High operating cost caused by electric energy consumption is a common problem
challenging many municipal wastewater treatment plants (WWTPs). Due to the
characteristics of intermittent inflow and aeration, WWTPs using sequencing batch
reactor technology and its variants can be managed to relieve operating cost through
taking advantage of time-of-use electricity pricing. However, little attention has been
paid to the scheduling of treatment processes in the context of WWTPs. In this paper, a
novel mixed-integer linear programming model is established for scheduling the batch
operation of a WWTP under time-of-use electricity pricing, which considers constraints
arising from task allocation, processing sequence, and processing duration. The modeling
method is developed from the event-based continuous-time approach. The start time and
end time of each treatment task are optimized to shift electricity consumption from peak
hours to off-peak hours to the greatest extent, thus minimizing electricity cost. A case
study demonstrates that the proposed model can quickly generate precise operational
plans for the investigated WWTP. By implementing the optimum schedules, the WWTP can
save on its electricity bill without changing the treatment capacity or the treatment
process. The widening of peak and off-peak electricity pricing gap is favorable for the
proposed model to display a more significant effect in reducing electricity cost.