Analysis of a wastewater treatment plant using fuzzy goal programming as a management tool: A case study

Analysis of a wastewater treatment plant using fuzzy goal programming as a management tool: A... Water management is currently a priority in all integrated water cycle sections when a close relation between water and energy is considered. Wastewater treatment plants are high-energy consumers and, therefore, energy reduction is necessary to improve the energy footprint and to also reduce operating costs. This research presents a combined strategy using linear mathematical programming which, in turn, employs current treatment techniques with dilution through regenerated water at the treatment plant. The strategy used a new model that was adapted to minimise exploitation costs. The strategy also obtained a global solution by considering the uncertainty of the different variables, which are included in the treatment process. This uncertainty was considered by fuzzy goal programming, which allowed water managers to optimise treatment according to energy costs, contaminant loads, and the inlet and outlet concentrations. A mathematical tool was applied to a real case study located in a township in the province of Alicante (Spain). The solution showed a 49.47% reduction in economic cost when comparing the optimised solution to the deterministic solution. This energy reduction was 803 GWh/year and the theoretical reduction of greenhouse emissions was 586.2 tCO2/year. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Cleaner Production Elsevier

Analysis of a wastewater treatment plant using fuzzy goal programming as a management tool: A case study

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Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier Ltd
ISSN
0959-6526
D.O.I.
10.1016/j.jclepro.2018.01.129
Publisher site
See Article on Publisher Site

Abstract

Water management is currently a priority in all integrated water cycle sections when a close relation between water and energy is considered. Wastewater treatment plants are high-energy consumers and, therefore, energy reduction is necessary to improve the energy footprint and to also reduce operating costs. This research presents a combined strategy using linear mathematical programming which, in turn, employs current treatment techniques with dilution through regenerated water at the treatment plant. The strategy used a new model that was adapted to minimise exploitation costs. The strategy also obtained a global solution by considering the uncertainty of the different variables, which are included in the treatment process. This uncertainty was considered by fuzzy goal programming, which allowed water managers to optimise treatment according to energy costs, contaminant loads, and the inlet and outlet concentrations. A mathematical tool was applied to a real case study located in a township in the province of Alicante (Spain). The solution showed a 49.47% reduction in economic cost when comparing the optimised solution to the deterministic solution. This energy reduction was 803 GWh/year and the theoretical reduction of greenhouse emissions was 586.2 tCO2/year.

Journal

Journal of Cleaner ProductionElsevier

Published: Apr 10, 2018

References

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