(249s) A Multi Criteria Design Approach Regarding the Economic Impact of Heat Recovery on Chemical Processes

Energy efficiency is a mayor global concern of latest research as well as industrial application. Limited fossil fuels lead to constantly rising energy costs. Tightening environmental regulations necessitate the reduction of CO₂-emissions and waste water generation. All these issues underline the importance of the efficient use of energy and resources likewise. In this context process integration and optimization are powerful approaches that allow process industries to increase their effectivity and profitability.

In order to advance the state-of-the-art technology and accelerate a move to low carbon manufacturing industries several research projects were funded by the European Commission via the seventh framework program. One of those projects, namely EFENIS, aims for a fundamentally improved process integration by applying novel methods of total site targeting, heat recovery, intensified heat transfer, CO₂ and waste water management. The EFENIS project is composed of 17 partners including 10 academic institutions and 7 industrial companies.

Within EFENIS an efficient and sustainable workflow for assuring a long term validity of total site analysis results will be developed and implemented into a decision supporting software tool. This Energy Integration Manager has to be based on sophisticated interfaces between state-of-the-art process simulation, process optimization and data management. The operability of this software tool will be tested with datasets and process models of actual operating industrial plants.

Utilizing the above mentioned software solutions for process simulation enable the parallelization of process integration and process optimization as a simultaneous design step. This concept is in contrast to the traditional workflow of sequentially doing the heat integration after finishing the process design. In terms of heat integration, the design of a comprehensive heat exchanger network will be the focus. In terms of process optimization, the optimal parameterization of relevant process variables is the core objective.

In the presentation a concept of a genetic algorithm for process parameter optimization using a multi-criteria solution approach is shown. The impact of process parameters on heat integration measures will be presented via suitable pareto illustration. As a case study a process for the synthesis of dimethyl ether from methanol is used.