Calculating the cost of HVAC air filters



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Thomas Carlsson R&D Director Table of Contents: Abstract 2 Background 3 Project Aim 3 Results 4 Conclusions 6

Abstract A computer program for calculating and optimising the filter cost in a ventilation system has been developed. The total cost for a filter during its service time can be divided into the following parameters, Cost for the Filter Energy cost for the fan to overcome pressure drop Cost for Maintenance ( labour cost for changing filters) Cost for Waste The distribution of costs on the different categories depends on which filter class is used, fan efficiency and service time. The dominating part is the energy cost (for a filter with filter class F7 the energy cost is 80 % of the total cost [1] ). Using a filter with lower pressure drop (more filter bags) will reduce the cost for energy use, but the filter cost will increase. To get a cost-effective installation, the ventilation system has to be optimised regarding the number of pockets on the filter. 2

Background In Sweden there is an energy conservation program running in order to minimise the amount of electricity used. For the HVAC industry there has been a focus on the energy consumption, during the service period for HVACcomponents. To justify more energy efficient equipment (from an economical point of view) a calculation model has been developed to calculate the Life Cycle Cost (LCC) for components in an HVAC system. LCC = Investment Cost + Energy Cost (during service time) + Maintenance Cost + Disposal Cost The idea with this approach is to get as low LCC for a component as possible. By increasing the investment cost, the cost for energy use can be reduced more than the cost increase for the investment. This would lead to a lower total cost for the customer and lower energy consumption. This model can be used for fans, pumps, filters, building insulation, low energy lamps etc. Project Aim The aim for this project has been to develop a computer program that optimises the filter cost (energy+ investment cost for the filter) in an HVAC system. The inputs to the program are Investment cost for the filter Number of filters in the system Flow rate Dust concentration in air Exchange interval Energy cost ( caused by pressure drop from the filter) Fan efficiency By inserting this data, the program calculates the lowest filter cost for a filter installation. The calculation starts with a 4-pocket filter (standard concept from Scandfilter) in the installation. When the program has calculated the filter cost for the installation it automatically changes one of the filters to a 6-pocket filter (extending the filtration area in order to reduce the pressure drop and lower the energy consumption) and runs the calculation one more time. If this new filter cost is lower than the first calculated cost the program goes on increasing the filtration surface area until it reaches the lowest filter cost. 3

If the program found that after the first calculation the cost has increased, it automatically starts to reduce the filtration area by removing filters from the filter installation. When the lowest filter cost is found it stops and presents the result. The program output is number of filters and pockets, energy consumption, initial pressure drop and final pressure drop. Filter Cost vs. Filter Surface Cost Minimum Filter Cost Filter Surface Results Calculations have been made for two different filter classes to show the difference in filter cost comparing an optimised installation and a not optimised installation. Further on the calculations show the difference in filter cost for a filter of class F5 and F6. Example Filter Class F6 Number of filters 10 PCs. Flow rate 10 m 3 /s Dust concentration 15 µg/m 3 Energy cost 0.05 US$/kWh Fan efficiency 50 % Change Interval 12 months Filter class F6 Table 1 Filter Class F6 Standard Concept (4-pocket filter) Optimised Concept (6-pocket filter) Number of Filters 10 10 Initial Pressure Drop Pa 77 61 Final Pressure Drop Pa (after 12 months) 230 140 Cost for Energy US $ 1600 1000 Cost for Filter US $ 550 750 Total Cost (Filter +Energy) US $ 2150 1750 4

As we can see from the example it is possible to reduce the cost by 17 % from 2 150 to 1 750 US $, just by selecting correct number of pockets for the system. The energy consumption has been reduced from 26 800 kwh/year to 17 600 kwh/year. Another important output from the program is that it highlights the differences in cost between different filter classes. When the calculation is made for a filter class F5 we get the following results. Table 2 Filter Class F5 Standard Concept (4-pocket filter) Optimised Concept (6-pocket filter) Number of Filters 10 10 Initial Pressure Drop Pa 51 40 Final Pressure Drop Pa (after 12 months) 118 58 Cost for Energy US $ 890 510 Cost for Filter US $ 340 500 Total Cost (Filter +Energy) US $ 1230 1020 As we can see from the calculation the total cost (optimised concept) for a filter of class F5 is 1020 US $. Upgrading from F6 to F5 will lead to an increase in costs of 730 US $ (1750-1020 US $). The major part of the cost increase depends on the energy consumption. The difference in energy consumption between an F6 filter and an F5 filter is 9800 kwh/year (490 US $) 5

Conclusions The program has been in use in our sales force for a period of one and half year. Our experiences this is that optimising the filter banks often results in substantial reduction of the filter cost. One example is Landvetter Airport. Landvetter has expanded the building surface during the last years. To get enough supply air to the new building area, the revolutions on the fans has been increased, but the filter surface was not increased. When we did calculations on the system we found that by increasing the filter surface by 50 % the filter cost could be reduced by 40 %. We found that the program could also result in big savings when the optimised bank turned out to be smaller than original one. In order to save money, they have closed many operation theatres at Borås Hospital. To those areas the supply air have been minimised. We did a calculation on a filter bank with 80 filters. The program found that the optimum number of filters was 16. Another important output from the program is highlighting the cost for different filter classes. 2500 Cost for Different Filter Classes 2000 US $ 1500 1000 500 0 F5 F6 F7 Diagram 1 Same input for the calculation as for the example As we can see from the diagram the filter cost for running F7 filters is 2,2 times more higher than for running a filter of class F5. Reference [1] Eurovent/Cecomaf, Recommendation concerning calculation of life cycle cost for air filters 6