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A useable multi-level BESSs sizing model for low-level data accessibility with risk assessment application under marketization and high uncertainties

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  • Alizadeh, Ali
  • Esfahani, Moein
  • Kamwa, Innocent
  • Moeini, Ali
  • Mohseni-Bonab, Seyed Masoud

Abstract

The applications and advantages of Battery Energy Storage Systems (BESSs) are noticeable. However, the financial aspects of BESS still require further clarifications for investors to encourage them to size BESS more than before. The uncertain prices, the impact of installed capacity of generation/demand on profit, income sources, and the degradation of BESS are the primary factors that make the financial analysis of BESS more challenging. Additionally, investors' ability to develop an accurate sizing model is hampered by low-level data accessibility. This paper presents a multi-level sizing model for investors using available public data. The sizing problem and operational constraints of BESS have been modeled at the upper levels, while the lower levels present the capacity, day-ahead, real-time, and reserve markets. The uncertainties of prices and capacities are also considered with the risk assessment application using the Conditional Value at Risk (CVAR) index. Furthermore, a new linear degradation and replacement model is developed using a novel linear recursive function to capture the impact of BESS degradation. Implementations revealed that considering various markets can improve the net present value (NPV) at least by 5.31%. Besides, the proposed degradation and replacement model can improve the NPV and rate of return (ROR) by 6.64% and 33.65%, respectively.

Suggested Citation

  • Alizadeh, Ali & Esfahani, Moein & Kamwa, Innocent & Moeini, Ali & Mohseni-Bonab, Seyed Masoud, 2024. "A useable multi-level BESSs sizing model for low-level data accessibility with risk assessment application under marketization and high uncertainties," Energy, Elsevier, vol. 290(C).
    • Handle: RePEc:eee:energy:v:290:y:2024:i:c:s0360544223033467
    DOI: 10.1016/j.energy.2023.129952
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