Abstract
Concerns over the environmental influence of greenhouse gas (GHG) emissions have encouraged researchers to develop alternative power technologies. Among the most promising, environmentally friendly power technologies for large-scale applications are solar power tower plants. The implementation of this technology calls for practical modeling and simulation tools to both size the plant and investigate the scale effect on its economic indices. This paper proposes a methodology to design the main components of solar power tower plants and to estimate the specific investment costs and the economic indices. The design approach used in this study was successfully validated through a comparison with the design data of two operational commercial power tower plants; namely, Gemasolar (medium-scale plant of 19.9 MWe) and Crescent Dunes (large-scale plant of 110 MWe). The average uncertainty in the design of a fully operational power tower plant is 8.75%. A cost estimation showed the strong influence of the size of the plant on the investment costs, as well as on the economic indices, including payback period, internal rate of return, total life charge costs, and levelized cost of electricity. As an illustrative example, the methodology was applied to design six solar power tower plants in the range of 10–100 MWe for integration into mining processes in Chile. The results show that the levelized cost of electricity decreases from 156 USD/MWhe for the case of a 10-MWe plant to 131 USD/MWhe for the case of a 100-MWe plant. The internal rate of return of plants included in the analyses ranges from 0.77% (for the 10-MWe case) to 2.37% (for 100-MWe case). Consequently, the simple payback ranges from 16 years (for the 100-MWe case) to 19 years (for the 10-MWe case). The sensitivity analysis shows that the size of the solar receiver heavily depends on the allowable heat flux. The degradation rate and the discount rate have a strong influence on economic indices. In addition, both the operation and the deprecation period, as well as the price of electricity, have a crucial impact on the viability of a solar power tower plant. The proposed methodology has great potential to provide key information for prospective analyses for the implementation of power tower technologies to satisfy clean energy needs under a wide range of conditions.
Highlights
Fossil fuel reserves in the world are rapidly decreasing, and so it is important to tap the abundant solar energy source to both meet future energy demands and reduce greenhouse gas (GHG) emissions
The results show that the degradation rate has a critical influence on the levelized cost of electricity (LCOE)
If this value is doubled (1.5%), the LCOE increases to reach more than 150 USD/MWh
Summary
Fossil fuel reserves in the world are rapidly decreasing, and so it is important to tap the abundant solar energy source to both meet future energy demands and reduce greenhouse gas (GHG) emissions. Of all CSP technologies available today, the solar power tower (PT) is expected to both significantly reduce its cost and improve its efficiency over time [2,3] This technology has several potential advantages over other CSP technologies (parabolic trough, linear Fresnel, and solar dish), including higher operating temperatures, which allow for greater efficiency of the thermodynamic cycle, low water consumption, and high-energy-density storage [3]. The design of these power plants poses considerable challenges given the complexity of the mathematical models required in both optical and thermal analyses of their main components. To speed up the growth in the installed capacity of PT plants and the associated cost reductions, practical design procedures and reliable data on investment costs are required
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