Metamodeling energy indicators in neighborhoods with growing deployment of heat pumps and rooftop photovoltaics. (October 2017)

• Record Type: Journal Article
• Authors: Protopapadaki, Christina; Saelens, Dirk
• Is Part Of: Energy procedia. Volume 132(2017)
• Page Start: 555
• Page End: 560
• Publication Date: 2017-10
• Subjects: metamodeling -- linear regression -- logistic regression -- grid impact -- electricity demand -- residential neighborhood -- heat pump; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2017.09.736
• Languages: English
• ISSNs: 1876-6102

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.