Tesco’s Top Shelf Energy Reduction Plan

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At Tesco reducing our impact on the environment is not only an essential part of our overall commitment to be a responsible business, but it is also a way to increase our resilience to risk, help secure the supply of our products and provide opportunities to save money, such as energy.

Over the last few years, Tesco, one of the world’s leading supermarket and retail companies with operations in 14 countries, has been working with external experts and colleagues to take another look at our environmental strategy, ensuring it remains credible in meeting our commitments to reduce our impact on the environment. From this consultation process we identified key environments that we have an impact on, either through our direct operations or through our sourcing activities. One of these is energy.

In fact, it’s estimated that refrigeration alone, both commercial and residential, accounts for 9% of the world’s electric energy usage budget today. With this in mind, we needed greater visibility and a better understanding of the energy and operational performance of our refrigeration assets in all of our 147 stores to meet our continued energy reduction goals.

To do this, we partnered with IBM Research-Ireland to help us unlock the known value within our extensive and comprehensive refrigeration datasets to pinpoint where we had issues, and how best to address them using Big Data analytics.

The Tesco Ireland highly instrumented fridge system generates more than 10 billion discrete records on an annual basis. Although highly structured, given the sheer volume of data involved, this presented a pretty big challenge — we couldn’t get our hands around the data and get the insight we needed.

As a project starting point, IBM Researchers deployed big data tools and methodologies to manage and analyze this IoT data environment.

The result? Through the development and use of rule-based screening analytics, fridge statistical models, and working closely with the Tesco Engineering and Maintenance teams, we were able to apply the IBM analytic findings to deliver new and valued insight on our fridge operations. For example, we were able to automatically detect non-performing fridges, equipment failures, elements that would continue to waste energy if left undetected.

From this new insight, Tesco management was able to generate a series of fridge policy and control settings change recommendations, which are now being implemented across the company and yielding average energy savings of between 10%-15% per refrigeration pack type.

Currently, from analysis and project implementation work already carried out over the last 18 months by the Tesco and the IBM teams, annualized savings of €1.25 million having already been realised within the project, with an expected savings of €2.5million per annum once implementation work has been completed across the company over the next 12 months.

Additionally the project has already delivered almost 3,500 tonnes of CO2 saving, with an additional 3,500 tonnes of CO2 expected to be saved by project end, thus making a significant contribution to meeting Tesco’s ongoing carbon reduction goals. The big data insights and expertise that the IBM team brought to this project have been invaluable to unlocking these significant savings.

This project — started 3 years ago– has been an exciting and on-going journey of discovery for us.

Up until recently refrigeration was almost treated as a “black box” within most organizations, and systems were considered too complex and challenging to be thought of as major sources of energy saving potential.

The Tesco and IBM research project has helped to challenge and change this position significantly. It’s now evident that with the right mix of engineering and statistical skills, and with teams working closely together, we can significantly advance our understanding of the drivers of energy usage.

Additional refrigeration research now underway at Tesco is expected to provide even greater insight and savings. The application of deeper statistical methodologies will produce comprehensive and accurate demand side energy usage and maintenance prediction models, thus pushing further energy cost savings and system performance to even higher levels.

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Article taken from an interview on September 4th 2015 with John Walsh, Energy and Carbon Manager for Tesco Ireland and leader of Tesco’s energy reduction strategy for the past 5 years which included a key focus area of retrofitting existing commercial buildings with low energy and renewable technologies, and in the low energy design for future commercial buildings.