Global sensitivity analysis of an energy–economy model of the residential building sector. (August 2015)

• Record Type: Journal Article
• Authors: Branger, Frédéric; Giraudet, Louis-Gaëtan; Guivarch, Céline; Quirion, Philippe
• Is Part Of: Environmental modelling & software. Volume 70(2015:Aug.)
• Page Start: 45
• Page End: 54
• Publication Date: 2015-08
• Subjects: Sensitivity analysis -- Morris method -- Monte Carlo -- Energy efficiency; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.03.021
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: In this paper, we discuss the results of a sensitivity analysis of Res-IRF, an energy–economy model of the demand for space heating in French dwellings. Res-IRF has been developed for the purpose of increasing behavioral detail in the modeling of energy demand. The different drivers of energy demand, namely the extensive margin of energy efficiency investment, the intensive one and building occupants, behavior are disaggregated and determined endogenously. The model also represents the established barriers to the diffusion of energy efficiency: heterogeneity of consumer preferences, landlord–tenant split incentives and slow diffusion of information. The relevance of these modeling assumptions is assessed through the Morris method of sensitivity analysis, which allows for the exploration of uncertainty over the whole input space. We find that the Res-IRF model is most sensitive to energy prices. It is also found to be quite sensitive to the factors parameterizing the different drivers of energy demand. In contrast, inputs mimicking barriers to energy efficiency have been found to have little influence. These conclusions build confidence in the accuracy of the model and highlight occupants' behavior as a priority area for future empirical research. Highlights: We perform a sensitivity analysis of a model for space heating in dwellings. We do a Monte Carlo analysis and use the Morris method to find important inputs. The most important input is energy price. We further test the robustness of the ranking and the screening.