Multi-objective optimization and selection of hybrid combined cooling, heating and power systems considering operational flexibility

Abstract This paper proposes a multi-objective optimization model integrated with operational flexibility to optimize a hybrid combined cooling, heating and power (CCHP) system. The operational flexibility of the hybrid CCHP system is proposed and expressed by the combined indicators to show the capacity to resist performance degradation because of externally variable conditions to increase energy saving and cost saving, to reduce carbon dioxide emissions, and to enhance renewability, the ability to adjust heat and electricity, and the grid integration level. A Pareto frontier of solutions considering a larger operational flexibility with less performance degradation is obtained in genetic algorithm. The use of a multi-criteria decision making method combined with an entropy weighting method is employed to quantitatively evaluate the composite sustainability index of the Pareto schemes and choose the optimal hybrid CCHP option with the best integrated performance. The results of a case study that considers operational flexibility and optimization indicated that the potential adjustable ability was increased by 438.9%, and the grid integration level and net interaction with the grid were decreased by 3.6%. However, the increase in flexibility reduces the energetic, economic and environmental benefits achieved by the CCHP system by 5.1%, 56.4% and 3.0%, respectively.