Shankar Narasimhan S

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.

Small RO based desalination plants driven by solar power are attractive options, especially in areas with unreliable grid power supply. Batteries or other energy storage devices can be used to buffer against the inherent variability in solar power. However, the capital and maintenance cost of batteries and problems associated with their safe disposal renders this option unattractive. The focus of this work is optimal operation of an RO plant driven by solar power without batteries under continuously varying solar radiation intensity. A model of an RO plant driven by solar power without batteries is developed and demonstrated to have adequate predictive capability. The model is used to determine optimal operation policies under two different methods of operation, namely, (i) without storage of permeate and (ii) with permeate storage. Examination of the optimal solution in the first mode of operation reveals that a simple, robust, and model free implementation strategy using active constraint control is possible. Comparison of results show that accounting for the permeate storage results in a higher permeate production, and the buffer tank can be viewed as a surrogate energy storage device.