Overheating risk and cooling demand in residential buildings: performance prediction and improvement using a prescriptive approach

Abstract

Depending on general climatic trends and specific (urban) microclimatic conditions, the reliable estimation of the overheating risk in buildings has become increasingly important. As such, detailed simulation of the related phenomena can provide useful information. However, deployment of detailed simulation involves a number of challenges, including time and effort expenditures not accounted for in typical building delivery processes. In this context, careful application of prescriptive methods may provide – at least for a specific class of applications – a reasonable alternative. The present contribution explores this possibility via a specific case study involving a large sample of residential buildings in Gaza, Palestine. This sample includes some fifty multi-unit apartment buildings representing the bulk of residential building stock in Gaza. These buildings were assessed via both numeric simulation and regression-based methods, assuming the latter can provide the basis for development and validation of a prescriptive approach. Toward this end, a number of independent variables were considered and the level of their association with the computed values of the designated building performance indicators was observed. Comparison of the regression-based and simulation-based methods revealed a reasonable level of agreement. This suggests that the proposed prescriptive method may provide an attractive alternative to highly detailed simulation.