Dr. Salvador Acha – Imperial College Research Associate

1. Dr. Salvador Acha – Imperial College Research Associate Supermarket Tasks and Strategies inReducing Energy Demand and CO2 Emissions 9th January 2012

2. Contents

3. Who is Sainsbury’s? • Supermarket chain was founded in 1869. • Currently has16% share of UK market (3rd place), tallying over 600 supermarkets and 400 convenience stores. • Approximate labour force of 200,000 workers. • Annual sales of £20,000 m and £600 m profits (3%) • Annual energy demand (only supermarkets) – 77% power and 23% natural gas. Notas: 1Electricas Emisiones UK:0.554 kgCO2/kWh 2Natural Gas Emisiones UK: 0.184 kgCO2/kWh 3Electricity cost: 0.077 p/kWh = $1.54 pesos/kWh 4Natural gas cost: 0.02 p/kWh = $0.40 pesos/kWh

4. Strategic Collaboration • Background • March 2010, Sainsbury’s announced a 5 year business partnership with Imperial College London and Grantham Institute. • Covers Climate Change, Supply Chain Management, Energy Efficiency and Intelligent System Operation and Low Carbon Construction. • Vision • Develop low carbon pathways to create a store fit for 2020 and beyond ahead of sector • Scenario planning – identify future performance requirements + key policy challenges, opportunities and constraints. • Objectives: • Decarbonisation • Energy efficiency and cost savings • Wider sustainability • Education and training

5. Low Carbon Roadmap • Has the purpose to illustrate the factors Sainsbury’s should consider when defining their long term energy strategy

6. Hythe is our Test Bed • The “smart-grid supermarket” concept focuses on managing the different processes occurring within a store with the objective of enhancing its energy consumption for mutual cost and environmental benefits while not forsaking the appeal and daily operations of supermarkets. • It will be a learning exercise • Practical implementation or use of existing smart controls to enhance supermarket energy demand. • Management of in-store processes • Enhancing energy efficiency strategies and ‘load flexibility’ in order to calculate the capacity available for devising ‘demand response’ programs.

7. Hythe Deliverables • Objectives of the project include the following: • Conduct a thorough monitoring of energy demand • Understand demand characteristics of services • Identify operational constraints of systems • Perform system trials that either save/shift energy use • Define best practices of energy demand per system and reduce carbon emissions • Trials will serve to validate Imperial College models • Assess potential of adopting flexible tariff schemes and offering demand response services to the grid • If trials are successful adopt roll back/roll fwd plan

8. Hythe Specs – A Carbon Step Store • Store specifications and what's innovative? • Opened in late February 2011 • Sales floor area of 35,759 sq. ft. with reflective ceiling, light tubes and considerable windows in the shop front and GM areas • Thorough energy monitoring with over 50 sensors • Rain water harvesting unit reduces water demand • Biomass boiler supplies low carbon heat with a maximum 700 kW capacity • Generator supplies low carbon electricity with a maximum 140 kW capacity (installed recently) • 50 kW PV panels in the roof

9. A day in the life of Hythe • About 5000 kWh/day = £385/day = 2.7 tCO2 • 272 kW peak, 130 kW base, 205 kW average Refrigeration systems begin consuming more energy during trade hours due to higher occupancy levels and ambient temperatures. Lighting systems go on 15 minutes before store opens and then smart controls manage the sales floor lighting while trading. HVAC system consume most of its energy through AHU’s during trading hours; weather conditions, occupation and set-points drive this demand. Hot food activities begin at 5 am when prepping the fish and meat counters, energy peaks indicate oven use for chickens, pastries, pizzas and staff food. Bakery activities begin at 4 am and are usually over by lunch time.

