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Improving Cooling Loop Efficiency in Modern Data Centres

Learn how data-centre cooling loops are optimised using hydronic modelling, enabling improved energy efficiency, reliability and chiller performance.

Why Data-Centre Cooling Requires Precision

Data centres operate under strict thermal conditions. Even small inefficiencies in cooling loops can raise energy use, increase operating costs or threaten system uptime. Because cooling runs 24/7, hydronic behaviour — flow, pump performance, ΔT, chiller stability — has a major impact on both reliability and cost.

Cooling optimisation therefore depends not only on equipment selection but on how the full loop behaves as an interconnected system.

Key Strategies Used to Optimise Cooling Loops

Hydronic modelling helps engineers evaluate how different design and control strategies influence both stability and efficiency. Common optimisation areas include:

  • chiller staging and sequencing
  • free cooling integration
  • redundancy strategies (N+1, N+2)
  • supply–return temperature optimisation
  • pump speed control and variable flow

These strategies ensure the system remains stable under varying IT loads while minimising cooling energy use.

If you want to explore how modelling supports system-wide thermal optimisation, discover how Hysopt helps engineers improve portfolio-wide HVAC performance ›

Reducing Energy Use While Protecting Uptime

Data centres cannot compromise on uptime. Any optimisation strategy must therefore protect cooling redundancy while reducing operational costs. Hydronic modelling reveals limitations that traditional calculations overlook, such as:

  • pressure bottlenecks
  • uneven flow distribution across cooling coils
  • insufficient ΔT for chiller efficiency
  • pump oversizing or undersizing
  • unstable control strategies under partial load

By visualising real hydraulic behaviour, engineers can adjust system configurations before costly issues arise.

Future-Proofing Cooling Systems With Advanced Modelling

As data centres grow, cooling systems must scale without increasing risk. Modelling enables engineers to test capacity expansions, new chiller connections or hybrid cooling concepts before implementation.

It also supports long-term performance benchmarking across multiple sites, ensuring consistent, predictable cooling behaviour throughout a full building portfolio.

To explore how modelling strengthens long-term performance management, see how Hysopt supports HVAC portfolio optimisation ›

FAQ: Data-centre Cooling Optimisation

What matters most when optimising a cooling loop?

Flow balance, ΔT performance, pump control and chiller sequencing typically have the greatest impact.

Can free cooling always be integrated?

It depends on climate conditions and system temperatures, but modelling helps identify when it is viable and how much it saves.

How does modelling protect uptime?

It exposes hydraulic issues that may cause unstable cooling, allowing engineers to design redundancy and control strategies that maintain safe temperatures under all load conditions.

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