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A Through-Life Cost Analysis Model to Support Investment Decision-Making in Concentrated Solar Power Projects

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  • Mahmood Shafiee

    (School of Engineering and Digital Arts, University of Kent, Canterbury CT2 7NT, UK
    Department of Energy and Power, Cranfield University, Bedfordshire MK43 0AL, UK)

  • Adel Alghamdi

    (Department of Energy and Power, Cranfield University, Bedfordshire MK43 0AL, UK)

  • Chris Sansom

    (Department of Energy and Power, Cranfield University, Bedfordshire MK43 0AL, UK)

  • Phil Hart

    (Department of Energy and Power, Cranfield University, Bedfordshire MK43 0AL, UK)

  • Adriana Encinas-Oropesa

    (Centre for Competitive Creative Design, Cranfield University, Bedfordshire MK43 0AL, UK)

Abstract

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 50 MW 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.

Suggested Citation

  • Mahmood Shafiee & Adel Alghamdi & Chris Sansom & Phil Hart & Adriana Encinas-Oropesa, 2020. "A Through-Life Cost Analysis Model to Support Investment Decision-Making in Concentrated Solar Power Projects," Energies, MDPI, vol. 13(7), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1553-:d:337596
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    References listed on IDEAS

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    1. Bhattarai, Sujala & Kafle, Gopi Krishna & Euh, Seung-Hee & Oh, Jae-Heun & Kim, Dae Hyun, 2013. "Comparative study of photovoltaic and thermal solar systems with different storage capacities: Performance evaluation and economic analysis," Energy, Elsevier, vol. 61(C), pages 272-282.
    2. Zhao, Zhen-Yu & Chen, Yu-Long & Thomson, John Douglas, 2017. "Levelized cost of energy modeling for concentrated solar power projects: A China study," Energy, Elsevier, vol. 120(C), pages 117-127.
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    Cited by:

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    2. Afra, Mohammad & Peyghambarzadeh, S.M. & Shahbazi, Khalil & Tahmassebi, Narges, 2021. "Thermo-economic optimization of steam injection operation in enhanced oil recovery (EOR) using nano-thermal insulation," Energy, Elsevier, vol. 226(C).
    3. Zhixian Wang & Ying Wang & Qia Ding & Chen Wang & Kaifeng Zhang, 2020. "Energy Storage Economic Analysis of Multi-Application Scenarios in an Electricity Market: A Case Study of China," Sustainability, MDPI, vol. 12(20), pages 1-17, October.
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    6. Milford, James & Henrion, Max & Hunter, Chad & Newes, Emily & Hughes, Caroline & Baldwin, Samuel F., 2022. "Energy sector portfolio analysis with uncertainty," Applied Energy, Elsevier, vol. 306(PA).
    7. Mika Fabricius & Daniel Øland Tarp & Thomas Wehl Rasmussen & Ahmad Arabkoohsar, 2020. "Utilization of Excess Production of Waste-Fired CHP Plants for District Cooling Supply, an Effective Solution for a Serious Challenge," Energies, MDPI, vol. 13(13), pages 1-21, June.

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