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.
© 2022 The Authors. Published by American Chemical Society.