A novel framework for multi-objective techno-econo-environmental optimization applied to a formaldehyde production process with energy recovery

The global demand for formaldehyde is projected to grow by 52% before the year 2030, reaching 70.8 Mt/year. Although there have been several prior publications regarding formaldehyde production, none have suggested automated frameworks aimed at optimizing this process to reduce its environmental impact. Furthermore, the incorporation of heat recovery systems, specifically the application of organic Rankine cycles (ORC), into this process to mitigate environmental and economic impacts has yet to be explored. To address these gaps, in this work an innovative framework is proposed for multi-objective optimization of the methanol-to-formaldehyde process with the integration of a genetic algorithm. The framework was applied for systematic minimization of the global warming impact potential (GWP) and total annual costs (TAC) while maximizing formaldehyde production. In addition to a base case without ORC implementation, three cases with different types of ORCs were designed and assessed. According to the obtained results, the optimized base case would achieve 18.7% increase in the formaldehyde production rate, 11.3% reduction in TAC and 29.0% reduction in GWP compared to the non-optimized one. Furthermore, optimized ORC integration would lead to reducing the carbon footprint of the optimized base case by 5.4%. At formaldehyde plant capacities higher than 40 kt/year, ORC installation would improve both the environmental and economic performance of the plant. • A new framework for multicriteria optimization of formaldehyde plants was proposed. • Minimized costs and environmental impacts with maximized throughput. • Achieved 18.7% higher formaldehyde output with reduced cost and carbon footprint. • Pareto-optimal solutions for production, costs, and emissions were reported. • ORC integration led to 5.4% saving in carbon footprint vs. optimized base case.