WATER MANAGEMENT IN CHEMICAL PROCESS INDUSTRIES

Abstract

Water is an important natural resource. utilized in almost all sectors like agriculture, industrial uses, domestic purposes, etc. Population growth accompanied with industrialization lead to an increasing demand for water. For example in India, the industrial sector uses about 13% of the total freshwater in the country. Water demand for industrial use was predicted to grow at a rate of 4.2% per year, rising from 67 billion cubic metres in 1999 to 228 billion cubic metres by 2025 [35]. Water resources being limited and accounting the risen demand for water, it can be considered as a renewable source only if consumed and disposed carefully. The increasing cost of fresh water and stringent environmental regulations are forcing industries to minimize water consumption and waste water generation. Simultaneous minimization of fresh water consumption and waste water generation can be achieved by reusing outlet streams with lower contaminant concentration. identification of scope for reuse can be done using Pinch technology or mathematical modeling. The present works involves minimizing water consumption in industrial case studies using both Pinch technology and mathematical modeling. Four case studies are considered from open literature and solved using three software such as WaterPinch. Aspen Water and GAMS. WaterPinch uses the principles of Pinch technology for minimizing water consumption whereas Aspen Water and GAMS use mathematical modeling approach. A program based on superstructure model is formulated in GAMS considering water cost and piping cost of the network in objective function. It is solved using MINLP solver. The results obtained using these three software are compared and discussed. Case study-i is a multi contaminant problem of typical Indian starch industry, which is solved using Aspen Water, WaterPinch and GAMS. The results obtained using the three software are compared and observed that GAMS shows best results amongst the three. Reduction in consumption of DM water and fresh water is 29.41% and 70 %, respectively, and waste water is reduced by 71 % using GAMS. Economic analysis of the results shows savings of Rs. 126.3 lakhs per year is obtained using GAMS. Results of the present work are compared with that of published work and found that reduction in DM water is same in both the cases. Whereas, fresh water and waste water reductions are 1 .3% more and 4.8% less in present work compared to the published xii work. Though difference in water consumption is less the modified network found in present work is simpler compared to that obtained in published work. - Case studies 2, 3 are single contaminant cases without water loss. Final flow rates of fresh water and waste water obtained using three software are same. Reduction in fresh water consumption and waste water generation for Case study-2 is 33.9% each found through all the three software. Similarly for case study-3 reduction in fresh water and waste water flow rates is 47.5 % each. Modified networks found through these software are different and thus different piping cost is involved in these. It is observed for case studies 2 and 3 that modified network obtained using GAMS has least piping cost amongst those obtained using Aspen Water, WaterPinch and GAMS. It shows that GAMS gives simpler network in comparison to that found through other two software. Saving of Rs. 874.5 lakhs and Rs. 412.3 lakhs is predicted in case study 2 and 3 respectively using GAMS. Case study4 is a single contaminant case, which involves water loss from the cooling towers in the form of evaporation loss. This is solved using Aspen Water, WaterPinch and GAMS. The optimized flow rates of fresh water and waste water are least in the result obtained using WaterPinch. Aspen Water and GAMS results show 0.028% and 0.013% more fresh water and waste water flow rates compared to WaterPinch. As observed in Case studies 1, 2 and 3 simpler network is obtained using GAMS because of the inclusion of piping cost in objective function. Reduction in fresh water flow rates using GAMS is 17.3 %. Saving of Rs. 113.2 lakhs is obtained due to network modifications and reduction in fresh water consumption and waste water generation. From the case studies considered in present work it can be concluded that best results are obtained using GAMS i.e. inclusion of piping cost in the objective function along with water costs gives better and simpler networks.