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A Through-Life Cost Analysis Model to Support Investment Decision-Making in Concentrated Solar Power Projects
School of Engineering and Digital Arts, University of Kent, Canterbury CT2 7NT, UK
Department of Energy and Power, Cranfield University, Bedfordshire MK43 0AL, UK
Centre for Competitive Creative Design, Cranfield University, Bedfordshire MK43 0AL, UK
Author to whom correspondence should be addressed.
Energies 2020, 13(7), 1553; https://doi.org/10.3390/en13071553 (registering DOI)
Received: 15 July 2019 / Revised: 3 March 2020 / Accepted: 20 March 2020 / Published: 27 March 2020
This research paper aims to propose a through-life cost analysis model for estimating the profitability of renewable concentrated solar power (CSP) technologies. The financial outputs of the model include net present value (NPV) and benefit-cost ratio (BCR) of the project, internal rate of return (IRR) and discounted payback period (DPBP) of the investment, and levelized cost of energy (LCoE) from the CSP technology. The meteorological data for a specific location in the city of Tucson in Arizona is collected from a network of automated weather stations, and the NREL System Advisor Model (SAM) is applied to simulate hourly energy output of the CSP plant. An Excel spreadsheet tool is designed to calculate, in a bottom-up approach, the financial metrics required for approval of CSP projects. The model is tested on a 50MW parabolic trough CSP plant and the results show an annual energy production of 456,351,232 kWh, NPV of over $64 million and LCoE of 0.16 $/kWh. Finally, a sensitivity analysis is performed to identify the factors which have the most significant effect on the economic performance of CSP technologies. The proposed model can provide valuable guidance to support the strategic planning and investment decision-making in CSP projects.
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