Optimum building energy retrofits under technical and economic uncertainty

In a prior study, the authors showed that decomposing holistic, blackbox building energy models into discrete components can increase the computational efficiency of large-scale retrofit analysis. This paper presents an extension of that methodology to include an economic cost-benefit model. The entire framework now comprises an integrated modelling procedure for the simulation and optimisation of retrofit decisions for individual buildings. Potential decisions can range from the installation of demand-side measures to the replacement of energy supply systems and combinations therewithin. The classical decision theories of Wald, Savage, and Hurwicz are used to perform non-probabilistic optimisation under both technical and economic uncertainty. Such techniques, though simple in their handling of uncertainty, may elucidate robust decisions when the use of more intensive, probabilistic assessments of uncertainty is either infeasible or impractical.

► Retrofit decision-making using conventional building energy models is desirable, but costly.
► Decomposing such models into sequences can make exhaustive simulations practical.
► Highly unknown economic forecasts make non-probabilistic uncertainty handling useful.
► This work presents a holistic optimisation strategy for building retrofits.