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Abstract
A new simulation-based strategy for optimal design of a renewable cooling and heating system that includes a desiccant wheel, a photovoltaic/thermal-solar air collector (PV/T-SAC) and a thermal storage unit using phase change material (PCM) is presented in this study. The strategy is formulated by integrating an integer-based genetic algorithm (IGA) with the response surface method (RSM), in order to tackle the system nonlinearity with manageable computational costs. The PV/T-SAC is used to provide thermal energy for desiccant wheel regeneration and space heating in cooling and heating seasons, respectively. The thermal storage unit is used to mitigate the intermittency of solar energy. The twenty-year system life cycle cost (LCC) is employed as the optimisation objective. The influence of four economic factors, i.e. PV/T price, PCM price, electricity purchase price and electricity sale price on the optimal design and LCC of this system is also investigated. The resul ....

Integer Based Genetic Algorithm , Life Cycle Analysis , Optimal Design , Enewable Cooling And Heating , Esponse Surface Method , Thermal Energy Storage ,