A taxonomy of key uncertainties using high-level frameworks for energy modelling

Published in: Industry, Innovation, and Infrastructure for Sustainable Cities and Communities: Proceedings of the 17th LACCEI International Multi-Conference for Engineering, Education and Technology
Date of Conference: July 24-26, 2019
Location of Conference: Montego Bay, Jamaica
Authors: Javier Urquizo (Escuela Superior Politécnica del Litoral, EC)
Carlos Calderón (Newcastle University, GB)
Philip James (Newcastle University, GB)
(Escuela Superior Politécnica del Litoral)
Full Paper: #1

Abstract:

This paper provides a tri-dimensional taxonomy of uncertainty of the Newcastle CarbonRoute Framework (NCRF) using a concept map. It requires the identification of the sources, issues and sub-issues of the uncertainties in the modelling process. These issues can be broken down in the contributing forms of uncertainty and classified as either contributing to inaccuracy (systematic bias of the data) or imprecision (random variability of the data). Much of the data used in this research comes from surveys based on samples; some inaccuracy is unavoidable in the energy estimations presented. The most significant source of inaccuracy is perhaps the sampling error, where the characteristics of a sample do not exactly match the characteristics of the whole population. The purpose of the research is to develop a taxonomy that shows how uncertainties are propagated through the modelling process (data – model – refinement – validation) and in the resulting estimates of annual energy consumption.