Although the finite volume method and the Poppe method are
the most comprehensive methods for simulation of a cooling tower
process, these methods require considerable computational time to
converge compared to other methods such as Merkel or 3-NTU
methods. The cooling tower mathematical model to be used in this
integrated building energy simulation application must exhibit
limited complexity with acceptable accuracy as well as being
computationally efficient. Moreover, it must be capable of being
used in simulation analysis based on 5 min intervals for periods of
up to one year. Kloppers and Kroger note that by constraining
certain assumptions and applying other corrections to the Merkel
or 3-NTU methods, results closer to the more rigorous Poppe
method [15,17] are possible. It is proposed that by applying the
improved methods, then not only the computational requirements
time decrease but also increased accuracy of results are possible. In
the context of the current research, the conflicting constraints of
computational efficiency versus simulation accuracy is critical, as
the proposed mathematical model must not only be capable of
being integrated with a contemporary building energy simulation
package (e.g., EnergyPlus, ESPr or TRNSYS), but also must provide
an integrated platform for detailed whole building analysis on a
seasonal basis.