Many cities around the world have reached a critical situation when it comes to energy and water supply, threatening the urban sustainable development. From an engineering and architecture perspective it is mandatory to design cities taking into account energy and water issues to achieve high living and sustainability standards. The aim of this paper is to develop an optimization model for the planning of residential urban districts with special consideration of renewables and water harvesting integration. The optimization model is multi-objective which uses a genetic algorithm to minimize the system life cycle costs, and maximize renewables and water harvesting reliability through dynamic simulations. The developed model can be used for spatial optimization design of new urban districts. It can also be employed for analyzing the performances of existing urban districts under an energy-water-economic viewpoint. The optimization results show that the reliability of the hybrid renewables based power system can vary between 40 and 95% depending on the scenarios considered regarding the built environment area and on the cases concerning the overall electric load. The levelized cost of electricity vary between 0.096 and 0.212$/kWh. The maximum water harvesting system reliability vary between 30% and 100% depending on the built environment area distribution. For reliabilities below 20% the levelized cost of water is kept below 1$/m3 making competitive with the network water tariff.