Mathematical modelling of simultaneous water and energy minimisation considering water management hierarchy options
Water and energy are closely interlinked together. The goal to reduce water and energy simultaneously has been a growing research. However, previous studies only consider maximising water reuse and, in some cases, also include water regeneration. This study aims to develop a mathematical model to de...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/85919/1/LilySyafikahMansorMSChE2018.pdf |
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| Summary: | Water and energy are closely interlinked together. The goal to reduce water and energy simultaneously has been a growing research. However, previous studies only consider maximising water reuse and, in some cases, also include water regeneration. This study aims to develop a mathematical model to design water and energy network that further reduces the water consumption, considering the whole water management hierarchy (WMH) schemes. This includes elimination, reduction, reuse, outsourcing and regeneration. Two steps solution is proposed, which involves solving two MINLP models. First, water and energy minimisation network considering WMH schemes and direct heat transfer is designed. The obtained network is then improved by inclusion of indirect heat integration to minimise the objective cost function. Two cases of thermal data extraction are studied for heat integration, Case A extracts individual streams based on supply and targeted temperature, whereas Case B extracts stream after mixer based on mixer temperature and targeted temperature. Streams which temperature load is satisfied in direct heat transfer were excluded for heat integration. The proposed method has been tested with literature case study. The implementation of all possible WMH scheme yields a lower freshwater consumption and wastewater generation. The model selected 35% and 15% of reduction for demand 3 and demand 1 respectively. Case A yields a lower total operating cost but slightly higher investment cost compared to Case B. Case B result in a simpler heat exchanger network, but degradation of the potential energy causes more heating and cooling. Case A is chosen as the optimal network and exhibits 13% reduction of the total cost compared to the literature case study. |
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