Pump scheduling is a key element in water distribution systems operation. Modeling this problem requires a mixed integer nonlinear program (MINLP) formulation. Even linearization schemes of mixed integer linear programs (MILPs) are typically beyond the capability of real-time optimization frameworks. In this study, we explore different levels of MILP approximations by reducing the number of binary decision variables (i.e., different binarization levels). In addition, we present a simple demand forecast model and evaluate the performance and approximation accuracy of the suggested approach in a real-time optimization framework under a receding horizon operation mode. The results show that the balance between approximation accuracy and solution efficiency is biased. That is, a simple low-accuracy approximation may yield an efficient and practical solution algorithm that results in a near-optimal solution.
|Journal||Journal of Water Resources Planning and Management - ASCE|
|State||Published - 1 Apr 2020|
Bibliographical noteFunding Information:
This study was supported by the Israeli Water Authority (Contract number 4501284516).
© 2020 American Society of Civil Engineers.
- Demand forecast
- Model predictive control
- Pump scheduling
- Real time
- Water network operation
ASJC Scopus subject areas
- Civil and Structural Engineering
- Geography, Planning and Development
- Water Science and Technology
- Management, Monitoring, Policy and Law