Objective Building Energy Performance Benchmarking Using Data Envelopment Analysis and Monte Carlo Sampling

Seong-Hwan Yoon,Cheol-Soo Park

doi:10.3390/su9050780

Abstract

An objective measure of building energy performance is crucial for performance assessment and rational decision making on energy retrofits and policies of existing buildings. One of the most popular measures of building energy performance benchmarking is Energy Use Intensity (EUI, kwh/m2). While EUI is simple to understand, it only represents the amount of consumed energy per unit floor area rather than the real performance of a building. In other words, it cannot take into account building services such as operation hours, comfortable environment, etc. EUI is often misinterpreted by assuming that a lower EUI for a building implies better energy performance, which may not actually be the case if many of the building services are not considered. In order to overcome this limitation, this paper presents Data Envelopment Analysis (DEA) coupled with Monte Carlo sampling. DEA is a data-driven and non-parametric performance measurement method. DEA can quantify the performance of a given building given multiple inputs and multiple outputs. In this study, two existing office buildings were selected. For energy performance benchmarking, 1000 virtual peer buildings were generated from a Monte Carlo sampling and then simulated using EnergyPlus. Based on a comparison between DEA-based and EUI-based benchmarking, it is shown that DEA is more performance-oriented, objective, and rational since DEA can take into account input (energy used to provide the services used in a building) and output (level of services provided by a building). It is shown that DEA can be an objective building energy benchmarking method, and can be used to identify low energy performance buildings.

Highlights

For the energy performance assessment of existing buildings, various benchmarking methods have been developed, such as a regression model [1,2,3,4] and a dynamic simulation model [5,6]
The current building energy performance benchmarking approaches are hampered by a range of deficiencies such as lack of objectively quantifiable expressions of requirements and lack of proper assessment tools to ascertain expected performance [7]
Energy Use Intensity (EUI) is straightforward and easy to understand, but it only represents the amount of energy

Summary

Introduction

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Results

Conclusion