A Methodology for Best Pathway Identification of Waste Recovery
Résumé
Industry has always looked for maximizing on-site synergies using energy and mass integration methods, rather independently. Many studies were conducted to assess the economical feasibility of heating networks based on industrial heat recovery and similarly for water reuse and recycling. However, considering the component valorization in its original form, corollary implies missing the reuse opportunities of the component in another form. The conversion brings the possibility of turning the non-usable waste into another usable energy or material through chemical processes, and allows its reinsertion in the system. Hence the inclusion of these processes enables exploring new paths for the recovery of waste streams and bridging the gap between the two integration methods. We introduce a methodology which couples Energy and Mass integration techniques through conversion processes, in the aim of finding the best valorization pathway of waste streams in a local context. In this methodology, the valorization pathways are driven by the local demand leading to the synergies maximization. Indeed modeling the local demand profile will indicate the feasible pathways through identifying the needs. The best pathway will hence be determined through detailed economic evaluation. The proposed methodology is demonstrated on a case study considering a large industrial site where waste wood valorization is assessed. Since waste wood has multiple valorization pathways by its conversion to energy or to another high added value material, the proposed methodology will serve as a tool for the identification of the best economic valorization solution. Each of these conversionpathwaysismodeledusingModelicametalanguageandvalidatedwithliteratureresults. Inthiscasestudy,wastewoodvalorizationthroughheatandpowergeneration,hydrogenormethane generationischallengedinamulti-objectivesoptimization. Foreachpossiblewastewoodconversion system, the obtained superstructure is analyzed through Energy and Mass integration methods for each set of the objectives.