Multi-objective optimization of a combined cooling, heating and power system driven by solar energy

This paper presented a multi-objective optimization of a combined cooling, heating and power system (CCHP) driven by solar energy. The flat-plate solar collector was employed to collect the solar radiation and to transform it into thermal energy. The thermal storage unit was installed to storage the thermal energy collected by the collectors to ensure a continuous energy supplement when solar energy was weak or insufficient. The CCHP system combined an organic Rankine cycle with an ejector refrigeration cycle to yield electricity and cold capacity to users. In order to conduct the optimization, the mathematical model of the solar-powered CCHP system was established. Owing to the limitation of the single-objective optimization, the multi-objective optimization of the system was carried out. Four key parameters, namely turbine inlet temperature, turbine inlet pressure, condensation temperature and pinch temperature difference in vapor generator, were selected as the decision variables to examine the performance of the overall system. Two objective functions, namely the average useful output and the total heat transfer area, were selected to maximize the average useful output and to minimize the total heat transfer area under the given conditions. NSGA-II (Non-dominated Sort Genetic Algorithm-II) was employed to achieve the final solutions in the multi-objective optimization of the system operating in three modes, namely power mode, combined heat and power (CHP) mode, and combined cooling and power (CCP) mode. For the power mode, the optimum average useful output and total heat transfer area were 6.40 kW and 46.16 m2. For the CCP mode, the optimum average useful output and total heat transfer area were 5.84 kW and 58.74 m2. For the CHP mode, the optimum average useful output and total heat transfer area were 8.89 kW and 38.78 m2. Results also indicated that the multi-objective optimization provided a more comprehensive solution set so that the optimum performance could be achieved according to different requirements for system.