Multi-objective optimization of solar power tower hybridization with gas turbine and thermal energy storage back up

This work assesses the performance of solar power tower technology with both fossil fuel and renewable energy-based backup systems. The probable effects of aerosols on this type of concentrated solar power in arid regions are measured prior to the hybridization with the fossil fuel backup which is to compensate any energy losses due to the density of aerosols. The assessment is based on a multi-objective optimization approach where key design parameters of the solar power tower such as the thermal energy storage capacity and the solar field size are considered as variables. The performance of the solar power tower is evaluated using the System Advisor Model simulation tool while that of the gas turbine is evaluated by Aspen Plus. The hybridization of both technologies is obtained using an in-house developed algorithm. The multi-objective optimization is realized with the assistance of the Non-dominated Sorted Genetic Algorithm II where the conflicting objective functions of lowest levelized cost of energy, highest annual energy generation, highest capacity factor and lowest CO2 emissions are targeted. The optimization targets the best techno-economic configuration among the various possible scenarios which potentially can fulfill Kuwait's 2035 vision of renewable energy adoption with the exploitation of existing natural resources. The assessment considers the already assigned renewable energy site of Shagaya as a case study location.