The optimal design and operation of exible energy polygeneration systems using coal and biomass to coproduce power, liquid fuels, and chemicals is investigated. This problem is formulated as a multi-period optimization problem, which is a potentially large-scale nonconvex mixed-integer nonlinear program MINLP and cannot be solved to global optimality by state-of-the-art global optimization solvers, such as BARON, within a reasonable time. A duality-based decomposition method, which can exploit the special structure of this problem, is applied. In this work, the decomposition method is enhanced by the introduction of additional dual information for faster convergence. The enhanced decomposition algorithm guarantees to find an ε-optimal solution in a finite time. The case study results show that the enhanced decomposition algorithm achieves much faster convergence than both BARON and the original decomposition algorithm, and it solved the large-scale nonconvex MINLPs to ε-optimality in practical times.