Adversing: 01622 699116 Editorial: 01354 461430


Eciency and connecvity of cooling technology remains at the forefront of speciflcaon. But does the answer lie in product innovaon, or should we change how we think about saving energy and data analysis? Tim Bound, Director, Transtherm Cooling Industries – the designer and manufacturer of adiabac cooling technologies – demonstrates how a new mindset could help speciflers to opmise their cooling technology choices.

he cooling market is rife with technologies that deliver impressive efficiencies and tap into all that is great about a smart facility or Industry 4.0. From the integration of PLCs to futureproof cooling methods, a wealth of technology is available but often, a shift in mindset is all that is needed to optimise these deliverables in the most cost effective way. Here are two examples:


Consider local weather conditions and reduce reliance on evaporative cooling

Finding the most energy and water efficient cooling method depends largely on regional weather. Cooler climates are ideal for dry cooling or even free cooling to reduce energy consumption, but only with the right insight.

Average daily temperatures for the UK range from 5°C in January to 16.4°C in August, averaging around 10.3°C across the year. Using this information, specifiers can make an informed choice about the cooling technology that performs the most efficiently for our climate. Furthermore, technology that leverages our cooler temperatures can reduce reliance on water- hungry evaporative cooling. Cooling towers generally rely on evaporative cooling 100% of the time, no matter what the temperature, whilst hybrid cooling plant uses evaporative cooling methods for around 50% of the year, only switching to dry mode in temperatures lower than 9.6°C. Adiabatic technology works efficiently in dry cooling mode for 97% of the year when operating in colder climates like the UK – only switching to evaporative cooling when temperatures exceed 21-23°C, which in mission critical environments that work around the clock, equates to just 3% of the year.

Understanding that cooling towers and hybrid systems rely heavily on evaporative cooling methods, it’s no surprise that adiabatic coolers

EFFICIENT, CONNECTED COOLING A shi change in consideraon

consume around 1% of the water used by traditional cooling towers, and approximately 2% of that used by wetted surface hybrid dry coolers. Even when operating in wet mode, adiabatic systems automatically employ a pulsed spray operation to minimise water usage. This is especially important for sites tasked with reducing water consumption, delivering much-improved Water Usage Effectiveness (WUE). Looking at those figures more closely, as water consumed in cubic meters over a one-year period for a 1000kW unit, an adiabatic cooler consumes 92m³ of water, compared to a hybrid cooler, which requires 8,647m³ and a conventional cooling tower which is more in the region on a staggering 28,032m³. Latent heat of evaporation dictates that for every kW of heat that a cooling tower dissipates it must evaporate 1.6kg of water. On top of this, in order to stop cooling tower base tanks from being clogged with the residual scale left over from the evaporation process, an additional amount of water must be bled off and replenished from a mains water supply. This means that the total water consumed is approximately 3.2kg per kW of cooling. For a typical 1,000kW cooling system this gives a cooling tower water consumption of 3,200kg every hour.

In contrast, adiabatic coolers, designed with water conservation in mind, would typically consume 350kg every hour and only for 3% of the year rather than 100% of the year.

A ‘whole facility’ approach to efficiency using connectivity and data analysis

In 2015, Transtherm integrated PLC (Programmable Logic Controller) interfaces into its industrial cooling systems. These enable smart communication between complex machinery including the cooling solution and software systems such as the building management system, to give greater control of the building environment and maximise system efficiencies.

The benefits of IoT connectivity are plentiful. With the addition of PLCs, operators can check/read parameters such as energy consumption, adjust/write parameters such as water temperature and understand the impact that changes will have not just on the cooling system, but on other related equipment too. It means improved efficiency, whilst facilitating the option to check performance and even prevent downtime by spotting problems earlier and undertaking preventative maintenance. Crucially, however, this development enables a ‘whole facility’ approach to sustainability, resulting in lower energy bills and reduced carbon emissions. But a barrier to improving energy efficiency is that many companies don’t understand other systems well enough. OEMs and specifiers of related products must work closely, from the design stage, to establish optimum conditions for the system as a whole, rather than individual products – particularly where sold as packaged solutions.

Let’s use the example of an industrial process cooling system. If we adjust the water temperature delivered by an air blast cooler from 40°C to 35°C it would inevitably mean the equipment has to work harder, may need additional fans and of course use more energy.

uThe top of the air blast cooler.

However, cooling systems are designed to reduce the temperature of other equipment and by analysing the effect this change has on entire system, it could mean greater energy savings overall. To demonstrate this using system EERs (Energy Efficiency Ratios), let’s imagine an air blast cooler with EER of 30 when cooling to 35°C, combined with a chiller with condenser water at 35°C with EER 8 (scenario A). Together, these would give an illustrative system EER of ‘X’, for the purposes of this exercise – it’s very difficult to calculate actual figures of course in a representative scenario. In scenario B, if an air blast cooler when cooling to 40°C at EER 40 was combined with a chiller with condenser water at 40°C (EER 6), it would give a system EER of ‘0.9X’. You can see that in this situation (given for illustrative purposes only), a less efficient EER on the air blast cooler in scenario A can give a higher system EER overall. The Internet of Things enables us to think outside of silos and consider the chain reaction – particularly useful for packaged solutions.



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  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50