Performance enhancement of solar tower power plant: A multi-objective optimization approach

The aim of this research is to design, optimize, and evaluate the performance of the solar tower (ST) power plant. The plant is initially designed for solar multiple (SM) of 2, tower height of 190 m and 10 h of full load thermal energy storage (TES). The initial design of the plant is optimized for number of full load storage hours, tower height and SM using multi-objective optimization technique. A fuzzy goal programing approach and an evolutionary computational technique, particle swarm optimization are used. The optimized design parameters converge to SM of 2.7, tower height of 205 m and TES system of 8.7 h. The optimized and initial designs of the plant are compared based on annual and lifetime energy output, capacity utilization factor (CUF), land use factor, solar to electric efficiency, levelized cost of energy (LCoE), and net capital cost (NCC). The main optimization objectives are LCoE and energy output. Although the optimized ST plant design has 13.5% more NCC and 0.9% less solar to electric efficiency, but the optimized design has outperformed the initial design in all the other performance parameters. It has 16.2% better CUF with 35.6% better energy output, 3.1% better land use factor and 16.9% lower LCoE compared to the initial design. The optimized design utilizes the TES system more effectively and it can produce electricity for longer duration after the sunset. It has long average operational hours from 8 am to 3 am as compared to initial design from 8 am to 10 pm.