Robust Multi-Objective Optimization With Life Cycle Assessment Of Hybrid Solar Combined Cooling, Heating And Power System

Hybridization of solar energy technologies results in varieties of inherent characteristics of natural gas combined cooling, heating and power (CCHP) system. This work aims to propose a life cycle assessment-based robust multi objective optimization model of hybrid solar-assisted CCHP system, which is driven by the complementarities of photovoltaic/thermal collectors and gas turbine. The environmental impact potentials including global warming, respiratory effect and acidification of hybrid system are assessed according to life cycle energy and emission inventory analysis. The optimal plan of hybrid system, using nondominated sorting genetic algorithm II, is implemented to minimize these environmental impacts, in which the robustness is incorporated as part of the search process of genetic algorithm. The sensitivity analysis of candidate Pareto solutions by transferring to linear programming sub-problem drives to the selection of new solutions with robustness requirements. A case study in a hotel building was presented to demonstrate the proposed optimization method. The key uncertain factors on optimization and system performances are discussed. The comparisons of partially and fully covered photovoltaic/thermal collectors indicate that the partially covered collectors lower the impacts of respiratory effect and acidification by 28.4% and 6.7%, respectively, by optimizing system configurations and energy compositions, and the optimum partially covered collectors with CCHP system is more cost-effective and feasible.