Ies Model in Building

1. Introduction 2

Description of case-study 2

Summary of results 2

Results analysis 3

Conclusions 3

1. Introduction

Briefly describe the nature of the exercise and the kind of questions that you will be investigating.

There is significant and growing evidence that buildings do not perform as anticipated at their project design stage. Variables that affect building energy performance arise from design, construction, handover and operation. The result is that actual energy performance is often significantly different from its predictions. This is often referred to as the ‘performance gap’.

Brise soleil

 building energy consumption in kWh/m²/annum or carbon emissions data from the CDP. Benchmarks allow us to understand performance in relation to others and as such are useful for setting targets, enacting change, improving performance or sometimes just a well-deserved pat on the back for being the leader in the league tables.

By definition, benchmarks must come from the analysis of a large sample. For example, when producing energy consumption benchmarks for specific types of buildings e.g. offices, retail, warehouses, a large number of these must have been measured in the first place for this average (benchmark) to be statistically significant and reasonably accurate. A good example is CIBSE Technical Manual 46: Energy Benchmarks, which was produced to accompany the Operational Energy Rating methodology from the Department of Communities & Local Government. This document has proved useful since it was published in 2008 (although it needs updating!) and has provided energy professionals, academics, facilities managers and many more with a yard stick to compare and contrast their own energy consumption with. One needs to understand the assumptions made in the methodology (as always) to fully appreciate the applicability of benchmarks. For example, ‘adjusted’ data for weather, occupancy or any other variable can mean not comparing apples...