dc.contributor.author | Sweetapple, C | |
dc.contributor.author | Fu, G | |
dc.contributor.author | Butler, D | |
dc.date.accessioned | 2016-03-01T11:43:02Z | |
dc.date.issued | 2014-05-15 | |
dc.description.abstract | This study investigates the potential of control strategy optimisation for the reduction of operational greenhouse gas emissions from wastewater treatment in a cost-effective manner, and demonstrates that significant improvements can be realised. A multi-objective evolutionary algorithm, NSGA-II, is used to derive sets of Pareto optimal operational and control parameter values for an activated sludge wastewater treatment plant, with objectives including minimisation of greenhouse gas emissions, operational costs and effluent pollutant concentrations, subject to legislative compliance. Different problem formulations are explored, to identify the most effective approach to emissions reduction, and the sets of optimal solutions enable identification of trade-offs between conflicting objectives. It is found that multi-objective optimisation can facilitate a significant reduction in greenhouse gas emissions without the need for plant redesign or modification of the control strategy layout, but there are trade-offs to consider: most importantly, if operational costs are not to be increased, reduction of greenhouse gas emissions is likely to incur an increase in effluent ammonia and total nitrogen concentrations. Design of control strategies for a high effluent quality and low costs alone is likely to result in an inadvertent increase in greenhouse gas emissions, so it is of key importance that effects on emissions are considered in control strategy development and optimisation. | en_GB |
dc.description.sponsorship | Thanks are given for the Matlab/Simulink implementation of
the BSM2 from the Department of Industrial Electrical Engineering
and Automation, Lund University, Lund, Sweden.
Christine Sweetapple gratefully acknowledges financial support
provided by the University of Exeter in the form of a
studentship. | en_GB |
dc.identifier.citation | Water Research, 2014, Vol. 55, pp. 52 - 62 | en_GB |
dc.identifier.doi | 10.1016/j.watres.2014.02.018 | |
dc.identifier.uri | http://hdl.handle.net/10871/20314 | |
dc.language.iso | en | en_GB |
dc.publisher | Elsevier | en_GB |
dc.relation.url | http://www.ncbi.nlm.nih.gov/pubmed/24602860 | en_GB |
dc.subject | Control | en_GB |
dc.subject | Greenhouse gas | en_GB |
dc.subject | Multi-objective optimisation | en_GB |
dc.subject | NSGA-II | en_GB |
dc.subject | WWTP | en_GB |
dc.subject | Carbon Dioxide | en_GB |
dc.subject | Waste Disposal, Fluid | en_GB |
dc.title | Multi-objective optimisation of wastewater treatment plant control to reduce greenhouse gas emissions. | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2016-03-01T11:43:02Z | |
dc.identifier.issn | 0043-1354 | |
exeter.place-of-publication | England | |
dc.description | Published | en_GB |
dc.description | Research Support, Non-U.S. Gov't | en_GB |
dc.description | This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.watres.2014.02.018 | en_GB |
dc.identifier.journal | Water Research | en_GB |