Robust Optimization Application of Cchp System Planning Based on Typical Day Selection: Combining 3e (Energy, Environmental, Economy) Analysis and Global Sensitivity Analysis

The efficient design of combined cooling, heating, and power (CCHP) systems is influenced by many uncertain factors. However, many current studies have not fully considered uncertainty, and solutions obtained in extreme cases are not feasible. In this regard, based on the k-means method, the typical day method is used to generate typical days for the whole year, and the CCHP system planning of a hospital in North China is modeled as linear programming with energy; the objective is to conduct energy, environmental and economic (3E) analysis. The optimal robust optimization scheme with different degrees of conservatism was obtained by combining a two-stage global sensitivity analysis and a robust optimization framework. Based on the results of deterministic modeling research, considering the uncertainty of the system, through two-stage global sensitivity analysis, it was found that the purchase price has the most significant impact on the comprehensive indicators. The extensive index corresponding to the optimal configuration scheme under deterministic conditions is 28.17%, and the comprehensive index corresponding to the robust optimization optimal configuration scheme is 24.70%, a decrease of 3.47%, but significantly improving the robustness of the system. Finally, this result can provide a reference for planning a hospital's comprehensive energy systems.