Comprehensive optimization of combined cooling, heating, and power hybrid renewable multienergy system based on enhanced implementation feasibility

Abstract

To promote the implementation of optimization schemes, a comprehensive optimization approach is proposed with the aim of enhancing the implementation feasibility of a combined cooling, heating, and power (CCHP) system based on optimization solutions. The proposed method not only focuses on optimizing objective functions but also considers the optimization characteristics of decision variables. A computational model for a multienergy CCHP hybrid system incorporating solar, biomass, and geothermal energy is established. The optimization objective functions include the net present value, fossil energy consumption, and carbon dioxide emissions. The objective function results show that the HV values of the original algorithm and the jointly improved algorithm differ by 4.4%, indicating that they have similar performance characteristics. Regarding decision variables, the results show that the standard deviations of the decision variable deviations increase by 42.2%. In addition, the Solow–Polasky diversity measure increases by 21.3%. The improved algorithm presented in this paper significantly enhances the feasibility and diversity of system configurations (decision variables) while minimally impacting the objective functions. Further simplification of the decision variables in the optimization plan provides simplified optimization solutions for construction and operational maintenance. Moreover, the standardization of decision variables facilitates enhanced coordination between construction teams and equipment suppliers.