Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 222222
Loughborough University

Centre for Innovative and Collaborative Construction Engineering

2015


Dr Maria Spyrou

Thesis

Multi-scale analysis of the energy performance of supermarkets

Project Title

Energy Modelling of Buildings in the Tesco Estate

Company

Tesco

Supervisors

Academic:
ProfessorMalcolm Cook
Professor John Mardaljevic

Industrial:
Mr James Pitcher
Mr James Conlin

Director of Research:
Professor Stephen Ison

Research Period

2010 - 2014

Energy Modelling of Buildings in the Tesco Estate

Context/Background

The Tesco estate contains more than 2000 buildings comprising data centres, offices, distribution centres and shops. These range from over 40 years old to brand new and, although Tesco have a very well developed energy management strategies, the consumption of energy in the sector is correlated to a wide variety of factors, including football, weather, promotions, etc. Tesco also have vast quantities of energy data resulting from sub-metering carried out on most of its sites. The focus of this project is to make use of this data, coupled with a detailed understanding of the main drivers of energy consumption, to deliver better control and energy reduction targeting. Although this research would primarily be concentrated in UK and Ireland, as a growing international business there is scope for a comparative study with their overseas businesses.

Aims and Objectives

To develop modelling tools for predicting future energy consumption of buildings in the Tesco estate which lead to demonstrable savings in energy use.

  • Conduct an analysis of existing energy consumption data and establish correlations with weather, product promotions, time of year, control strategies, design practices and other possible drivers.
  • Construct dynamic thermal simulation (DTS) models for each Tesco store format and use these to predict current energy consumption. These will be validated using the existing energy data and BMS data.
  • Use the DTS models to test the energy saving potential of a range of design and practice interventions and to test these using current and future weather data sets.
  • Use the DTS predictions of each store type and the correlations established, to develop a non-expert (possibly spreadsheet) tool, for testing the energy impact of operating practices.


Methods

Research methods are likely to include building simulation software for predicting energy consumption, thermal comfort and ventilation performance, and data analysis software for determining cross correlations and variable dependencies and collection of BMS data. It may also be necessary to undertake additional monitoring of certain parameters such as temperature and lighting levels, in order to gain a better understanding of their impact.     

Benefits/Expected Outcomes

As the UK’s largest retailer, Tesco has a vast property portfolio which includes offices, distribution centres and retail stores. Reducing the energy consumption of these assets by developing suitable energy consumption prediction tools and carrying out operational or design interventions is likely to yield major benefits for the company and to the sector as a whole.

Spyrou, M., et al., 2011. Energy consumption prediction models in the retail sector, CIBSE Technical Symposium, De Montfort University 6 & 7 September 2011.

 

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Loughborough University
Leicestershire
LE11 3TU

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