Abstract:
Solar water heating systems (SWHS) have fast become a suitable alternative to conventional
water heating systems due to growing energy demands. A SWHS generally consists of a solar
collector (which is used to convert solar radiation to heat), a water storage tank, and a flow
control device such as a pump in the case of forced circulation SWHS. Extensive research
and analysis on the operation and performance of these systems has been conducted, and
results show that optimal flow control is an important factor that can be used to improve the
performance and efficiency of SWHS.
This study focuses on pump flow rate optimization for forced circulation SWHS with pipes.
The system analyzed consists of an array of flat plate solar collectors, two storage tanks (one
for the circulation fluid and one for the water), a heat exchanger, two pumps, and connecting
pipes which are considered as one of the components of the SWHS so as to account for their
thermal effects. The proposed model is developed using mainly the first and second laws of
thermodynamics. The model is used to maximize the difference between the energy extracted
from the solar collector and the combined sum of the energy extracted by the heat exchanger
and corresponding energies used by the pumps in the primary and secondary loops. The
objective function maximizes the overall system energy gain whilst minimizing the sum of the energy extracted by the heat exchanger and energy used by the corresponding pumps
in the secondary loop to conserve the stored energy and meet the user requirement of water
tank temperatures.
The model is solved using the fmincon solver in MATLAB’s optimization toolbox. When
compared to other flow control techniques, in particular the most suitable energy efficient
control strategy, the results of this study show a significant increase in the system’s overall
energy gain. The results also illustrate the effects of system pipe thermal losses for the
different control strategies, hence highlighting the importance of developing a model that
takes such losses into account so as to improve the overall accuracy of the model.
