočnik, Primož ; Soldo, Božidar ; Šimunović, Goran ; Šarić, Tomislav ; Jeromen, Andrej ; Govekar, Edvard
Izvornik
Applied energy (0306-2619) 129
(2014);
94-103
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
short-term natural gas demand ; adaptive forecasting models ; linear forecasting models ; nonlinear forecasting models
Sažetak
In this paper the performance of static and adaptive models for short-term natural gas load forecasting has been investigated. The study is based on two sets of data, i.e. natural gas consumption data for an individual model house, and natural gas consumption data for a local distribution company. Various forecasting models including linear models, neural network models, and support vector regression models, were constructed for the one day ahead forecasting of natural gas demand. The models were examined in their static versions, and in adaptive versions. A cross-validation approach was applied in order to estimate the generalization performance of the examined forecasting models. Compared to the static model performance, the results confirmed the significantly improved forecasting performance of adaptive models in the case of the local distribution company, whereas, as was expected, the forecasts made in the case of the individual house were not improved by the adaptive models, due to the stationary regime of the latter’s heating. The results also revealed that nonlinear models do not outperform linear models in terms of generalization performance. In summary, if the relevant inputs are properly selected, adaptive linear models are recommended for applications in daily natural gas consumption forecasting.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Projekti:
152-1521781-2235 - Razvoj ERP sustava za digitalno poduzeće (Šarić, Tomislav, MZOS ) ( CroRIS)
Ustanove:
Strojarski fakultet, Slavonski Brod
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus