Short term electricity load forecasting for institutional buildings

Gespeichert in:

Veröffentlicht in:	Energy reports 5(2019) vom: Nov., Seite 1270-1280
Personen und Körperschaften:	Kim, Yunsun (VerfasserIn), Son, Heung-gu (VerfasserIn), Kim, Sahm (VerfasserIn)
Titel:	Short term electricity load forecasting for institutional buildings/ Yunsun Kim, Heung-gu Son, Sahm Kim
Format:	E-Book-Kapitel
Sprache:	Englisch
veröffentlicht:	2019
Gesamtaufnahme:	: Energy reports, 5(2019) vom: Nov., Seite 1270-1280 , volume:5
Schlagwörter:	Aufsatz in Zeitschrift
Quelle:	Verbunddaten SWB Lizenzfreie Online-Ressourcen

Details
Zusammenfassung:	Peak load demand forecasting is important in building unit sectors, as climate change, technological development, and energy policies are causing an increase in peak demand. Thus, accurate peak load forecasting is a critical role in preventing a blackout or loss of energy. This paper presents a study forecasting peak load demand for an institutional building in Seoul. The dataset were collected from campus area consisting of 23 buildings. ARIMA models, ARIMA-GARCH models, multiple seasonal exponential smoothing, and ANN models are used. We find an optimal model with moving window simulations and step-ahead forecasts. Also, including weather and holiday variables is crucial to predict peak load demand. The ANN model with external variables (NARX) worked best for 1-h to 1-d ahead forecasting.
ISSN:	2352-4847
DOI:	10.1016/j.egyr.2019.08.086