Predicting Building Energy Demand and Retrofit Potentials Using New Climatic Stress Indices and Curves

Building energy requalification in Italy and Europe has been much discussed recent years due to the high percentage of existing buildings with poor performance. In this context, it is useful obtain a user-friendly fast tool predict thermal demand (TED) for space conditioning related primary consumption (PEC) as function climatic stress. study, SLABE methodology (simulation-based large-scale uncertainty/sensitivity analysis building performance) used simulate representative Italian buildings, varying parameters such geometry, envelope HVAC (heating, ventilating conditioning) systems. MATLAB® combination EnergyPlus analyze 200 belonging two structural types (multi-family apartment blocks) built 1961–1975. Nine scenarios (as-built eight retrofit ones) are investigated 63 locations. A regression shows that classical HDDs (heating degree days) approach cannot give an accurate prediction TED because solar radiation not accounted for. Thus, new indices developed alongside radiation, including heating stress index (HSI), cooling (CSI) yearly (YCSI). The purpose our work curves PEC. Testing novel performed by comparison another simulation tool, showing low discrepancy, i.e., coefficient variation root mean square error between 12% 28%, which confirms certain reliability here proposed.