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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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    1. Rodrigues, Daniel L. & Ye, Xianming & Xia, Xiaohua & Zhu, Bing, 2020. "Battery energy storage sizing optimisation for different ownership structures in a peer-to-peer energy sharing community," Applied Energy, Elsevier, vol. 262(C).
    2. Richard Kinley, 2017. "Climate change after Paris: from turning point to transformation," Climate Policy, Taylor & Francis Journals, vol. 17(1), pages 9-15, January.
    3. Mohseni-Bonab, Seyed Masoud & Kamwa, Innocent & Rabiee, Abbas & Chung, C.Y., 2022. "Stochastic optimal transmission Switching: A novel approach to enhance power grid security margins through vulnerability mitigation under renewables uncertainties," Applied Energy, Elsevier, vol. 305(C).
    4. Mohseni-Bonab, Seyed Masoud & Rabiee, Abbas & Mohammadi-Ivatloo, Behnam, 2016. "Voltage stability constrained multi-objective optimal reactive power dispatch under load and wind power uncertainties: A stochastic approach," Renewable Energy, Elsevier, vol. 85(C), pages 598-609.
    5. Mishra, Partha Pratim & Latif, Aadil & Emmanuel, Michael & Shi, Ying & McKenna, Killian & Smith, Kandler & Nagarajan, Adarsh, 2020. "Analysis of degradation in residential battery energy storage systems for rate-based use-cases," Applied Energy, Elsevier, vol. 264(C).
    6. Zhao, Haoran & Wu, Qiuwei & Hu, Shuju & Xu, Honghua & Rasmussen, Claus Nygaard, 2015. "Review of energy storage system for wind power integration support," Applied Energy, Elsevier, vol. 137(C), pages 545-553.
    7. Johnston, Lewis & Díaz-González, Francisco & Gomis-Bellmunt, Oriol & Corchero-García, Cristina & Cruz-Zambrano, Miguel, 2015. "Methodology for the economic optimisation of energy storage systems for frequency support in wind power plants," Applied Energy, Elsevier, vol. 137(C), pages 660-669.
    8. Koskela, Juha & Rautiainen, Antti & Järventausta, Pertti, 2019. "Using electrical energy storage in residential buildings – Sizing of battery and photovoltaic panels based on electricity cost optimization," Applied Energy, Elsevier, vol. 239(C), pages 1175-1189.
    9. Liu, Ye & Wu, Xiaogang & Du, Jiuyu & Song, Ziyou & Wu, Guoliang, 2020. "Optimal sizing of a wind-energy storage system considering battery life," Renewable Energy, Elsevier, vol. 147(P1), pages 2470-2483.
    10. Antonio J. Conejo & Miguel Carrión & Juan M. Morales, 2010. "Decision Making Under Uncertainty in Electricity Markets," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7421-1, April.
    11. Jiang, Xin & Jin, Yang & Zheng, Xueyuan & Hu, Guobao & Zeng, Qingshan, 2020. "Optimal configuration of grid-side battery energy storage system under power marketization," Applied Energy, Elsevier, vol. 272(C).
    12. Frazier, A. Will & Cole, Wesley & Denholm, Paul & Greer, Daniel & Gagnon, Pieter, 2020. "Assessing the potential of battery storage as a peaking capacity resource in the United States," Applied Energy, Elsevier, vol. 275(C).
    13. Icaza-Alvarez, Daniel & Jurado, Francisco & Tostado-Véliz, Marcos & Arevalo, Paúl, 2022. "Decarbonization of the Galapagos Islands. Proposal to transform the energy system into 100% renewable by 2050," Renewable Energy, Elsevier, vol. 189(C), pages 199-220.
    14. Dorahaki, Sobhan & Rashidinejad, Masoud & Fatemi Ardestani, Seyed Farshad & Abdollahi, Amir & Salehizadeh, Mohammad Reza, 2023. "An integrated model for citizen energy communities and renewable energy communities based on clean energy package: A two-stage risk-based approach," Energy, Elsevier, vol. 277(C).
    15. Novoa, Laura & Flores, Robert & Brouwer, Jack, 2019. "Optimal renewable generation and battery storage sizing and siting considering local transformer limits," Applied Energy, Elsevier, vol. 256(C).
    16. Jannesar, Mohammad Rasol & Sedighi, Alireza & Savaghebi, Mehdi & Guerrero, Josep M., 2018. "Optimal placement, sizing, and daily charge/discharge of battery energy storage in low voltage distribution network with high photovoltaic penetration," Applied Energy, Elsevier, vol. 226(C), pages 957-966.
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