Cost-Efficient Algorithms for a Pump Horizon Control in Water Supply System

Abstract

Modern cities have water supply systems (WSS) that reliably meet the water demand of every individual household. If inefficiently managed, these energy-consuming systems can become very costly. To produce the most cost-efficient operational strategies, many techniques using emerging computer power, simulation technologies, and sensing devices have been developed. Some of these techniques rely on water consumption predictions to provide optimal pumping strategies. However, predicted consumptions contain errors, and these techniques do not automatically adjust to sudden changes in demand. To solve this problem, a cost-adaptive finite-horizon controller to efficiently update the pumping operation strategy based on monitored deviations against the predicted consumption is proposed. This methodology takes into account the tariffs of electricity over time and an optimized reference to continuously make the most cost-efficient updates in the pumping strategy. To validate the cost-adaptive controller, two case studies were used: (1) a single pump-tank network; and (2) the Richmond benchmark network. Both evaluations delivered positive results achieving the desired control reliability while improving cost efficiency. The combination of water consumption predictions and adaptive control methodologies provides a reliable and cost-efficient solution for the automatic operation of WSS.