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2021, vol. 49, br. 3, str. 643-652
Kratkoročno predviđanje brzine vetra bazirano na mrežama za dugotrajne-kratkoročne memorije (LSTM)
aKFUPM, Electrical Engineering Department, Dhahran, Saudi Arabia
bKFUPM, The Research Institute, Center for Engineering Research, Dhahran, Saudi Arabia

e-adresasalmantaiwo@gmail.com
Ključne reči: ANN; errors; forecasting; LSTM; wind speed; wind power
Sažetak
Elektroprivredne kompanije, programeri i investitori se zalažu za veći prodor proizvodnje energije vetra i solarne energije u postojeći energetski miks. Rad je posebno okrenut korišćenju energije vetra u Saudijskoj Arabiji. Profitabilan razvoj korišćenja energije vetra podrazumeva precizno poznavanje brzine vetra kako u vremenskom tako i u prostornom domenu. Brzina vetra je parametar sa najviše prekida i fluktuacija u poređenju sa svim meteorološkim promenljivim. Neizvesna priroda brzine vetra otežava vremensko predviđanje snage vetra. Brzina vetra zavisi od meteoroloških faktora kao što su pritisak, temperatura i relativna vlažnost. Predviđanje brzine vetra je od značaja za upravljanje mrežom, cenom energije, kvalitetom snabdevanja energijom. U radu se daje predlog za kratkoročno, višedimenzionalno predviđanje brzine vetra korišćenjem LSTM. Autori su razvili pet modela obukom mreža na osnovu izmerenih vrednosti brzine vetra na čas u periodu 1980-2019. uključujući egzogene inpute (temperaturu i pritisak). Utvrđeno je da je LSTM moćan alat za kratkoročno predviđanje brzine vetra. Međutim, LSTM može biti i nedovoljno precizan metod kada se u obuku mreža uključe egzogeni faktori i predviđanja dužine trajanja unapred.
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O članku

jezik rada: engleski
vrsta rada: neklasifikovan
DOI: 10.5937/fme2103643S
primljen: 15.05.2021.
prihvaćen: 15.06.2021.
objavljen u SCIndeksu: 30.07.2021.
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