A multi-objective optimisation model for pump scheduling using renewable solar energy in water distribution networks

Saeid Najjar-Ghabel

School of Computing and Engineering

Supervisor:

Professor Kourosh Behzadian

School of Computing and Engineering

Optimal pump scheduling in solar-powered water distribution networks (WDNs) is essential for cost savings, environmental benefits, and efficient water supply. By leveraging solar energy effectively, utilities can minimise operational expenses and promote sustainable practices. Addressing this challenge requires advanced optimisation techniques and accurate modelling to achieve robust control policies for pump settings.

This study presents an optimisation model to

1) minimise the daily cost of water pumping and 2) minimise the number of pump switches. The WDNs hydraulic model, EPANET, is linked to the multi-objective genetic algorithm, namely NSGA-II, for finding a set of solutions between the two objectives. The developed model is evaluated in Anytown WDN. Moreover, various constraints are defined in the optimisation model to meet the water demand of consumers, pressure control in each node, and water level control in the storage tank.

The result showed that using solar energy can effectively reduce the daily cost of water pumping. Moreover, the NSGA-II algorithm showed a high capability in finding the optimum daily cost and a minimum number of switches. The optimal Pareto front generated by NSGA-II allows water utilities to analyse trade-offs between objectives. The proposed method in this research can be applied to other case studies to help the decision-makers explore the impact of different pump scheduling policies on energy costs and system reliability.