Multiobjective genetic algorithm optimization of water distribution systems accounting for economic cost, greenhouse gas emissions and reliability.

Multiobjective optimization is becoming an increasingly important approach for both the design and operation of water distribution systems (WDSs). Given the multiobjective nature of these problems, multiobjective optimization is expected to provide decision makers with increased insight into the tradeoffs between competing objectives and alternative solutions of WDSs, which might benefit the water industry, society and environment. Due to the advances in computing technology and the development of fast multiobjective sorting algorithms, research activities into the application of multiobjective algorithms to WDS design and operation have increased significantly in the past decade. Minimization of economic cost and maximization of network reliability are the two most commonly considered objectives in WDS optimization. In addition, some environment related issues, such as energy conservation, have been incorporated into the optimization of WDSs. However, the leading environmental concern – Greenhouse gas (GHG) emissions – has not yet been addressed directly in the field of WDS optimization. Consequently, this research incorporates GHG emission minimization as an objective directly into the optimal design of WDSs, together with the economic objective of minimizing cost and the hydraulic reliability objective of maximizing surplus power factor via a multiobjective approach. The major research contributions are presented in six journal publications. These publications describe the motivation and methodology to incorporate GHG emission minimization as an objective of WDS optimization; explore the tradeoffs between the traditional objective of minimizing life cycle cost and the environmental objective of minimizing life cycle GHG emissions; investigate the sensitivity of these tradeoffs to a number of factors, including the discount rate, electricity tariffs and emission factors used in the objective function evaluation process, the price of carbon under a potential emissions trading scheme and the use of fixed-speed or variable-speed pumps; and finally examine the impact of the inclusion of the hydraulic reliability objective of maximizing surplus power factor on WDS optimization account for economic cost and GHG emissions. In addition, two technical issues have also been solved in order to achieve the overall research aim. First, an optimization based generic pump power estimation method has been developed in this research to efficiently estimate the size and pump power of the pumps required for different network configurations, thus variable-speed pumps can be incorporated into the optimal design of WDSs. Secondly, a new hydraulic reliability measure based on the concept of surplus power factor has been incorporated into the optimal design of WDSs. The advantage of this hydraulic measure over currently used hydraulic reliability measures is that it can be used for WDSs involving the delivery of water into storage facilities, where other measures have failed. The overall contribution of this research is the incorporation of GHG emission consideration into the design optimization of WDSs together with the traditional economic and reliability objectives via a multiobjective approach. It is anticipated that this research will lead to a new paradigm for the optimization of WDSs in the real world.Thesis (Ph.D.) -- University of Adelaide, School of Civil, Environmental & Mining Engineering, 201