The Simulation of Swimming Pools in T*SOL

In T*SOL Pro 5.5 swimming pool systems (indoor and outdoor) are also simulated. An increasing number of swimming pool operators are adding solar devices to their heating systems. T*SOL helps planners calculate the amount of energy that will be saved by such combinations.

T*SOL's previous swimming pool simulation model has been redesigned and improved from the ground up.

  • Different calculations for private and public pools

  • Calculation based on number of hours of use

  • Calculation includes time during which the pool lies in shadow

  • New algorithms for the calculation of insulation gains with different methods for diffuse and direct sunlight

  • More precise calculation of the effect of clouds

  • New algorithms for calculating evaporation and convection

  • New thermodynamic model for pool cover

Improved algorithms have been verified with real measurement data  [1] (see image 1).

Image 1: Measured and simulated pool temperature (54 days)
temperature change, measured values, previous model, new model

As can be seen in Image 1, there has been clear improvement in the quality of the simulation. The new model's RMSD [2] of 0.48 °C is far under the 1.38 °C of the previous model


Simulation model

The mid pool water temperature is taken from local climate data, operational parameters and environmental conditions. Heat transport currents are also included in the calculation (see Image 2).

Image 2: Energy balance of swimming pool
global irradiance, wind, humidity, air temperature, sunlight absorption, evaporation, radiation loss, convection, energy input by means of space heating or solar device, loss of fresh water, heat conduction, ground temperature.

The calculation of the individual heat transport mechanisms has been reworked based on new publications on swimming pools. A detailed description can be found here:

By balancing the heat flow Q ̇_i, the pool water temperature Tw(t) is determined  at intervals of up to six minutes. The model assumes that the temperature is constant in the entire pool (single node model):

(dT_w)/dt=(∑Q ̇_i )/(c_pw∙ρ_w∙V_w  )    

T_w: temperature of water in K

Q_i: amount of heat transport in J

c_pw: specific heat capacity of water in J/(kg K)

ρ_w: density of water in kg/m³

V_w: volume of pool in m³


Examples of simulation results

The individual energy transport mechanisms and variables can be entered into programs like Excel or directly entered into T*SOL graphically:

Image 3: Water temperatures of a newly filled pool in the first week of May (T*SOL graphic)


Image 4: Water temperatures of a newly filled pool with and without a solar system from mid-May to early June (EXCEL graphic)

Energy efficiency measures such as use of a cover or the integration of a solar device can be analyzed by means of a comparison of simulation results. In Image 5 the heat energy use and solar energy contribution of a fictional public pool are shown with different system configurations.


Image 5: Heat energy consumption and solar energy contribution for different potential systems of a fictional pool with a target water temperature of 23 °C.

We see that the simple use of a cover can significantly decrease energy consumption. In this example the savings are about 47%. The effects of a cover vary depending on climatic conditions and cover times. In this example the solar system contributes additional savings of about 21 %.

An enhanced effect is achieved with the simultaneous use of a solar device and a cover. The average pool temperature in the example above is increased from the target temperature of 23 °C to 24 °C. Here one can decide whether the temperature increase is desirable or whether for economic reasons a smaller system would be more suitable.

Depending on the location and use parameters climatic differences can have a significant effect on the results. With the improved simulation model the effects of environmental conditions are better illustrated and the simulation serves as a useful tool in answering questions about energy use and swimming pools.


[1] Data based on: Woolley, J., Harrington, C., Modera, M.: Swimming pools as heat sinks for air  conditioners : Model design and experimental validation for natural thermal behavior of the pool.
In: Building  and Environment (2011), Vol. 46, S. 187-195

[2] Engl. Root Mean Square Deviation, a statistical method for determining the variation of calculated values


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