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A real option-based simulation model to evaluate investments in pump storage plants

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  • Muche, Thomas

Abstract

Investments in pump storage plants are expected to grow especially due to their ability to store an excess of supply from wind power plants. In order to evaluate these investments correctly the peculiarities of pump storage plants and the characteristics of liberalized power markets have to be considered. The main characteristics of power markets are the strong power price volatility and the occurrence of prices spikes. In this article a valuation model is developed capturing these aspects using power price simulation, optimization of unit commitment and capital market theory. This valuation model is able to value a future price-based unit commitment planning that corresponds to future scope of actions also called real options. The resulting real option value for the pump storage plant is compared with the traditional net present value approach. Because this approach is not able to evaluate scope of actions correctly it results in strongly smaller investment values and forces wrong investment decisions.

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  • Muche, Thomas, 2009. "A real option-based simulation model to evaluate investments in pump storage plants," Energy Policy, Elsevier, vol. 37(11), pages 4851-4862, November.
    • Handle: RePEc:eee:enepol:v:37:y:2009:i:11:p:4851-4862
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    2. Steffen, Bjarne & Weber, Christoph, 2016. "Optimal operation of pumped-hydro storage plants with continuous time-varying power prices," European Journal of Operational Research, Elsevier, vol. 252(1), pages 308-321.
    3. Muche, Thomas, 2014. "Optimal operation and forecasting policy for pump storage plants in day-ahead markets," Applied Energy, Elsevier, vol. 113(C), pages 1089-1099.
    4. Gaudard, Ludovic, 2015. "Pumped-storage project: A short to long term investment analysis including climate change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 91-99.
    5. Locatelli, Giorgio & Mancini, Mauro & Lotti, Giovanni, 2020. "A simple-to-implement real options method for the energy sector," Energy, Elsevier, vol. 197(C).
    6. Kroniger, Daniel & Madlener, Reinhard, 2014. "Hydrogen storage for wind parks: A real options evaluation for an optimal investment in more flexibility," Applied Energy, Elsevier, vol. 136(C), pages 931-946.
    7. Rious, Vincent & Perez, Yannick, 2014. "Review of supporting scheme for island powersystem storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 754-765.
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    9. Zvonimir Glasnovic & Karmen Margeta & Visnja Omerbegovic, 2013. "Artificial Water Inflow Created by Solar Energy for Continuous Green Energy Production," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2303-2323, May.
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    11. Moon, Yongma & Baran, Mesut, 2018. "Economic analysis of a residential PV system from the timing perspective: A real option model," Renewable Energy, Elsevier, vol. 125(C), pages 783-795.
    12. David Wozabal & Christoph Graf & David Hirschmann, 2016. "The effect of intermittent renewables on the electricity price variance," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(3), pages 687-709, July.
    13. McPherson, Madeleine & Tahseen, Samiha, 2018. "Deploying storage assets to facilitate variable renewable energy integration: The impacts of grid flexibility, renewable penetration, and market structure," Energy, Elsevier, vol. 145(C), pages 856-870.
    14. Feldman, David & Jones-Albertus, Rebecca & Margolis, Robert, 2020. "Quantifying the impact of R&D on PV project financing costs," Energy Policy, Elsevier, vol. 142(C).
    15. Locatelli, Giorgio & Invernizzi, Diletta Colette & Mancini, Mauro, 2016. "Investment and risk appraisal in energy storage systems: A real options approach," Energy, Elsevier, vol. 104(C), pages 114-131.
    16. Abadie, Luis M. & Goicoechea, Nestor, 2022. "Optimal management of a mega pumped hydro storage system under stochastic hourly electricity prices in the Iberian Peninsula," Energy, Elsevier, vol. 252(C).
    17. Keles, Dogan & Scelle, Jonathan & Paraschiv, Florentina & Fichtner, Wolf, 2016. "Extended forecast methods for day-ahead electricity spot prices applying artificial neural networks," Applied Energy, Elsevier, vol. 162(C), pages 218-230.
    18. Mesias Alfeus & James Collins, 2023. "A novel stochastic modeling framework for coal production and logistics through options pricing analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-19, December.
    19. Connolly, D. & Lund, H. & Finn, P. & Mathiesen, B.V. & Leahy, M., 2011. "Practical operation strategies for pumped hydroelectric energy storage (PHES) utilising electricity price arbitrage," Energy Policy, Elsevier, vol. 39(7), pages 4189-4196, July.
    20. Yongma Moon, 2014. "Optimal Time to Invest Energy Storage System under Uncertainty Conditions," Energies, MDPI, vol. 7(4), pages 1-19, April.
    21. Daniel Ziegler & Katrin Schmitz & Christoph Weber, 2012. "Optimal electricity generation portfolios," Computational Management Science, Springer, vol. 9(3), pages 381-399, August.
    22. He, YongXiu & Liu, Yang & Li, MoXing & Zhang, Yan, 2022. "Benefit evaluation and mechanism design of pumped storage plants under the background of power market reform - A case study of China," Renewable Energy, Elsevier, vol. 191(C), pages 796-806.

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