search.noResults

search.searching

saml.title
dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
ENERGY EFFICIENT DATA CENTRES


DESIGNING COOLING SYSTEMS TO ALIGN WITH DATA CENTRE EXPANSION


Jacob Wolfe, global key account manager, Data


Centres, at Armstrong Fluid Technology, looks into the benefits of setting up a data centre HVAC system that increases in load gradually


T


he case for utilising the modular approach in data centre HVAC has become even stronger in


recent months. Potential limitations in terms of grid power service and stringent environmental demands means that setting up a HVAC system which is designed to increase in load gradually over time has multiple benefits. Other than the obvious boon of lower initial capex, the approach helps to avoid the pitfall of pump over-sizing which, within HVAC, is seen as a common factor in inefficient systems.


WHY NOT JUST DESIGN FOR 100% STRAIGHT AWAY? One issue with designing for final cooling load from the outset involves the unnecessary front-loading of investment in building services for the site. It also fails to provide the necessary flexibility to increase incrementally over time, effectively limiting future capacity without significant disruption. In addition, this approach involves significant risks of energy wastage due to the operation of over-sized equipment. Although the cooling technologies themselves are highly reliable, technical issues are more likely in these situations. Simply put, it can get a project off to a bad start whilst complicating future efforts to change or expand the system.


ALIGNING COOLING SYSTEMS WITH DATA CENTRE BUSINESS MODELS The keys to effective incremental expansion of cooling systems in alignment with increasing processing capacity include modularity, repeatability, scalability, demand-based control and Active Performance Management.


Modularity: The best cooling systems for data centres are those that are designed on modular principles, specifically for incremental expansion. This ensures that additions to the system can be integrated quickly and seamlessly, without time-consuming and costly installation and commissioning, or additional development in-situ. In general, increasing ease and speed of expansion efforts while avoiding over-sizing at all times is a good strategy.


Repeatability: To create a cooling system which delivers in terms of both modularity and repeatability, it is helpful to think in terms of offsite-manufactured packaged plantrooms. As these solutions are fully assembled and tested before they leave Armstrong’s factory, many potential project risks (such as poor system integration) are eliminated. Solutions such as this, which are capable of ‘bolting-on’ additional cooling in line with expansion of IT processing capacity, can avoid the energy wastage of an over-sized plant, whilst providing repeatability of performance.


Scalability: With proper forecasting, plant capacity will help Armstrong build these repeatable designs in a scalable fashion as the data centre expands. A global footprint also helps as it ensures similar systems and potentially exposes extra capacity.


Armstrong packaged plant room www.essmag.co.uk


Demand-based control: As data centre cooling systems need to be reliable and efficient over wider ranges of operating conditions as the site expands, it is crucial that system components and control technologies are designed for variable demand and ultra-efficient performance at part-load. This requires variable- speed components across the system, and a control strategy specific to the unique operating characteristics of variable-speed devices. When a variable frequency drive (VFD) is added to a compressor, pump or fan to


3D rendering of chilled water plant room


improve part-load efficiency, the energy saving potential is huge due to the pump fan laws which state that power is proportional to rotary speed cubed (PαN3). This would equate to a potential 400% increase in operating efficiencies. This is only possible, however, if the pump fan law relationship between pressure and rotary speed, along the Natural Curve, is maintained at the decreased speed. Traditional control practices often fail to optimise


this potential. Pumps, for example, are often set to maintain a fixed or minimum differential pressure across the pump supply and return headers. This means the pump will not have the freedom to operate along its Natural Curve and will consume more energy. With variable speed chillers, integrated control ensures operation along the chiller’s Natural Curve for all operating scenarios, ensuring optimum efficiency at all loads.


Active Performance Management: Advanced connectivity and visibility of system performance are also important throughout the lifetime of ultra-efficient critical cooling systems. The Active Performance Management developed by Armstrong Fluid Technology, for example, helps to optimise HVAC systems at any stage of a data centre’s life-cycle, responding to changing cooling requirements. APM also creates maintenance savings, being able report issues such as excessive vibration, pump in hand, risk of cavitation or a dead head should they start to occur. With data centres, the


unpredictability of the sector itself must be met by flexibility in design methodology.


Jacob Wolfe


Armstrong Fluid Technology https://armstrongfluidtechnology.com/


ENERGY & SUSTAINABILITY SOLUTIONS - Summer 2026 17


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40