Multi-Objective Optimization of Pumping Operations from Alternative Water Sources

Water supply and distribution systems are an integral part of our society and can incur significant costs in their construction and operation. Many different optimization techniques have been applied to both the design and operation of traditional potable systems, which generally receive water from natural water bodies. As climate change and increasing populations prompt concerns of water security, in addition to natural harvested water supplies, alternative sources such as harvested stormwater, recycled wastewater and desalination are becoming more commonly used for both potable and nonpotable supply. These systems have not been researched as extensively, particularly their operation. This thesis examines the optimisation of pumping operations in water supply and distribution systems that can include conventional potable systems as well as systems that use alternative water sources. The major contributions of this research are presented in three publications. Firstly, a single-objective optimisation model was applied to potable water distribution systems, both hypothetical and real, for different types of pump operating regimes using the EPANET toolkit to alter rule-based controls. While minimizing pump energy costs was the primary objective, minimization of greenhouse gas emissions was also explored, including the variation of greenhouse gas emission factors for different electrical energy sources. Time-based scheduling operating strategies were found to perform better than the other operating regimes, and significant cost savings were achieved for the real-life system compared to its current operation. In the second paper, a framework for the optimization of water supply and distribution systems that use alternative water sources is presented, along with a detailed discussion of the components and key variables. The framework connects the potential decision variables, both design and operational, the physical components of the water system to be modelled, the simulation of each potential system configuration and evaluation against objectives and constraints, and relevant policies from regulating bodies. These all exist within an optimization algorithm structure, and sensitivity analysis of uncertain variables is also discussed. Two case study systems are used to illustrate how the framework would be applied to minimize the cost of water system operations. The final paper applies multi-objective optimisation techniques to a harvested stormwater case study system and also covers an extensive sensitivity analysis of the inputs to the system. This system has distinct winter (harvesting) and summer (irrigation) operational seasons; for the winter operation, operating rules were optimized to minimize the cost of pumping into an aquifer and to maximize the volume harvested, considering restrictions on the aquifer injection rate and pressure; during summer, irrigation scheduling was optimized to minimize pumping costs, considering the requirements for irrigation rates and amounts at various public parks and green area reserves. Results from both the optimisation and sensitivity analysis found operational cost savings if new pumps are installed, wider trigger levels are used, and certain reserves are irrigated together. This research has produced significant overall contributions to the body of knowledge. Methodologies have been developed for optimisation of potable and alternative water sources systems, highlighting important considerations and generalizable results. For three real-life case study systems, operating strategies and infrastructure changes have been suggested to provide significant savings in the cost of pumping operations.Thesis (Ph.D.) -- University of Adelaide, School of Civil, Environmental and Mining Engineering, 201

Stochastic Co-design of Storage and Control for Water Distribution Systems

Water distribution systems (WDSs) are typically designed with a conservative estimate of the ability of a control system to utilize the available infrastructure. The controller is subsequently designed and tuned based on the designed water distribution system. This sequential approach may lead to conservativeness in both design and control steps, impacting both operational efficiency and economic costs. In this work, we consider simultaneously designing infrastructure and developing a control strategy, the co-design problem, to improve the overall system efficiency. However, implementing a co-design problem for water distribution systems is a challenging task given the presence of stochastic variables (e.g. water demands and electricity prices). In this work, we propose a tractable stochastic co-design method to design the best tank size and optimal control parameters for WDS, where the expected operating costs are established based on Markov chain theory. We also give a theoretical result that investigates the average long-run co-design cost converging to the expected cost with probability 1. Furthermore, the method can also be applied to an existing WDS to improve operation of the system. We demonstrate the proposed co-design method on three examples and a real-world case study in South Australia

Additional file 3: of Framework for the optimization of operation and design of systems with different alternative water sources

CS2 Orange Data Summary. (PDF 537 kb

Alternative Water Sources Pumping Optimisation Tool for the Orange Water Supply System

These slides were presented on Thursday 23rd of June 2016 to Samantha McGufficke from the Orange City Council (NSW) and Martin Haege from Geolyse to transfer the software tool developed for the optimisation of pumping operations in water distribution systems that use alternative water sources. <br><br>This research is part of the Project C5.1 Intelligent Urban Water Systems funded by the Cooperative Research Centre for Water Sensitive Cities. <br

Additional file 1: of Framework for the optimization of operation and design of systems with different alternative water sources

CS1 Ridge Park Data Summary. (PDF 548 kb