10. A day in the life of Hythe • Load composition • Lighting 32%, Refrigeration 39%, HVAC 10%, Hot Food 8%, Bakery 6%, Others 4%

11. A day in the life of Hythe • League Table Analysis • Ability to monitor thoroughly improves the level of analysis Top users of energy

12. A day in the life of Hythe • Carbon emissions • Having a biomass boiler shifts almost entirely the carbon emissions to the use of electricity

13. Hythe Monitoring • Opened in February 2011, Hythe allows the partnership to learn the characteristics of each system’s energy demand. • Trials of different systems for energy efficiency and demand response strategies which will benefit SSL are in progress • Desired outcome will be to better understand how to optimally integrate the systems • Benchmarking: • Hythe per week: 1st Q = 0.97 kWh/ft2 and 2nd Q = 1.01 kWh/ft2 • Baselines per week 05/06 = 2 kWh/ft2 and 09/10 = 1.40 kWh/ft2

14. Hythe Load Profile Analysis • Thorough monitoring allows us to build virtual store models and hence assess trade-offs in energy design strategies when the framework is strengthened • Consequently, impact of low carbon technologies can be estimated (e.g. biomass boiler, bio fuel generator) • At Hythe new technologies can abate emissions 20-45% and imported electricity from 1-25%

15. Quarterly Report • Refrigeration relationship results (spring 2011) • Temperature variations have an impact on pack performance however this is not the case for cabinets

16. Quarterly Report • HVAC relationship results (spring 2011) • Temperature variations have a slight impact on air handling unit performance but over 15 degrees demand more or less stagnates

17. Quarterly Report • Lighting relationship results (spring 2011) • As sunlight hours increase the energy demand is reduced indicating that natural light is well used by light tubes, windows and reflective ceiling

18. Quarterly Report • Daily profile results (spring 2011) • Logging energy data every half hour allows us to visualise daily load profiles with great detail, this will help us build energy models • This figure displays daily refrigeration demand, clearly showing how the system behaves differently due to weather conditions

19. Case study: Lighting System • Research and trials • Through the Clipsal system lux intensity can be regulated and there is an opportunity to question current settings (900 lux) and re-define best practices when commissioning new projects • Projected savings at Hythe under current settings are of 50 tCO2

20. Hythe Lighting (September 2011)Granularity is key in analysing performance Diming in the shop front area is not being achieved Car park load impact Dimming is being achieved efficiently in GM, shop front,and car park areas when natural day is abundant

21. Case study: Lighting System • Further work • Revise final commissioning and ideal sensor location • There are 100 Sainsbury’s sites with Clipsal – roll back/fwd program would be an easy win (10 store pilot approved!!!) • Each store is unique in itself, however new standard settings can be established based on store characteristics Peak Reduction 90% DSI 93% DSI Sensor 1Next to a duct

22. Case study: Lighting System • Early learning’s from trials are: • Customers and staff have not perceived changes and these have not impacted trade • Trials have been successful due to the robust lighting system control, thorough study of how the system works, and good collaboration between the partners • Lighting system at Hythe has benefited greatly from light tubes, shop front windows, and reflective ceilings and floor • Flexible energy demand in the lighting system is non-intrusive with Sainsbury’s business and has potential for further uses that can generate value for the company • Dial-in system is required to easily modify settings

23. Case study: HVAC System • Research and trials • The BMS Trend system controls the heating and cooling of the building through AHUs and biomass boiler • Although energy use in this system is efficient it was noted temperature set-points in the dry goods area are not being met • AHUs are low energy consumers, the boiler constitutes most of the demand (excessive use of the boiler during summer months)

24. Case study: HVAC System • Research and trials • Called Trend bureau to reduce set-points, changes have achieved less wood pellet use (20%) and ambient temperatures are closer to set point, savings are estimated to be 3 tCO2 • However, boiler efficiency also appears to give poor performance 22.7C 25.5C Old 19C Set-point Set-point

25. Case study: HVAC System • Early learning’s from trial and further work: • The HVAC system is quite efficient at Hythe and hence it’s demand is not as flexible as for lighting • Biggest area of opportunity is to save operating costs by using less wood chips to fuel the boiler and optimising temperature set points, and VSD of AHUs; proper post-comission plan is needed!!! • Relationship between HVAC and refrigeration needs work (waste heat recovery) and hence data needs to be logged

26. Case study: HVAC System • Data logging via Trend Energy Manager is now possible: • Trend BMS is now able to log its data and display it in its interface for Sainsbury’s and Imperial’s benefit • Level of detail in comparing metrics will allow us to find easier the relationship between HVAC, refrigeration, and ambient store temperatures.

