PLIO: a generic tool for real-time operational predictive optimal control of water networks

Journal of Process Control

Cembraño

2017

105

This paper addresses a non-linear economic model predictive control (EMPC) strategy for water distribution networks (WDNs). A WDN could be considered as a non-linear system described by differential-algebraic equations (DAEs) when flow and hydraulic head equations are considered. As in other process industries, the main operational goal of WDNs is the minimisation of the economic costs associated to pumping and water treatment, while guaranteeing water supply with required flows and pressures at all the control/demand nodes in the network. Other operational goals related to safety and reliability are usually sought. From a control point of view, EMPC is a suitable control strategy for WDNs since the optimal operation of the network can not be established a priori by fixing reference volumes in the tanks. Alternatively, the EMPC strategy should determine the optimal filling/emptying sequence of the tanks taking into account that electricity price varies between day and night and that the demand also follows a 24-hour repetitive pattern. On the other hand, as a result of the ON/OFF operation of parallel pumps in pumping stations, a two-layer control scheme has been used: a non-linear EMPC strategy with hourly control interval is chosen in the upper layer and a pump scheduling approach with one-minute sampling time in the lower layer. Finally, closed-loop simulation results of applying the proposed control strategy to the D-Town water network are shown.

Section: Control-oriented Modelling Water Distribution Networkmentioning

confidence: 99%

Non-linear economic model predictive control of water distribution networks

Wang

Journal of Process Control

Cembraño

2017

105

“…PLIO, which is a tool for the optimal operational control of DWN that implements non-linear MPC as introduced in Cembrano et al (2011), has been developed using standard GUI(graphical user interface) techniques and objective oriented programming using Visual Basic.NET. In PLIO, models are built using the GAMS optimization modelling language.…”

Section: Validation Of Csp-mpc Using Pliomentioning

confidence: 99%

“…Other authors employ discrete dynamic programming as presented in Zessler and Shamir (1989), which is only applicable to small networks. There exist tools like PLIO in Cembrano et al (2011), which is able to solve both linear and non-linear MPC problems with a gradient-based optimization being only able to guarantee local optimal solutions.…”

Section: Introductionmentioning

confidence: 99%

Combining CSP and MPC for the operational control of water networks

Sun

Engineering Applications of Artificial Intelligence

Cembraño

2016

This paper presents the combination of linear Model Predictive Control (MPC) with Constraint Satisfaction Problem (CSP) for the operational control of drinking water networks. The methodology has been divided into two functional layers: First, a CSP algorithm is used to transfer non-linear pressure equations of drinking water networks (DWNs) into linear constraints, which can enclose feasible solution of the hydraulic non-linear problem during the optimizing process. Then, a linear MPC with added linear constraints is solved to generate control strategies which consider control objectives. Finally, the proposed approach is simulated using Epanet to represent the real DWNs. PLIO, which is a generic operational tool for controlling water networks that uses non-linear MPC, is used for validation. The Richmond water system is used as a case study.

“…This allows testing the controller against a virtual reality introducing for example real demand in the simulator different from the predicted demand used by the controller. The MPC controller was implemented with the tool presented in (Cembrano, 2011) that uses GAMS/CONPOPT solver to solve the optimization problem (16) (see Appendix I).…”

Section: Application: the Barcelona Water Transport Networkmentioning

confidence: 99%

Operational Predictive Optimal Control of Barcelona Water Transport Network

Pascual

Romera

IFAC Proceedings Volumes

et al. 2011

Self Cite

This paper describes the application of model-based predictive control (MPC) techniques to the supervisory flow management in large-scale drinking water networks including a telemetry/telecontrol system. MPC is used to generate flow control strategies (set-points for the regulatory controllers) from the sources to the consumer areas to meet future demands, optimizing performance indexes associated to operational goals such as economic cost, safety storage volumes in the network and smoothness of the flow control actions. The designed management strategies are applied to a model of a real case study: the drinking water transport network of Barcelona (Spain).