Formulation of the Pump Operations Optimization Problem for a Harvested Stormwater System. (2017)

• Record Type: Journal Article
• Authors: Blinco, Lisa J.; Simpson, Angus R.; Lambert, Martin F.; Marchi, Angela
• Is Part Of: Procedia engineering. Volume 186(2017)
• Page Start: 202
• Page End: 209
• Publication Date: 2017
• Subjects: Water supply systems -- optimization -- harvested stormwater -- pump operation -- irrigation scheduling -- genetic algorithms; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Conference proceedings; Periodicals; 620.005
• DOI: 10.1016/j.proeng.2017.03.228
• Languages: English
• ISSNs: 1877-7058

Abstract

Abstract: As climate change and population growth, among other factors, put pressure on traditional water supplies, alternative sources of water are increasingly being used to supplement demand, particularly for non-potable applications. Stormwater from urban catchments can be harvested and treated to supply irrigation demands of public green spaces such as parks, reserves and sporting grounds. Operation of such systems often requires several pumping stages between multiple storage ponds, which can result in a significant amount of energy use and also increases the complexity of the operations. In many water supply systems, demand rates and patterns are determined by when consumers choose to use water and how much they use, thus the demands constrain the system operation. For irrigation of public green spaces, however, the operators can prescribe when water should be used at each demand point, and thus the demand pattern is a choice rather than a constraint. This paper discusses how harvested stormwater systems with multiple pumping stages can simulated as multiple 'sub-systems' in order to better understand the hydraulics and better formulate the corresponding optimization problem. A case study site from Australia that utilizes harvested stormwater for non-potable irrigation demands is used to demonstrate the simulation approach. Simulating the case study in smaller 'sub-systems' has highlighted the need for better pump and tank sizing for the system, and has then informed the optimization problem formulation.