Modelagem matemática e avaliação econômica de uma nova abordagem para concentrar vinhaça de cana-de-açúcar: otimização da eficiência exergética, área de troca térmica e performance térmica utilizando algoritmo genético e TOPSIS

Abstract

Historically, multi-stage flash distillation (MSF) was the leading process for potable water production. However, by 2019, MSF had largely given way to emerging technologies. Nonetheless, it remains promising from an energy and exergetic standpoint due to its reliance on low-temperature heat sources, making it particularly attractive when cogeneration is feasible. The sugar-energy industry, in contrast, consumes about 0.7 m³ of water per metric ton of sugarcane processed. Considering the rising environmental, social, and corporate governance (ESG) concerns, there is a clear trend toward reducing water usage in this sector. Accordingly, this study seeks to determine the optimal configuration for integrating a once-through MSF system with a sugarcane processing facility. The proposed system aims to recover water from vinasse, a byproduct of the ethanol production, by employing steam generated in the sugarcane juice concentration process as its energy source. The process was modeled in MATLAB using real data from a Brazilian plant. Optimization was achieved using the genetic algorithm with exergy efficiency, total heat exchange area and thermal performance ratio as the objectives. Subsequently, the order preference by similarity to ideal solution (TOPSIS) method was applied to select the best alternative from the Pareto Front. The results indicate that the optimal configuration involves 58 flashing stages, yielding distilled water at a specific cost of 0.49 US$/m³ and producing a total of 49,649 m³ of water per harvest.