Optimal control of water distribution networks with storage facilities. (August 2015)

• Record Type: Journal Article
• Authors: Sankar, Gokul Siva; Mohan Kumar, S.; Narasimhan, Sridharakumar; Narasimhan, Shankar; Murty Bhallamudi, S.
• Is Part Of: Journal of process control. Volume 32(2015:Aug.)
• Page Start: 127
• Page End: 137
• Publication Date: 2015-08
• Subjects: Water distribution networks -- Model predictive control -- Optimal operation -- Storage facilities; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2015.04.007
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract : Highlights: Applied model predictive control to water distribution networks. Devised a strategy for efficient and equitable distribution of water. Exploited storage facilities at demand points for effective control. Abstract: Optimal operation of water distribution networks (WDNs) is concerned with meeting consumer demands at desired pressures in an efficient and equitable manner while conserving resources. This can be achieved by implementing advanced control schemes such as model predictive control (MPC). If sufficient water is available, the control objective is to meet consumer demands while preventing wastage. On the other hand, if the available water is insufficient or inadequate to meet consumer demands at the required pressures, equitable distribution of the available resource is of primary importance. In this contribution, a nonlinear model predictive controller is proposed for optimal operation of WDNs that can deal with both the above situations. The proposed approach takes into account availability of storage facilities at the source and demand points. In addition, the control algorithm can account for plant-model mismatch. Performance of the proposed model based control strategy is illustrated through numerical simulations of an illustrative WDN operating under various water availability scenarios. In the water sufficient scenario, the proposed MPC strategy is able to meet the consumer requirements while minimizing the excess amount of water supplied. In the water deficient scenario, the MPC algorithm is able to exploit the available storage facilities at consumer end to reduce the daily supply deficit by about 20%. Using a longer prediction horizon in MPC results in a further reduction of about 40% in the daily supply deficit.