Incorporating Environmental Impacts into Multi-Objective Optimization of Water Distribution Systems

• Main Author: HERSTEIN, LESLEY
• Other Authors: Queen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))
• Format: Others
• Language: en; en
• Published: 2009
• Subjects: Engineering; Sustainability; Water Distribution Systems; Optimization; Environmental Impact
• Online Access: http://hdl.handle.net/1974/5090

Municipal water distribution system (WDS) expansion is often focused on increasing system capacity with designs that best meet hydraulic requirements at the least cost. Increasing public awareness regarding global warming and environmental degradation is making environmental impact an important factor in decision-making for municipalities. There is thus a growing need to consider environmental impacts alongside cost and hydraulic requirements in the expansion and design of WDSs. As a result, the multiplicity of environmental impacts to consider in WDS expansion can complicate the decisions faced by water utilities. For example, a water utility may wish to consider environmental policy issues such as greenhouse gas emissions, non-renewable resource use, and releases to land, water, and air in WDS expansion planning. This thesis outlines a multi-objective optimization approach for WDS design and expansion that balances the objectives of capital cost, annual pumping energy use, and environmental impact minimization, while meeting hydraulic constraints. An environmental impact index that aggregates multiple environmental measures was incorporated as an environmental impact objective function in the multi-objective non-dominated sorting genetic algorithm-II (NSGA-II) optimization algorithm. The environmental impact index was developed to reflect stakeholder prioritization of specific environmental policy issues. The evaluation of the environmental impact index and its application to the WDS expansion problem was demonstrated with a water transmission system example. The environmental impact index and multi-objective non-dominated sorting genetic algorithm-II (NSGA-II) optimization algorithm were applied to the “Anytown” network expansion problem. Preliminary results suggest that solutions obtained with the triple-objective capital cost/energy/EI index optimization minimize a number of environmental impact measures while producing results that are comparable in pumping energy use and, in some instances, slightly higher in capital cost when compared to solutions obtained with a double cost/energy optimization in which environmental impact was not considered. === Thesis (Master, Civil Engineering) -- Queen's University, 2009-08-25 16:08:33.636