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Estimating revenues from offshore wind-storage systems: The importance of advanced battery models

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  • Jafari, Mehdi
  • Botterud, Audun
  • Sakti, Apurba

Abstract

We investigate six different lithium-ion battery modeling approaches to highlight the importance of accurately representing batteries in decision tools. Advanced mixed-integer-linear battery models account for efficiencies as a function of the discharge power, power-limits as a function of the state-of-charge, along with degradation, which are usually not accounted for in power systems models. The revenue potential from offshore wind paired with battery systems is then examined using the more advanced representation where degradation is the sum of the capacity fades resulting from calendar- and cycle-aging. The impacts of variability of offshore wind output along with energy- and capacity-market prices are evaluated using publicly available data from 2010 to 2013 using NYISO as a test case. For 2013, results highlight that without accurate battery representations, models can overestimate battery revenues by up to 35%, resulting primarily from degradation-tied costs. Advanced dispatch algorithms that account for calendar- and cycle-aging of the battery can help operate the battery more efficiently. Locating the battery onshore yields higher revenues and with wider useable SOC windows, it is possible to monetize higher arbitrage opportunities, which can compensate for any additional degradation-tied costs. The added value of a MWh of energy storage varies from $2 to $4.5 per MWh of wind energy, which leads to a breakeven cost range of $50–115 per kWh for the battery systems. As such, energy- and capacity-market revenues were found to be insufficient in recovering the investment costs of current battery systems for the applications considered in this analysis.

Suggested Citation

  • Jafari, Mehdi & Botterud, Audun & Sakti, Apurba, 2020. "Estimating revenues from offshore wind-storage systems: The importance of advanced battery models," Applied Energy, Elsevier, vol. 276(C).
  • Handle: RePEc:eee:appene:v:276:y:2020:i:c:s0306261920309296
    DOI: 10.1016/j.apenergy.2020.115417
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    4. Jafari, Mehdi & Botterud, Audun & Sakti, Apurba, 2022. "Decarbonizing power systems: A critical review of the role of energy storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    5. Mao, Jiachen & Jafari, Mehdi & Botterud, Audun, 2022. "Planning low-carbon distributed power systems: Evaluating the role of energy storage," Energy, Elsevier, vol. 238(PA).
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    7. Li, Ming & Luo, Haojie & Zhou, Shijie & Senthil Kumar, Gokula Manikandan & Guo, Xinman & Law, Tin Chung & Cao, Sunliang, 2022. "State-of-the-art review of the flexibility and feasibility of emerging offshore and coastal ocean energy technologies in East and Southeast Asia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    8. Bompard, Ettore & Ciocia, Alessandro & Grosso, Daniele & Huang, Tao & Spertino, Filippo & Jafari, Mehdi & Botterud, Audun, 2022. "Assessing the role of fluctuating renewables in energy transition: Methodologies and tools," Applied Energy, Elsevier, vol. 314(C).
    9. Baldi, Francesco & Coraddu, Andrea & Kalikatzarakis, Miltiadis & Jeleňová, Diana & Collu, Maurizio & Race, Julia & Maréchal, François, 2022. "Optimisation-based system designs for deep offshore wind farms including power to gas technologies," Applied Energy, Elsevier, vol. 310(C).
    10. Vykhodtsev, Anton V. & Jang, Darren & Wang, Qianpu & Rosehart, William & Zareipour, Hamidreza, 2022. "A review of modelling approaches to characterize lithium-ion battery energy storage systems in techno-economic analyses of power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).

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