A comparative study of benchmarking approaches for non-domestic buildings: Part 2 – Bottom-up approach

Abstract

The bottom-up methods for energy benchmarking aim to derive a yardstick for energy performance based on a theoretical analysis of a building. While the top-down methods drive performance improvement by ranking a building against its peers, the bottom-up methods are focused on the building's specific context. Consequently, the bottom-up methods can help identify how performance improvement could be materialised. These two complementary approaches can improve design practice and facilities' management. Two bottom-up methods that could be used for energy benchmarking have been reviewed using UK schools as case studies: Building physics and aggregated end-use. The aim is to demonstrate how these methods could be used for benchmarking and identify their benefits and limitations. When all energy components are included in a model under expected operating conditions, the building physics method can be used to establish a baseline for energy performance. It is demonstrated that where this method is used under standardised operating conditions and is subject to minimum energy performance requirements, as prescribed by the Energy Performance of Buildings Directive (EPBD), it can be used to establish a benchmark for energy performance. It is also shown how aggregated end-use methods such as CIBSE TM22 can be used to define system level benchmarks, and identify the root causes for discrepancy between measured performance and design intent in a systematic way.

Evaluating energy performance in non-domestic buildings: A review

“…Several sources have addressed the classification of building performance evaluation methodologies. A recent two-part study separates top-down (deductive) benchmarking methodologies involving statistical approaches [21] from bottom-up (inductive) methodologies which use aggregated end-use calculations or building simulation [22]. Other studies have categorised benchmarking through black, grey or white box methodologies [23], where these are defined as follows:…”

“…White-box Black box (sometimes grey box) [23], [26], [27] Bottom-up Top-down [21], [22] Forward modelling Data-driven modelling or inverse modelling [24], [28], [29] Benchmarking [15] Simple calculation The selection of the most appropriate analysis method will generally depend on the following factors: accuracy, sensitivity, versatility, speed, cost, reproducibility and ease of use [24].…”

“…At the simplest level, total energy consumption can be calculated as the sum of the estimated consumption of all of the energy-consuming systems [41]. This aggregated method has been cited as one of the most accurate methods for predicting energy performance, and has the advantage of permitting the development and use of system level benchmarks [22]. In existing buildings, these calculations are compared to benchmark levels and total measured energy consumption in the building in order to give useful information and evaluations of efficiency levels, in accordance with the CIBSE TM22 methodology [42].…”

A review on sustainable construction management strategies for monitoring, diagnosing, and retrofitting the building’s dynamic energy performance: Focused on the operation and maintenance phase

“…Many previous studies established benchmarking models for diagnosing a building's dynamic energy performance using various approaches, such as the engineering, statistical, and hybrid approaches (refer to Table 7) [70,[104][105][106][107][108][109][110][111][112][113][114][115][116][117][118][119][120][121][122][123].…”

“…This can be done in two different ways: (i) by calculating the theoretical energy performance of a building using equations; and (ii) by calculating the theoretical energy performance of a building with simulation tools. Burman et al [107] used the building physics method (i.e., UK National Calculation Methodology (NCM)) and aggregated end-use (i.e., the Technical Memorandum 22 (TM22) methodology) to develop a benchmarking model for diagnosing the dynamic energy performance of school buildings in the UK. The results showed that the energy benchmarks derived from the proposed method could be used as the baselines for diagnosing a building's dynamic energy performance, but it might not be practical for all buildings due to its complexity.…”