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A comparison of strategies for net demand forecasting in case of PV power production and electricity consumption
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics. (BEESG)
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics. (BEESG)
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics. (BEESG)
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

This paper aims to investigate the relative difference in accuracy between forecasting net demand, i.e., electricity con- sumption less the photovoltaic (PV) power production, directly and indirectly, where the latter implies forecasting consumption and production separately before subtraction. Depending on the variability and penetration of PV power production, variability of the net demand time series is likely to increase as well, which may influence accuracy of the forecast. The well-known AutoRegressive Integrated Moving Average (ARIMA) model is employed to forecast the univariate time series. We show that the direct strategy leads to a forecast with higher accuracy. Moreover, the difference in accuracy between the strategies appears to increase with lead time. 

Place, publisher, year, edition, pages
2017.
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:uu:diva-332891OAI: oai:DiVA.org:uu-332891DiVA: diva2:1154509
Conference
PVSEC
Available from: 2017-11-02 Created: 2017-11-02 Last updated: 2017-11-06

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