27. Case study: Bakery/Hot Food System • Research and trials • Dr Acha shadowed bakery and hot food counter activities in order to learn the reasoning behind energy demand patterns • After studying the equipment and the manner in which staff employ them tips are advisable to save energy – if followed they could save22 tCO2without negatively impacting trade • Hythe management is aware of the potential benefits and are keen on applying these tips to reduce operating costs; plan is needed!!!

28. Case study: Refrigeration System • Research and trials • Danfoss and Parasense monitor and control this system • Thorough investigation is in progress, hence only energy saving trials have taken place by covering frozen and chilled cabinets during ‘non-trading’ with exciting results! • Management needs to reinforce this practice when possible • After sufficient data is collected and approval is given a pre-cooling approach of frozen products would like to be trialled Covering frozen and chilled cabinets during non-trading has very attractive savings

29. Case study: Refrigeration System • Early learning’s from the trial and further work: • Working closely with Danfoss/Sainsbury’s/Arcus FM etc is key to successfully progress in this area • Covers were done last Sunday and compared to a similar day <Max> 18C <Min> 13C • Average savings over 29 tCO2

30. Case study: Refrigeration System • Covering frozen cabinets make much sense since: • Cooling of products is more efficient and packs are not worked that hard (good opportunity to seriously reduce base load) • Talks with suppliers, retail and refrigeration team to make cover trials a best practice

31. Case study: Refrigeration System • Imperial College recommends a pre-cooling approach of frozen products to assess energy shifting possibilities: • It would be useful to identify how much energy consumption can be consumed at night time and avoided during the day. • Furthermore, load shedding alternatives such as fan and defrost dispatch will also be considered • Close monitoring of product temperature is paramount Pre-cooling begins Pre-cooling ends

32. Generation Trials What trade-offs does on-site generation bring? • Research • Operating strategies to be tested will first serve to conduct tests that help comprehend the real performance of the bio fuel unit while later trials will focus on optimising particular variables • The operating strategies being considered are: • Basic response (efficiency and response times) • Peak shaving (reduce maximum demand times) • Partial off-grid scenarios (reduce energy imports) • Cost reduction scenarios (simulate flexible tariff schemes)

33. Generation Trials • Research • Operating strategies to be tested will first serve to conduct basic tests that help comprehend the real performance of the bio fuel unit while later trials will focus on optimising particular variables • The operating strategies being considered are: • Basic response (efficiency and response times) • Peak shaving (reduce local grid max demand) • Partial off-grid scenarios (reduce energy imports/emissions) • Cost reduction scenarios (simulate flexible tariff schemes)

34. Hythe Savings Summary • Hythe estimated bills are £165k/year with a carbon footprint of 985 tonnes • Potential savings accumulated thus far are £19k (11%) and 104 tonnes of carbon (10%) – easy wins that can have immediate impact – winter quarter of 0.90 kWh/ft2? • If we just extrapolate the electrical power savings to 500 Sainsbury’s stores an attractive benefit of 50,000 tCO2can be achieved • Sainsbury’s needs to make the most out of these findings. How can we effectively translate this learning's to other sites?

35. Going Forward • Tasks • Continue thorough monitoring of Hythe to learn seasonal variations and adopt control strategies accordingly; produce quarterly reports • Address technical issues required to conduct refrigeration trial • Assess trials conducted thus far until capabilities have been fully explored (e.g. lighting, HVAC, refrigeration, etc.) • Implement regular operating schedule of bio fuel generator • Use data to develop energy models that will serve to evaluate other Sainsbury supermarkets (e.g. Supervision of Sainsbury’s MSc projects; strategic planning and virtual store projects) • Contribute in developing a single interface that monitors and analyses the energy consumption of the store (GE partner) • Key learning's should continue to be explored and when ready transferred to SSL for roll back/forward that enrich the companies position in its business sector

36. Thank you for your attention!