(155c) A Computational Model to Evaluate Solar Offset and Water Generation From Atmospheric Moisture Using Location-Specific Annual Climate Data

This paper presents an algorithm developed to predict the offset renewable solar energy can offer to reduce energy requirement of a particular cooling or dehumidification system. The algorithm takes into account location specific parameters such as solar resource availability, cooling demand time series, climatic conditions, component cost and performance parameters.

This algorithm is then used to evaluate and compare the techno-economic performances of dehumidification systems driven by different solar collector systems, namely solar thermal and solar electric. The analysis also takes into consideration water generation from ambient moisture as another significant product potentially offsetting total cost. While annual statistical weather data of any location can be analyzed, Sydney and Abu Dhabi were selected as case studies. Compared to moderate climate and higher energy costs in Sydney, Abu Dhabi revealed to be a positive potential for solar cooling investment.

The algorithm is proposed for investment decision making since it couples the solar energy technical modeling with the capital and operating expenditures of the solar-cooling/ solar-dehumidification system. This model can be applied in any location to pre-determine the feasibility of using solar collectors in a cooling or dehumidification process.