Development of a new energy benchmark for improving the operational rating system of office buildings using various data-mining techniques

Abstract

As improving energy efficiency in buildings has become a global issue today, many countries have adopted the operational rating system to evaluate the energy performance of a building based on the actual energy consumption. A rational and reasonable energy benchmark can be used in the operational rating system to evaluate the energy performance of a building accurately and effectively. This study aims to develop a new energy benchmark for improving the operational rating system of office buildings. Toward this end, this study used various data-mining techniques such as correlation analysis, decision tree (DT) analysis, and analysis of variance (ANOVA). Based on data from 1072 office buildings in South Korea, this study was conducted in three steps: (i) Step 1: establishment of the database; (ii) Step 2: development of the new energy benchmark; and (iii) Step 3: application of the new energy benchmark for improving the operational rating system. As a result, six types of energy benchmarks for office buildings were developed using DT analysis based on the gross floor area (GFA) and the building use ratio (BUR) of offices, and these new energy benchmarks were validated using ANOVA. To ensure the effectiveness of the new energy benchmark, it was applied to three operational rating systems for comparison: (i) the baseline system (the same energy benchmark is used for all office buildings); (ii) the conventional system (different energy benchmarks are used depending on the GFA, currently used in South Korea); and (iii) the proposed system (different energy benchmarks are used depending on the GFA and the BUR of offices). The results of this study showed that the baseline and conventional operational rating system can be improved by using the new energy benchmark of the office building proposed in this study.