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Levelized income loss as a metric of the adaptation of wind and energy storage to variable prices

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  • Díaz, Guzmán
  • Coto, José
  • Gómez-Aleixandre, Javier

Abstract

Classifying and categorizing generators according to their financial efficiency is necessary to compare the degree of competitiveness of a generating technology. The levelized cost of energy (LCoE) is arguably the most relevant index for that purpose. It relates the capital and operating expenses to the expected energy output, to encapsulate the financial efficiency into an €/MWh. It is technology-independent, meaning that it can be used for comparing different generator types in a fair basis. However, the LCoE is defined to provide a cost figure under the assumption of a fixed-tariff. It does not make any difference when comparing the performance of an intermittent generating technology in different spot markets. The LCoE does not inherently account for the variability of prices.

Suggested Citation

  • Díaz, Guzmán & Coto, José & Gómez-Aleixandre, Javier, 2019. "Levelized income loss as a metric of the adaptation of wind and energy storage to variable prices," Applied Energy, Elsevier, vol. 238(C), pages 1179-1191.
    • Handle: RePEc:eee:appene:v:238:y:2019:i:c:p:1179-1191
    DOI: 10.1016/j.apenergy.2019.01.169
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    as
    1. Vijay, Avinash & Fouquet, Nicolas & Staffell, Iain & Hawkes, Adam, 2017. "The value of electricity and reserve services in low carbon electricity systems," Applied Energy, Elsevier, vol. 201(C), pages 111-123.
    2. Pietzcker, Robert Carl & Stetter, Daniel & Manger, Susanne & Luderer, Gunnar, 2014. "Using the sun to decarbonize the power sector: The economic potential of photovoltaics and concentrating solar power," Applied Energy, Elsevier, vol. 135(C), pages 704-720.
    3. Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September.
    4. Dressler, Luisa, 2016. "Support schemes for renewable electricity in the European Union: Producer strategies and competition," Energy Economics, Elsevier, vol. 60(C), pages 186-196.
    5. Lai, Chun Sing & McCulloch, Malcolm D., 2017. "Levelized cost of electricity for solar photovoltaic and electrical energy storage," Applied Energy, Elsevier, vol. 190(C), pages 191-203.
    6. Díaz, Guzmán & Gómez-Aleixandre, Javier & Coto, José, 2016. "Wind power scenario generation through state-space specifications for uncertainty analysis of wind power plants," Applied Energy, Elsevier, vol. 162(C), pages 21-30.
    7. Brouwer, Anne Sjoerd & van den Broek, Machteld & Zappa, William & Turkenburg, Wim C. & Faaij, André, 2016. "Least-cost options for integrating intermittent renewables in low-carbon power systems," Applied Energy, Elsevier, vol. 161(C), pages 48-74.
    8. Kapsali, M. & Kaldellis, J.K. & Anagnostopoulos, J.S., 2016. "Investigating the techno-economic perspectives of high wind energy production in remote vs interconnected island networks," Applied Energy, Elsevier, vol. 173(C), pages 238-254.
    9. 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.
    10. Ueckerdt, Falko & Hirth, Lion & Luderer, Gunnar & Edenhofer, Ottmar, 2013. "System LCOE: What are the costs of variable renewables?," Energy, Elsevier, vol. 63(C), pages 61-75.
    11. Feng, Ju & Shen, Wen Zhong, 2017. "Design optimization of offshore wind farms with multiple types of wind turbines," Applied Energy, Elsevier, vol. 205(C), pages 1283-1297.
    12. Petitet, Marie & Finon, Dominique & Janssen, Tanguy, 2017. "Capacity adequacy in power markets facing energy transition: A comparison of scarcity pricing and capacity mechanism," Energy Policy, Elsevier, vol. 103(C), pages 30-46.
    13. Newbery, David M., 2016. "Towards a green energy economy? The EU Energy Union’s transition to a low-carbon zero subsidy electricity system – Lessons from the UK’s Electricity Market Reform," Applied Energy, Elsevier, vol. 179(C), pages 1321-1330.
    14. Bennedsen, Mikkel, 2017. "A rough multi-factor model of electricity spot prices," Energy Economics, Elsevier, vol. 63(C), pages 301-313.
