Abstract: To meet the demand for large-range load tracking and dynamic energy efficiency improvement in the micro gas turbine-LiBr double effect absorption refrigerating machine combined cooling, heating and power system (MGT-LiBr CCHP), a multi-objective nonlinear economic predictive control method (MON-EMPC) based on the Utopian point tracking framework is proposed. First, the paper analyzes the nonlinear characteristics of operation process based on the MGT-LiBr CCHP mechanistic model and constructs an artificial neural network as predictive model describing the nonlinearity of the MGT-LiBr CCHP. Then, according to the formula of the exergy efficiency, the key factors affecting the exergy efficiency are analyzed, and the multi-objective optimal economic prediction control problem reflecting the load tracking and dynamic energy efficiency is constructed. Finally, the proposed multi-objective nonlinear economic prediction control algorithm is validated by simulation, which shows the algorithm can improve dynamic energy efficiency while satisfying the tracking accuracy of multiple loads in a wide range of variable working conditions.