I have written three posts & one audit report on this topic of cooling towers calculations. Recently one of our reader suggested that I should go for posting an article on how to identify different components of cooling tower performance. Therefore, I decided to provide the details on how to establish different factors contributing to the inefficiencies in case of a cooling tower.

The article & report I have earlier published are here.

Factors affecting cooling tower & how to find out the impact of each of them.

The impact of return water temperature is that the cooling approach must change by ~50% of the difference in the design & actual return water temperature. For example: If a tower is designed for 4°C approach for the cooling of water from 44°C to 34°C and actual return water temperature is 42°C then you must get an approach of 3°C instead of 4°C. The range of cooling will be 9°C against design value of 10°C. Thus, if your return water temperature is 42°C against design value of 44°C and you are getting design approach of 4°C that means your cooling tower is operating inefficiently.

Similarly, In this case, the approach of cooling will go up by ~50% of the difference between design & actual wet bulb, if wet bulb is lower than design value. However, total range of cooling will also increase in this case by ~50% of the difference in actual & design wet bulb i.e. 44°C to 33°C means range of cooling will increase from 10°C to 11°C.

Yes, one should not infer from these two examples that the thumb rules expressed here are valid for any changes in the temperatures. Instead, it is always governed by the equilibrium conditions & for larger changes one should go for proper evaluation procedure as described later in this article.

Cooling towers are normally supplied in standard modules called tower cells. Therefore, the cooling water is distributed equally on each cell in parallel configuration. However, in actual operation it deviates from what it should be (Average water flow/cell). This causes for example 80% water on one cell & total water flow being the same it will be 120% on the other. Even the same cell might have different water loading on both sides of distribution deck. This much deviation may result in ~5-10% rise in cooling approach.

Similarly, the imbalance in air loading in each side of every cell may cause 1.5 times more negative impact as compared to effect of disturbed water loading. Thus, 20% deviation in air distribution may cause ~10-15% rise in cooling approach.

By now it is clear that operators has to regularly monitor the performance of their cooling tower especially at different loads & at different ambient conditions. More appropriately, the comparison of actual approach with the design approach is not a good & actual indicator of its performance

For the identification of actual differences in the performance calculation of a cooling tower & for identifying the impact of each factor, NTU calculation method is the most useful & recommended one based on my experience.

As Promised earlier in the performance calculation - II, I am giving here the method for using this NTU for prediction of performance.

Start with how much is approximate difference in inlet & exit temperature from cooling tower & divide them in equal parts with say an increment of 0.2°C or so.

Start from first row & column A with some approx t temperature & make diff in column G as zero. (This all is explained in above linked article on this Blog)

Since all other rows are linked with same increment of 0.2 till last row, finally you should get your inlet temperature in last row & column A. If it is less or more change it in first row to get same.

With each change all rows in column G should have zero value as difference.

Once you get all zero in column G and inlet temperature in last row of Column A, the first row in column A should give you the exit temperature, but wait.

Now you need to check the sum of NTUL in column K or NTUG in column N. This value should be equal to your design NTU. (Yes, design NTU is also found in similar manner)

Example, so if you want to evaluate the impact of change in wet bulb compared to design, first consider all data of design & find out NTUG in design.

Now change wet bulb & you will see that ha in column F is changed, so you need to change t in column A to make difference in column G = 0.

Finally you will find the changed temperature figure at the exit by keeping NTUG same.

The article & report I have earlier published are here.

- Cooling Towers: Not The Coolest One
- Cooling Towers - Performance Calculation - I
- Cooling Towers - Performance Calculation - II

Factors affecting cooling tower & how to find out the impact of each of them.

**Effect of Water Temperature**The impact of return water temperature is that the cooling approach must change by ~50% of the difference in the design & actual return water temperature. For example: If a tower is designed for 4°C approach for the cooling of water from 44°C to 34°C and actual return water temperature is 42°C then you must get an approach of 3°C instead of 4°C. The range of cooling will be 9°C against design value of 10°C. Thus, if your return water temperature is 42°C against design value of 44°C and you are getting design approach of 4°C that means your cooling tower is operating inefficiently.

**Effect of Wet Bulb**Similarly, In this case, the approach of cooling will go up by ~50% of the difference between design & actual wet bulb, if wet bulb is lower than design value. However, total range of cooling will also increase in this case by ~50% of the difference in actual & design wet bulb i.e. 44°C to 33°C means range of cooling will increase from 10°C to 11°C.

Yes, one should not infer from these two examples that the thumb rules expressed here are valid for any changes in the temperatures. Instead, it is always governed by the equilibrium conditions & for larger changes one should go for proper evaluation procedure as described later in this article.

**Effect of Water Loading**Cooling towers are normally supplied in standard modules called tower cells. Therefore, the cooling water is distributed equally on each cell in parallel configuration. However, in actual operation it deviates from what it should be (Average water flow/cell). This causes for example 80% water on one cell & total water flow being the same it will be 120% on the other. Even the same cell might have different water loading on both sides of distribution deck. This much deviation may result in ~5-10% rise in cooling approach.

**Effect of Air Distribution**Similarly, the imbalance in air loading in each side of every cell may cause 1.5 times more negative impact as compared to effect of disturbed water loading. Thus, 20% deviation in air distribution may cause ~10-15% rise in cooling approach.

**Effect of Air Short Circuiting**By now it is clear that operators has to regularly monitor the performance of their cooling tower especially at different loads & at different ambient conditions. More appropriately, the comparison of actual approach with the design approach is not a good & actual indicator of its performance

**NTU Calculation**For the identification of actual differences in the performance calculation of a cooling tower & for identifying the impact of each factor, NTU calculation method is the most useful & recommended one based on my experience.

As Promised earlier in the performance calculation - II, I am giving here the method for using this NTU for prediction of performance.

**Step - 1**Start with how much is approximate difference in inlet & exit temperature from cooling tower & divide them in equal parts with say an increment of 0.2°C or so.

Start from first row & column A with some approx t temperature & make diff in column G as zero. (This all is explained in above linked article on this Blog)

Since all other rows are linked with same increment of 0.2 till last row, finally you should get your inlet temperature in last row & column A. If it is less or more change it in first row to get same.

With each change all rows in column G should have zero value as difference.

**Step - 2**Once you get all zero in column G and inlet temperature in last row of Column A, the first row in column A should give you the exit temperature, but wait.

Now you need to check the sum of NTUL in column K or NTUG in column N. This value should be equal to your design NTU. (Yes, design NTU is also found in similar manner)

Example, so if you want to evaluate the impact of change in wet bulb compared to design, first consider all data of design & find out NTUG in design.

Now change wet bulb & you will see that ha in column F is changed, so you need to change t in column A to make difference in column G = 0.

Finally you will find the changed temperature figure at the exit by keeping NTUG same.

## 3 comments:

SONA COOLING TOWERS is into manufacturing of FRP Cooling Towers. Since the inception, we constantly provide new solutions and applications in recalculating cooling tower systems to meet the requirement of rapidly advancing technology. SONA COOLING TOWERS highest quality products have been designed to provide unique solution with significant saving in energy consumption and cost associated with downtime for schedule maintenance.

Cooling Tower Supplier

FRP cooling towers - review our product catalog of cooling towers, which includes bottle shape cooling towers, FRP square cooling towers, rectangular towers etc.

Contact Us:

+91-9312466234

Address:T-507/14, IInd Floor, Motia Khan, P.Ganj, New Delhi-110055

The generic term " cooling tower " is used to describe both direct (open circuit) and indirect (closed circuit) heat rejection equipment.

Post a Comment