To maximize the energy performance and economic benefits of solar water heating (SWH) systems, the installation and operation-related design variables as well as those related to capacity must be optimized. This paper presents a novel design method for simultaneously optimizing the various design variables of an indirect forced-circulation SWH system that is based on the life cycle cost and uses a genetic algorithm. The effectiveness of the proposed method is assessed by evaluating the long-term performance corresponding to four cases, which are optimized using different annual solar fractions and sets of the design variables. When the installation and operation-related design variables were taken into consideration, it resulted in an efficient and economic design and an extra cost reduction of 3.2%–6.1% over when only the capacity-related design variables were considered. In addition, the results of parametric studies show that the slope and mass flow rate of the collector have a significant impact on the energy and economic performances of SWH systems. In contrast, the mass flow rate in the secondary circuit and the differences in the temperatures of the upper and lower dead bands of the differential controller have a smaller impact.
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