Techno-Economic Assessment for Off-grid Electricity Alternatives for the Seawater Energy and Agriculture System

Abstract

The world has begun a course of action towards a sustainable future where bold and integral solutions must be implemented. Freshwater, food and energy are some of the most valuable resources for humankind. However, as the population grows, these resources are being depleted at unsustainable rates. The Seawater Energy and Agriculture System has been envisioned as a holistic approach to produce jet fuel, food, and other byproducts by exploiting the harsh characteristics of a desert environment using seawater, sunlight and non-arable land. Facilities under the SEAS concept are to be built mainly in remote arid coastal areas with difficult or no access to an electric grid and therefore require an autonomous power source to be operated. This study contains a techno-economic evaluation of different energy systems to power a 200-ha SEAS farm in the western region of Abu Dhabi. The annual load of the facility is estimated using System Dynamics with Vensim software. This load is then used to model, optimize and compare a set of energy system combinations using HOMERPro software to find the most efficient, reliable and costeffective autonomous system. The proposed energy systems consider different configurations of solar photovoltaics and biomass conversion as means of electricity generation while batteries, hydrogen, and pressurized gas tanks are explored as energy storage alternatives. The annual load of the proposed SEAS was found to be 0.71 GWh. The least expensive energy system consisted of a 77.6 kW solar PV system combined with a gasification power plant with an installed capacity of 180 kW feeding an AC primary and deferrable daily average loads of 1.93 MWh. The system has a Net Present Cost of $1.01 million with a levelized cost of electricity of 0.184 $/kWh. Grid break-even analysis indicated that grid extension is economically preferable than implementing a standalone energy system due to the proximity of the facility with existing grid lines.

Date of Award	May 2017
Original language	American English