Real-time model predictive control of urban drainage system in coastal areas

In the context of global climate change and urbanization, model predictive control (MPC) has been increasingly applied in the field of real-time control of urban drainage systems to cope with frequent urban flooding events caused by extreme rainstorms. However, the computation time of the predictive model calculation greatly hinders further development of MPC in this field. In this study, we propose two surrogate models, namely the water tank-water balance model 1 (TWBM1) and the water tank-water balance model 2 (TWBM2), to replace the storm water management model (SWMM) as the prediction model for MPC, thus improving MPC computational efficiency. Both surrogate models can obtain the total outflow process at the downstream outfall of the study area and the corresponding overflow process. In comparison with TWBM1, TWBM2 requires 26 % fewer calibration parameters, and its structure is simpler. These results have been verified in the real-time optimal scheduling of a rainwater drainage system in the Doumen area of Fuzhou City, China. The results show that TWBM1 and TWBM2 have shorter computation time compared to SWMM, which improves the efficiency of MPC computation. Additionally, in comparison with the existing scheduling results, MPC has better performance in terms of economy, security and computational efficiency.