The aim is to establish the feasibility and efficacy of introducing real-time, optimal-control for water-distribution networks with a view to reducing operating costs and leakage. To that end, a generic methodology will be developed based on the use of a trained artificial neural network for predicting the consequences of control settings and a genetic algorithm to determine the optimal combination. Demand fluctuations, operating constraints and tariff structure will be taken into account. The prototype system will be applied to two networks of different complexities and the results compared with manual control. As a consequence of improved pressure management, it is confidently expected that optimal control will save some 20 percent of operating costs, particularly if leakage reduction is taken into account. Additionally, there will be improvements to system performance by ensuring that operational requirements are consistently met.
Funding SchemeCSC - Cost-sharing contracts