The continuous shortage of traditional energy resources combined with the increment in global warming is the main incentive beyond the deployment of solar energy resources in various applications. One of the most ambitious solar energy applications is the utilization of solar water heating systems (SWHS) in domestic applications since 70% of the consumed energy in the residential segment is utilized for space heating and appliances in cold climates. However, the proper effective deployment and assessment of the SWHS are directly by limited by the high capital cost and its compromise with the level of system effectiveness. Therefore, several simple techniques were established to estimate the long-term performance of SWHS, such as φ-chart and F-chart. These methods have several limitations that include the fully mixed assumption for the water storage tank, and subsequently, the collector inlet temperature is overestimated. In addition, these methods are suffering from the uncertainty associated with the metrological data due to the averaging. Over the last decades, several researchers developed simulation software with a user-friendly interface for evaluating the performance of various types of SWHS such as EnergyPlus, TRNSYS, SolDesigner, etc. These softwares provide simulation models which are ranged from simple to very detailed models based on the user requirement. However, these softwares are highly computationally expensive. Therefore, in the present study, the design of experiments (DOE) methodology is employed to statistically model and optimize the thermal performance of a forced circulation solar water heating system (FSWHS) with various budget constraints using a small number of simulation trials. The simulation trails are implemented using a model developed in TRNSYS 17 software, and climate conditions of Cairo, Egypt. A sequential approach is used to obtain the optimum system configuration with respect to the budget constraint. The definitive screening design is first utilized to eliminate the insignificant factors and investigate the effect of the quadratic terms. Then, the Box-Behnken design (BBD) is used for developing mathematical models based on multiple regression analysis. Finally, the optimization problem is formulated and solved using the desirability function. The developed mathematical models for the thermal performance responses showed a good agreement with the results obtained in TRNSYS for various budget constraints. This agreement proved the ability of the mathematical models to predict the performance of FSWHS precisely. Furthermore, the optimization methodology can be applied for various types of solar water heating systems and different renewable energy applications in order to assist different stakeholders from diverse backgrounds to participate in the early design stages.


Application of Response Surface Model for Sizing Solar Thermal Energy System for Residential Scale During the Early Design Stages

Division / Sponsor:
Advanced Energy Systems Division (AESD) & Solar Energy Division (SED)

Paper Proceedings: https://asmedigitalcollection.asme.org/ES/ES2020/volume/83631

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