This work proposes a cascade coupling system to recover low-grade waste heat. The hybrid system performs well in hot summer and cold winter areas of China. The economy, energy, and exergy analysis and multiobjective optimizations are conducted. Nondominated sorting genetic algorithm II is applied to realize the optimization process because of the contradiction between the three objective functions. The Pareto solutions are obtained, and the relationships between two different objectives are analyzed. The final optimal solutions are determined by the technique for order preference by similarity to an ideal solution method and the Shannon entropy method. Four schemes aiming at the maximum coefficient of performance (scheme 1), minimum total annual cost (scheme 2), minimum total exergy destruction (scheme 3), and multiobjective optimization (scheme 4) are studied. The results show that the minimum values of the total annual cost and the total exergy destruction are 57.73 × 10 4 $ and 336.91 kW, respectively. The maximum coefficient of performance is 0.61. The multiobjective optimization solutions achieve a 4.12% higher value than the minimum coefficient of performance, while the total annual cost and the total exergy destruction of solutions are 1.86 and 0.58%, respectively, lower than the maximum values. This work presents a deeper dissection and a multiobjective optimization of the cascade system and provides guidance for the development of low-grade waste heat recovery technologies.