Chapter 5: Abu Dhabi Water Capacity Planning Model
5.1 Problem Statement
In this study, a capacity expansion planning model for the EAD, characterized by limited renewable water resources, is proposed. GW is the only conventional source in the EAD, and it is non-renewable owing to scanty rainfall and low natural recharge.
Non-conventional supply sources are DW from seawater and TS from WW. Another option, namely, importation of water from places outside the EAD mainland is feasible, and therefore included. However, this option of long distance transportation via pipeline is limited to DW.
As the EAD covers a large region with multiple economic development zones, the area can be divided to constitute several regions based on population distribution and terrain. Each region has demands for specific uses, and it originates from each population centers located within each region. It is also assumed that there are several
locations ‘l’ representing the locations of DW and TS production plants and extraction of GW. In addition, there are several technology sets k for water production from each source and n number of plants on k technology is possible at any plant location l in any region r. These plants associated with DW and TS plants differ in capital, operation and environmental costs. The population centers and plant locations or origin of water supply are referred to as nodes in this study.
Therefore, the overall water supply system in the EAD comprises three main supply sources, namely, DW, TS and GW. DW is produced by treating seawater using various technologies in desalination plants located within or outside the EAD.
Moreover, DW that is produced can be imported to any of the population centers in the EAD by long-distance pipelines. Therefore, DW system at regional level comprises DW plants, inter-regional pipelines, and external DW plants and the pipelines connecting the sub-regions and external plants. The study was focused only to that point that DW is made available at the key distribution points within each sub-region to meet demands. Owing to the complexity in determining the distribution networks and its relatively low contribution to the overall cost of DW infrastructure and operation, the distribution to end users is not included. TS supply system can otherwise be called as non-potable system which comprises collection and transport of wastewaters from all population centers to the treatment plants to produce TS, and a distribution network of TS to the users. However, in this study the focus was only on the production of TS from the WW at the treatment plants, without considering the transportation of WW and distribution of TS. This was neglected because this study assumed that a sewer system and TS distribution already exist in all the major population centers and expanding these systems cost lesser when compared to the overall cost. It was assumed that GW supply is for both irrigational and non-potable
purposes. In this case too, the distribution cost is not considered. In addition, it was assumed that the pipeline for TS and GW supply is well established. To identify types of demand based on water quality and specific uses, demand types were classified as potable (pot), non-potable (np) and irrigation (ir), together representing the annual water demands. Potable water systems refer to the DW supply system with high purity of water that can be used to meet all types of demands including those by residential, industrial, commercial and other domestic purposes requiring drinking water quality.
Irrigation demand is a special case of non-potable demand as TS water quality is not satisfactory on aesthetic grounds. Therefore, irrigation demand is satisfied by two sources, namely, DW and GW. Finally, the non-potable demands are satisfied with the quality of tertiary-treated wastewater called TS. This represents irrigating non- agricultural lands such as forests, landscapes, public places with lawns and other recreational activities.
All types of demands in each region are considered to vary annually. The annual demands depend on population growth, and governmental strategies and policies. The study period is therefore divided into several time periods; each represent a year. Therefore, a planning horizon of T years is divided into t periods of demands.
Seasonal variations within a year are not considered in the study. This means the average daily demands and production of water are assumed to be same throughout the year.
In this optimization problem of water supply management of multiple regions for a multiperiod planning, the following data are considered to be given: regions of water demand and supply; population centers within each region; distance between DW plant locations and key distribution points of adjacent regions; regional annual
potable, non-potable and irrigation demands; WW generation at each population center in each region; total available GW reserve, unit capital and operation cost data of all technologies of treatments for different size capacity intervals, unit costs for installation of pipelines of different diameter sizes and materials, environmental cost of GW in terms of associated economic value, environmental costs of all production technologies and transportation in terms of carbon footprint, and cost of desalination brine discharge into sea.
The objective is to minimize the NPV of the multiperiod water supply problem over the planning horizon that includes the capital cost of treatment plants and pipelines, Operation and Maintenance (OM) cost of treatment plants and transportation, and environmental cost of treatment plants and transportation. The main decision variables to be determined from the optimization problem are optimal capacity planning of treatment plants for DW and TS, selection of optimal technologies for capacity increase of DW and TS plants, optimal retrofit of existing pipeline routes connecting regions and DW plants, year of retrofit/expansion of capacities of plants in the planning horizon, and optimal production and use of DW and TS water at all production locations in every region, and optimal extraction of GW to sustainably meet water demands in the EAD.