Optimum rescheduling of water networks for batch processes using a goal programming technique.

Area of Science:

• Chemical Engineering
• Environmental Engineering
• Industrial Optimization

Background:

• Batch processes in chemical industries often lack direct water reuse due to time constraints and the high cost of storage tanks.
• Efficient water management is crucial for cost-effectiveness and sustainability in industrial operations.

Purpose of the Study:

• To develop a cost-effective water network synthesis for batch processes by rescheduling water usage.
• To minimize freshwater consumption and wastewater discharge through optimized water network design.
• To reduce the number and capacity of required storage tanks.

Main Methods:

• A goal programming approach was employed to reschedule water networks in batch processes.
• A Mixed Integer Non-Linear Program (MINLP) model was developed using the Lingo optimization program.
• The model optimized multiple objectives including freshwater usage, wastewater discharge, tank requirements, stream shifting, and total network cost.

Main Results:

• Case studies demonstrated significant reductions in network cost and freshwater flowrate (e.g., 26.4% cost and 42% freshwater reduction in one case).
• The proposed method achieved cost reductions and freshwater decrease even without requiring storage tanks in certain scenarios.
• The model proved effective for both single and multi-contaminant batch water networks.

Conclusions:

• Rescheduling water networks is an effective strategy to reduce costs and environmental impact in batch processes.
• The developed MINLP model provides a robust tool for optimizing water usage and minimizing storage requirements.
• The approach offers a cost-effective solution for sustainable water management in diverse industrial settings.