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Energy Procedia
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License: CC BY NC ND
Data sources: Crossref
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Energy Procedia
Article
License: CC BY NC ND
Data sources: UnpayWall
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Metamodeling energy indicators in neighborhoods with growing deployment of heat pumps and rooftop photovoltaics

Authors: Dirk Saelens; Christina Protopapadaki;

Metamodeling energy indicators in neighborhoods with growing deployment of heat pumps and rooftop photovoltaics

Abstract

Abstract This paper evaluates simple metamodels to predict local electricity demand and grid restrictions, in residential neighborhoods with heat pumps and photovoltaics. The procedure and challenges of developing such models are described. Modeling is based on results obtained from detailed simulation of buildings and the grid. Linear and logistic regression models are developed for electricity demand and minimum voltage respectively, as a function of neighborhood characteristics, related to both building and electrical network properties. The paper shows that linear regression can be used for a first evaluation of electricity demand. For voltage violations, logistic regression gives acceptable results; however, more complex models are needed to approximate voltage levels.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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