LAUSR

Feasible heating systems have been designed to increase the availability of open-air swimming pools in winter in subtropical climate regions. However, the approach to optimally size the main components of the system from multiple aspects is lacking. A techno-economic optimization method for swimming pool heating systems is proposed here. Minimizing the lifecycle cost of the system while ensuring the thermal comfort of the pool are considered as the optimization objectives. The volume of phase change material storage tank and the heating capacity of air-source heat pumps are selected as design variables. To improve computational efficiency, surrogate models are developed using the response surface approach, in which the dataset is generated from the simulation platform established using MATLAB and TRNSYS. Generic algorithm and non-dominated sorting genetic algorithm II are adopted to conduct single-objective and double-objective optimizations, respectively. Case studies indicate that optimal combinations for the size of main components can be identified using the proposed optimization approach. The energy and economic performance of the heating system are enhanced after optimization. The proposed techno-economic optimization method provides an instructive guideline for the optimal design of swimming pool heating systems.