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Global sensitivity and uncertainty analysis of the levelised cost of storage (LCOS) for solar-PV-powered cooling

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  • Luerssen, Christoph
  • Verbois, Hadrien
  • Gandhi, Oktoviano
  • Reindl, Thomas
  • Sekhar, Chandra
  • Cheong, David

Abstract

In this paper, we investigate the sensitivity of the parameters affecting the levelised cost of storage (LCOS) of Lithium ion (Li-Ion) battery storage and chilled water storage for on-grid PV-powered cooling applications, namely an office and a hotel building. Therefore, we carry out multi-objective optimisations to minimise the LCOS and maximise the self-sufficiency based on TRNSYS simulation models. For selected optimal solutions, we perform Morris and Sobol global sensitivity as well as uncertainty analyses. The results show that the chilled water storage yields up to 8 ctUSD/kWhel lower LCOS than the battery storage at the same self-sufficiency; however, the battery storage can increase the self-sufficiency more. The dominant parameter affecting the LCOS is the storage lifetime for the battery. Careful design of the dedicated chiller plant to charge the storage is important for the system configuration with chilled water storage. Because of the wide range of possible battery lifetimes, the 90% confidence interval for the LCOS of battery storage is 2.6 times larger than the one for chilled water storage given the input parameter ranges in this study. The future trend indicates that battery storage is expected to become more competitive due to technological advancements and favourable price developments.

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  • Luerssen, Christoph & Verbois, Hadrien & Gandhi, Oktoviano & Reindl, Thomas & Sekhar, Chandra & Cheong, David, 2021. "Global sensitivity and uncertainty analysis of the levelised cost of storage (LCOS) for solar-PV-powered cooling," Applied Energy, Elsevier, vol. 286(C).
  • Handle: RePEc:eee:appene:v:286:y:2021:i:c:s0306261921000854
    DOI: 10.1016/j.apenergy.2021.116533
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    References listed on IDEAS

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    1. Verbois, Hadrien & Blanc, Philippe & Huva, Robert & Saint-Drenan, Yves-Marie & Rusydi, Andrivo & Thiery, Alexandre, 2020. "Beyond quadratic error: Case-study of a multiple criteria approach to the performance assessment of numerical forecasts of solar irradiance in the tropics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    2. Chow, T. T. & Chan, Apple L. S. & Song, C. L., 2004. "Building-mix optimization in district cooling system implementation," Applied Energy, Elsevier, vol. 77(1), pages 1-13, January.
    3. Comodi, Gabriele & Carducci, Francesco & Sze, Jia Yin & Balamurugan, Nagarajan & Romagnoli, Alessandro, 2017. "Storing energy for cooling demand management in tropical climates: A techno-economic comparison between different energy storage technologies," Energy, Elsevier, vol. 121(C), pages 676-694.
    4. Luerssen, Christoph & Gandhi, Oktoviano & Reindl, Thomas & Sekhar, Chandra & Cheong, David, 2019. "Levelised Cost of Storage (LCOS) for solar-PV-powered cooling in the tropics," Applied Energy, Elsevier, vol. 242(C), pages 640-654.
    5. Tian, Wei, 2013. "A review of sensitivity analysis methods in building energy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 411-419.
    6. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 214(C), pages 219-238.
    7. Obi, Manasseh & Jensen, S.M. & Ferris, Jennifer B. & Bass, Robert B., 2017. "Calculation of levelized costs of electricity for various electrical energy storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 908-920.
    8. DeForest, Nicholas & Mendes, Gonçalo & Stadler, Michael & Feng, Wei & Lai, Judy & Marnay, Chris, 2014. "Optimal deployment of thermal energy storage under diverse economic and climate conditions," Applied Energy, Elsevier, vol. 119(C), pages 488-496.
    9. Tran, Thomas T.D. & Smith, Amanda D., 2018. "Incorporating performance-based global sensitivity and uncertainty analysis into LCOE calculations for emerging renewable energy technologies," Applied Energy, Elsevier, vol. 216(C), pages 157-171.
    10. Zhu, Kai & Li, Xueqiang & Campana, Pietro Elia & Li, Hailong & Yan, Jinyue, 2018. "Techno-economic feasibility of integrating energy storage systems in refrigerated warehouses," Applied Energy, Elsevier, vol. 216(C), pages 348-357.
    11. Abdon, Andreas & Zhang, Xiaojin & Parra, David & Patel, Martin K. & Bauer, Christian & Worlitschek, Jörg, 2017. "Techno-economic and environmental assessment of stationary electricity storage technologies for different time scales," Energy, Elsevier, vol. 139(C), pages 1173-1187.
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