Water is the root of life and the engine that drives agriculture, industry, economy and services. The demand for water often necessitates desalination, particularly in arid coastal environments where there are several desalination technologies in use today such as Multi-Effect Distillation (MED) and Reverse Osmosis (RO). The key utility requirement for technologies such as desalination and population in general include energy in one form or another. Therefore, desalination and co-generation are often integrated. Another key utility is electricity which is generated from either renewable or non-renewable sources. The demands for water and electricity change over time and are subject to uncertainty. In this dissertation, a country-wide large-scale energy and water cogeneration planning model for Kuwait was proposed and solved. Five different plant technologies where the planning horizon used was set to 37 years starting in year 2014 and until 2050. A Mixed Integer Mathematical programming model was proposed and formulated using General Algebraic Modeling System (GAMS), the resulting model was solved using the CPLEX solver engine. In this research obtained detailed data on the consumption on water and energy in Kuwait and performed time series analysis of the population growth and individual behavior of water and energy consumption and novel method to represent cogeneration plants was implemented in the proposed mathematical programming model. ix A modeling framework that involves a data spreadsheet and a proprietary model was implemented. The data spreadsheet and the model were formulated as a template that can receive data from different applications. In addition, automation using Visual Basic for Application (VBA) was made to the data spreadsheets such that the data is sent to the model template, Gams-Cylix, and are written back to the spreadsheet. An analysis was made between oil-based plants, natural gas (NG) plants, and solar-based plants for co-generation. It was found that for water production solar-based plants can supply 50 percent or more of the demand during after period 2020 and after implementation and for electric power generation solar plants are limited. The results indicate the preferred technology for energy generation was NG-RO. With the implementation of solar based plants the electric power load is distributed among the technologies. NG-RO plants are more scalable and therefore were expanded to cope with the future demand. The percentage of the electric power supplied by solar plant was below 35 percent across the planning horizon. By the end of the planning horizon the percentage of electric power supplied by solar base plants was nearly 20 percent. Near 70 percent of the electric power was supplied by NG RO by period 2050. Other technologies had a representation of less than 10 percent by the end of the planning horizon.