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Probabilistic very short-term wind farm power forecasts based on varying-coefficient models: A case study of onshore wind farm Danilo


Lončarek, Tomislav; Đalto Mladen; Vašak Mario; Matuško, Jadranko
Probabilistic very short-term wind farm power forecasts based on varying-coefficient models: A case study of onshore wind farm Danilo // 2nd Frontiers in Computational Physics Conference: Energy Sciences
Zürich, Švicarska, 2015. (predavanje, nije recenziran, neobjavljeni rad, znanstveni)


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Naslov
Probabilistic very short-term wind farm power forecasts based on varying-coefficient models: A case study of onshore wind farm Danilo

Autori
Lončarek, Tomislav ; Đalto Mladen ; Vašak Mario ; Matuško, Jadranko

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, neobjavljeni rad, znanstveni

Skup
2nd Frontiers in Computational Physics Conference: Energy Sciences

Mjesto i datum
Zürich, Švicarska, 03.06.2015. - 05.06.2015

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Nije recenziran

Ključne riječi
wind farm power forecasts; varying-coefficient models

Sažetak
Very short-term wind farm power forecasts are essential for the Transmission System Operator in order to optimally operate reserves for the continuous balance of the power system, since wind power fluctuations at time scales of some minutes are those wich most seriously affect the balance in the power system. This aspect motivates our choice of 3-hours ahead forecasts and a time series resolution of 10 minutes. For such prediction horizons, it is generally accepted that statistical time series based models are more accurate than physical models. We focus on a non-linear approach based on varying-coefficient models by generalising linear Auto-Regressive with eXogenous input models. The main idea is to replace constant parameters of models with functions that take into account local observations such as wind speed and wind turbines power production and numerical weather predictions of wind speed and direction. To improve accuracy of very short-term wind power forecasts the relationship between the power production for each turbine of the farm are taken into account in order to minimize the impact of topographical particularities of the area, wind turbines interposition within the wind farm, atmospheric processes occurring at different scales, the wake shadowing effect generated by nearby wind turbines, etc. Furthermore, extension from point to probabilistic forecast is given since they are very useful in the sense that they provide us with a measure of the uncertainty associated with a point forecast. Comparison of two different families of varying-coefficient models (regime-switching and conditional parametric models) is carried out. The case of the on-shore wind farm of Danilo in Croatia has been considered.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Temeljne tehničke znanosti, Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Jadranko Matuško (autor)

Avatar Url Mario Vašak (autor)

Poveznice na cjeloviti tekst rada:

Pristup cjelovitom tekstu rada

Citiraj ovu publikaciju:

Lončarek, Tomislav; Đalto Mladen; Vašak Mario; Matuško, Jadranko
Probabilistic very short-term wind farm power forecasts based on varying-coefficient models: A case study of onshore wind farm Danilo // 2nd Frontiers in Computational Physics Conference: Energy Sciences
Zürich, Švicarska, 2015. (predavanje, nije recenziran, neobjavljeni rad, znanstveni)
Lončarek, T., Đalto Mladen, Vašak Mario & Matuško, J. (2015) Probabilistic very short-term wind farm power forecasts based on varying-coefficient models: A case study of onshore wind farm Danilo. U: 2nd Frontiers in Computational Physics Conference: Energy Sciences.
@article{article, author = {Lon\v{c}arek, Tomislav and Matu\v{s}ko, Jadranko}, year = {2015}, keywords = {wind farm power forecasts, varying-coefficient models}, title = {Probabilistic very short-term wind farm power forecasts based on varying-coefficient models: A case study of onshore wind farm Danilo}, keyword = {wind farm power forecasts, varying-coefficient models}, publisherplace = {Z\"{u}rich, \v{S}vicarska} }
@article{article, author = {Lon\v{c}arek, Tomislav and Matu\v{s}ko, Jadranko}, year = {2015}, keywords = {wind farm power forecasts, varying-coefficient models}, title = {Probabilistic very short-term wind farm power forecasts based on varying-coefficient models: A case study of onshore wind farm Danilo}, keyword = {wind farm power forecasts, varying-coefficient models}, publisherplace = {Z\"{u}rich, \v{S}vicarska} }




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