+44.7831096266

  • Home
  • Dynamic Harmonisation
  • How DLH Works
  • Why DLH
  • Results and Savings
  • Savings Calculator
  • How savings are verified
  • Sectors we serve
  • Results and Savings
  • Pubs/Restaurants Savings
  • Hospital Savings
  • Super Market Savings
  • Data Centre Savings
  • Hotel Savings
  • Cold Store Savings
  • SCC
  • Privacy Policy
  • More
    • Home
    • Dynamic Harmonisation
    • How DLH Works
    • Why DLH
    • Results and Savings
    • Savings Calculator
    • How savings are verified
    • Sectors we serve
    • Results and Savings
    • Pubs/Restaurants Savings
    • Hospital Savings
    • Super Market Savings
    • Data Centre Savings
    • Hotel Savings
    • Cold Store Savings
    • SCC
    • Privacy Policy

+44.7831096266

  • Home
  • Dynamic Harmonisation
  • How DLH Works
  • Why DLH
  • Results and Savings
  • Savings Calculator
  • How savings are verified
  • Sectors we serve
  • Results and Savings
  • Pubs/Restaurants Savings
  • Hospital Savings
  • Super Market Savings
  • Data Centre Savings
  • Hotel Savings
  • Cold Store Savings
  • SCC
  • Privacy Policy

Energy CO2 Save

Energy CO2 SaveEnergy CO2 SaveEnergy CO2 Save

Results and Savings

  

RESULTS & SAVINGS

Measured, Verified Savings – Not Guesswork

DLH programmes are designed and validated using recognised best practice for measurement and verification.

Typical performance

Multi‑retailer pilots and roll‑outs show average refrigeration energy savings of 13% or more, with higher savings where plant is starting from a sub‑optimised baseline.

In one 220‑site deployment, DLH delivered around 13–14% energy savings on refrigeration.

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In another 280‑site estate, average monthly energy savings per site were estimated at over £1,500 against a subscription cost of around £500, giving net savings of c. £1,000 per site per month and a projected five‑year benefit of approximately £16.9m.

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How we verify savings

Savings are independently checked using IPMVP‑aligned methods.

Baseline creation: at least a year of historical daily energy data and ambient temperature is used to build a “business as usual” model for each pack or site.

Regression analysis: we model the relationship between cooling energy use and drivers such as outside temperature and trading pattern to forecast what consumption would have been without DLH.

Sub‑metering: where available, pack‑level data allows granular comparison before and after optimisation.

Ongoing reporting: real‑time dashboards show kWh reduction, cost savings and associated CO₂avoided for ESG and net‑zero reporting.

Energy CO2 Save

The Old Farmhouse, Ashorne, Warwick CV35 9DU

+44.7831096266

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