Energy Management Model for Wastewater Treatment Plants

Wastewater Treatment Plants (WWTPs) are characterised by high energy consumption due to their reliance on electricity-intensive processes. Enhancing the flexibility of WWTPs to respond to dynamic electricity prices may reduce operational expenditures and contribute to electrical grid stability. This study introduces an advanced Energy Management model that extends the established IWA Benchmark Simulation Model No. 2 (BSM2) and is implemented in Python with discrete time steps. The Python model was validated against the original MATLAB/Simulink implementation, demonstrating computational speed improvements ranging from 70 % to 1199 % in open control loop configurations, with mean absolute percentage errors between 1.2 % and 6 %. The Energy Management model was scaled according to real-world data from WWTPs in Germany. It was further integrated with an operational aeration strategy aimed at reducing power consumption during peak load periods in a dynamic electricity market. Simulation results indicate that the proposed aeration management approach can enhance revenue from power sales by 12 % compared to a reference control strategy, while the Effluent Quality Index increases by only 10 %. Leveraging the insights provided by the model, researchers can make informed decisions to optimise the operation of WWTPs further by reducing operational costs, while supporting grid stability. • A model extension for energy management in wastewater treatment plants (WWTP) is presented. • A control strategy is proposed to reduce power consumption during peak electricity prices. • An example strategy increases revenues from power sales by 12%.