With the escalating levels of water demand, there is a need for expansion in the capacity of water desalination infrastructure and for better management and distribution of water resources. This dissertation introduces a systems approach to the optimization of macroscopic water desalination and distribution networks to tackle three problems: 1. Optimal design of desalination and allocation networks for a given demand, 2. Optimal operation of an existing infrastructure of water desalination, distribution, and storage, 3.Optimal planning for expanding the capacity of desalination plants to meet an increasing water demand over a time horizon.
A source-interception-sink representation was developed to embed potential configurations of interest. Mathematical programming was used to model the problem by studying different objective functions while accounting for constraints the supply, demand, mass conservation, technical performance, and economic aspects. Such approach determines the type of technologies to be selected, the location and capacity of the desalination plants, and the distribution of the desalinated water from sources to destinations. For the operation and planning problems, the planning horizon was discretized into periods and a multi-period optimization approach was adopted with decisions made for each period. Short- and long-term water storage options (e.g., in storage tanks, aquifers) were included in the optimization approach. Water recycle/reuse was enhanced via the use of treated water and its utilization was improved by minimizing the losses observed in discharged water resulting from the linkage of power plants and thermal desalination plants and the lack of integration between water production and consumption. Several case studies were solved to demonstrate the applicability of the devised approaches.
Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2011-12-10393 |
Date | 2011 December 1900 |
Creators | Atilhan, Selma |
Contributors | El-Halwagi, Mahmoud |
Source Sets | Texas A and M University |
Language | en_US |
Detected Language | English |
Type | thesis, text |
Format | application/pdf |
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