Analiza i predviđanje potrošnje energije poslovne zgrade korišćenjem višestruko linearno regresionog modela, metode potpornih vektora i neuronske mreže
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Apstrakt
S obzirom na stalni porast interesovanja za povećanje energetske efikasnosti u zgradarstvu, neophodno je primenjivati i unapređivati postojeće i razvijati nove metode za predviđanje i analizu
potrošnje zgrada. Na modelu tipične poslovne zgrade u Beogradu ispitivan je uticaj različitih karakteristika zgrade. Simulacija potrošnje energije na časovnoj bazi urađena je korišćenjem
programa HAP (Hourly Analysis Program). Za dalju analizu izabrana su tri faktora koja u najvećoj meri utiču na potrošnju energije za hlađenje: specifična instalisana snaga osvetljenja, udeo prozora
u spoljašnjem zidu i koeficijent propustljivosti Sunčevog zračenja kroz prozore. Analiza je vršena za različite vrednosti ova tri parametra. Za kreiranje i testiranje višeparametarskog modela korišćeno
je 245 simulacija. Predložen je višestruko linearni model koji može da se koristi za određivanje potrošnje energije za hlađenje, a koji kao ulazne veličine koristi pomenuta tri parametra. U cilju
predviđanja potrošnje, razvijeni su modeli primenom metode potpornih vektora (support vector machine) i veštačkih neuronskih mreža i izvršeno je poređenje rezultata sa višestruko linearnim
modelom. Pokazano je da modeli zasnovani na metodi potpornih vektora i neuronskim mrežama postižu veću tačnost predvidjanja u odnosu na linearni višeparametarski model.
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