Optimising sequencing batch reactor operation cycle planning using evolutionary algorithm

The objective of this research was to optimise the operation cycle of the Sequencing Batch Reactor (SBR). Appropriate time balances of aerobic to anaerobic phases, as well as a set dissolved oxygen level are the key to ensuring the quality of effluent from the wastewater treatment process. The proposal to solve this optimisation problem was based on multi-objective optimisation using an evolutionary multi-objective optimisation algorithm called ϵv-MOGA. Three indicators of effluent quality and a process cost factor were adopted as functions to be optimised. The results were tested using multi-level control system of a complex SBR simulation model. The research is based on a case study of the Water Resource Recovery Facility (WRRF) in Swarzewo, Northern Poland.