Synthesis of Energy Efficient Complex Separation Networks

Abstract Separation processes account for about fifty percent of capital and operating costs including the highest energy demand in the chemical industry. The rise in energy consumption, the high cost of the fuels, and combined with the environmental impact increases the demand for energy saving separation processes such as optimal complex column networks which are estimated to achieve energy savings of up to 70%. This paper introduces a novel algorithm to create optimal complex column arrangements which encode the cost and states of global solutions with minimum user input. In the complex column networks, several combinations and internal connections increase the difficulty to optimize these processes. The proposed configuration algorithm generates all possible network configurations expressed as a continuous sequence of column section profiles and discriminates suboptimal solutions taking the column network structure as input. Simultaneously, a robust feasibility test is applied to the generated systematic network based in thermodynamic transformations called temperature collocation where the operating conditions, structure, and length of the separation network for realizing the desired product purities are not predefined. This robust hybrid algorithm combines the advantages of deterministic and stochastic search techniques. This computational approach guarantees rigorous column profiles validated with industrially accepted simulation software such as ASPEN. The capabilities will be illustrated using multicomponent realistic case studies especially quaternary systems.