A Real Time Optimization Based Sequential Convex Program for Pressure Management in Water Distribution Systems

Abstract

Abstract Optimal pressure regulation to water leakage reduction in water distribution systems (WDSs) is one of the most priority tasks for water utilities worldwide. Mathematically, this engineering problem can be casted into a nonlinear program (NLP) where decision variables are valve settings and relative speeds of pumps. With given demand parameters, by formulating and and solving the NLP, control quantities will be computed and applied to the system for the control purpose. In practice, the demand parameters change continuously in time, and solving the formulated NLP requires a huge computation time, as a result, the control quantities obtained from the last NLP are remained to regulate the system until solution of the current NLP (with updated parameters) is available and so on. For this reason, how fast the solution of the NLP is deduced is vital for improving the control system performance. In this paper, we proposed to apply a new real time scheme based sequential convex program for computing approximated control profiles with respect to the change of water demand patterns. In particular, instead of solving the NLP with newly estimated demand pattern to full accuracy, only one convex NLP is solved in the computation framework of the sequential convex program (SCP) to get approximated solution with acceptable accuracy and in a near real time fashion. To demonstrate the efficacy of the real time optimization scheme, we apply it to determine fast control quantities for a real world WDS in Vietnam and one WDS benchmark for optimal pressure management. The results have demonstrated that, by applying such the optimization scheme, the obtained control profile gains acceptable accuracy as compared with the fully accurate one while the performance of control system is significantly enhanced.