    15. Hull, John & White, Alan, 1990. "Pricing Interest-Rate-Derivative Securities," The Review of Financial Studies, Society for Financial Studies, vol. 3(4), pages 573-592.
    16. Nowotarski, Jakub & Weron, Rafał, 2016. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting," Energy Economics, Elsevier, vol. 57(C), pages 228-235.
    17. Díaz, Guzmán & Moreno, Blanca & Coto, José & Gómez-Aleixandre, Javier, 2015. "Valuation of wind power distributed generation by using Longstaff–Schwartz option pricing method," Applied Energy, Elsevier, vol. 145(C), pages 223-233.
    18. Lund, Peter D. & Lindgren, Juuso & Mikkola, Jani & Salpakari, Jyri, 2015. "Review of energy system flexibility measures to enable high levels of variable renewable electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 785-807.
    19. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
    20. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    21. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    22. Pircalabu, A. & Benth, F.E., 2017. "A regime-switching copula approach to modeling day-ahead prices in coupled electricity markets," Energy Economics, Elsevier, vol. 68(C), pages 283-302.
    23. Ritter, Matthias & Deckert, Lars, 2017. "Site assessment, turbine selection, and local feed-in tariffs through the wind energy index," Applied Energy, Elsevier, vol. 185(P2), pages 1087-1099.
    24. Yukseltan, Ergun & Yucekaya, Ahmet & Bilge, Ayse Humeyra, 2017. "Forecasting electricity demand for Turkey: Modeling periodic variations and demand segregation," Applied Energy, Elsevier, vol. 193(C), pages 287-296.
    25. Edenhofer, Ottmar & Hirth, Lion & Knopf, Brigitte & Pahle, Michael & Schlömer, Steffen & Schmid, Eva & Ueckerdt, Falko, 2013. "On the economics of renewable energy sources," Energy Economics, Elsevier, vol. 40(S1), pages 12-23.
    26. Fred Espen Benth & Jan Kallsen & Thilo Meyer-Brandis, 2007. "A Non-Gaussian Ornstein-Uhlenbeck Process for Electricity Spot Price Modeling and Derivatives Pricing," Applied Mathematical Finance, Taylor & Francis Journals, vol. 14(2), pages 153-169.
    27. Hirth, Lion, 2016. "The benefits of flexibility: The value of wind energy with hydropower," Applied Energy, Elsevier, vol. 181(C), pages 210-223.
    28. Wiser, Ryan & Bolinger, Mark & Heath, Garvin & Keyser, David & Lantz, Eric & Macknick, Jordan & Mai, Trieu & Millstein, Dev, 2016. "Long-term implications of sustained wind power growth in the United States: Potential benefits and secondary impacts," Applied Energy, Elsevier, vol. 179(C), pages 146-158.
    29. Hou, Peng & Enevoldsen, Peter & Hu, Weihao & Chen, Cong & Chen, Zhe, 2017. "Offshore wind farm repowering optimization," Applied Energy, Elsevier, vol. 208(C), pages 834-844.
    30. Ritter, Matthias & Shen, Zhiwei & López Cabrera, Brenda & Odening, Martin & Deckert, Lars, 2015. "Designing an index for assessing wind energy potential," Renewable Energy, Elsevier, vol. 83(C), pages 416-424.
    31. Serrano González, Javier & Trigo García, Ángel Luis & Burgos Payán, Manuel & Riquelme Santos, Jesús & González Rodríguez, Ángel Gaspar, 2017. "Optimal wind-turbine micro-siting of offshore wind farms: A grid-like layout approach," Applied Energy, Elsevier, vol. 200(C), pages 28-38.
    32. Woo, C.K. & Moore, J. & Schneiderman, B. & Ho, T. & Olson, A. & Alagappan, L. & Chawla, K. & Toyama, N. & Zarnikau, J., 2016. "Merit-order effects of renewable energy and price divergence in California’s day-ahead and real-time electricity markets," Energy Policy, Elsevier, vol. 92(C), pages 299-312.
    33. del Río, Pablo & Resch, Gustav & Ortner, Andre & Liebmann, Lukas & Busch, Sebastian & Panzer, Christian, 2017. "A techno-economic analysis of EU renewable electricity policy pathways in 2030," Energy Policy, Elsevier, vol. 104(C), pages 484-493.
    34. Lantz, Eric & Mai, Trieu & Wiser, Ryan H. & Krishnan, Venkat, 2016. "Long-term implications of sustained wind power growth in the United States: Direct electric system impacts and costs," Applied Energy, Elsevier, vol. 179(C), pages 832-846.
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