IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i16p6089-d1221617.html
   My bibliography  Save this article

Robust Multiobjective Decision Making in the Acquisition of Energy Assets

Author

Listed:
  • Rafael Bambirra

    (Programa de pós Graduação em Engenharia Elétrica, Universidade Federal de Minas Gerais—UFMG, Belo Horizonte 31270-901, Brazil
    ASOTECH, Belo Horizonte 30535-630, Brazil)

  • Lais Schiavo

    (ENACOM, Belo Horizonte 31275-100, Brazil)

  • Marina Lima

    (ENACOM, Belo Horizonte 31275-100, Brazil)

  • Giovanna Miranda

    (ENACOM, Belo Horizonte 31275-100, Brazil)

  • Iolanda Reis

    (Aliança Energia, Belo Horizonte 30170-050, Brazil)

  • Michael Cassemiro

    (Aliança Energia, Belo Horizonte 30170-050, Brazil)

  • Antônio Andrade

    (Aliança Energia, Belo Horizonte 30170-050, Brazil)

  • Fernanda Laender

    (Aliança Energia, Belo Horizonte 30170-050, Brazil)

  • Rafael Silva

    (VALE, Nova Lima 34000-000, Brazil)

  • Douglas Vieira

    (ENACOM, Belo Horizonte 31275-100, Brazil)

  • Petr Ekel

    (ASOTECH, Belo Horizonte 30535-630, Brazil
    Programa de pós Graduação em Informática, Pontifícia Universidade Católica de Minas Gerais—PUC/MG, Belo Horizonte 30535-901, Brazil)

Abstract

In asset management for energy portfolios, quantitative methodologies are typically employed. In Brazil, the NEWAVE computational model is universally used to generate scenarios of hydraulic production and future prices, which result in revenue distributions. These distributions are then used to estimate the portfolio’s revenue and assess its risk. Although this is a well-established analysis, it has some shortcomings that are not always considered. The validity of the revenue series constructed by NEWAVE, especially in long-term analysis, is a real problem for agents concerning the acquisition of assets such as power plants. Another issue is the disregard for other objectives that are important for the operationality of the management task and are often ignored, such as operational risk. To address these limitations, this work combines the areas of multicriteria decision making under uncertainty and risk management and presents a methodology for evaluating the acquisition of long-term energy assets, as well as a practical application of the proposed method. Investment alternatives are evaluated in multiple developed scenarios, so it is possible to measure how robust a given option is. By analyzing several scenarios simultaneously, a larger region of uncertainties can be covered, and therefore, decision making becomes more secure. The proposed methodology includes six objectives, designed to address a wider range of stakeholder needs. This approach is applied to an illustrative portfolio, producing results that allow for a more comprehensive understanding of decision attributes. Therefore, this work not only addresses the current limitations in the field but also adds an original contribution by considering simultaneously several scenarios and integrating multiple objectives in a robust and secure decision-making framework.

Suggested Citation

  • Rafael Bambirra & Lais Schiavo & Marina Lima & Giovanna Miranda & Iolanda Reis & Michael Cassemiro & Antônio Andrade & Fernanda Laender & Rafael Silva & Douglas Vieira & Petr Ekel, 2023. "Robust Multiobjective Decision Making in the Acquisition of Energy Assets," Energies, MDPI, vol. 16(16), pages 1-21, August.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:16:p:6089-:d:1221617
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/16/6089/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/16/6089/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pérez Odeh, Rodrigo & Watts, David & Negrete-Pincetic, Matías, 2018. "Portfolio applications in electricity markets review: Private investor and manager perspective trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 192-204.
    2. Gökgöz, Fazıl & Atmaca, Mete Emin, 2017. "Portfolio optimization under lower partial moments in emerging electricity markets: Evidence from Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 437-449.
    3. de Freitas, Renan Alves & Vogel, Ederson Paulo & Korzenowski, André Luis & Oliveira Rocha, Luiz Alberto, 2020. "Stochastic model to aid decision making on investments in renewable energy generation: Portfolio diffusion and investor risk aversion," Renewable Energy, Elsevier, vol. 162(C), pages 1161-1176.
    4. Sadeghi, Mehdi & Shavvalpour, Saeed, 2006. "Energy risk management and value at risk modeling," Energy Policy, Elsevier, vol. 34(18), pages 3367-3373, December.
    5. Zorana Božić & Dušan Dobromirov & Jovana Arsić & Mladen Radišić & Beata Ślusarczyk, 2020. "Power Exchange Prices: Comparison of Volatility in European Markets," Energies, MDPI, vol. 13(21), pages 1-15, October.
    6. Weron, Rafal, 2000. "Energy price risk management," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(1), pages 127-134.
    7. Ilbahar, Esra & Kahraman, Cengiz & Cebi, Selcuk, 2022. "Risk assessment of renewable energy investments: A modified failure mode and effect analysis based on prospect theory and intuitionistic fuzzy AHP," Energy, Elsevier, vol. 239(PA).
    8. Bradshaw, Amanda, 2017. "Regulatory change and innovation in Latin America: The case of renewable energy in Brazil," Utilities Policy, Elsevier, vol. 49(C), pages 156-164.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Mingming & Song, Wenwen & Liu, Liyun & Zhou, Dequn, 2024. "Optimal investment portfolio strategy for carbon neutrality of power enterprises," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    2. Emanuel Canelas & Tânia Pinto-Varela & Bartosz Sawik, 2020. "Electricity Portfolio Optimization for Large Consumers: Iberian Electricity Market Case Study," Energies, MDPI, vol. 13(9), pages 1-21, May.
    3. Wenjiao Zai & Yuying He & Huazhang Wang, 2023. "Risk Prediction Method for Renewable Energy Investments Abroad Based on Cloud-DBN," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
    4. Lavička, Hynek & Kracík, Jiří, 2020. "Fluctuation analysis of electric power loads in Europe: Correlation multifractality vs. Distribution function multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    5. Liu, Xinglei & Liu, Jun & Ren, Kezheng & Liu, Xiaoming & Liu, Jiacheng, 2022. "An integrated fuzzy multi-energy transaction evaluation approach for energy internet markets considering judgement credibility and variable rough precision," Energy, Elsevier, vol. 261(PB).
    6. Rafał Weron, 2009. "Heavy-tails and regime-switching in electricity prices," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 457-473, July.
    7. Kanwal Iqbal Khan & Syed M. Waqar Azeem Naqvi & Muhammad Mudassar Ghafoor & Rana Shahid Imdad Akash, 2020. "Sustainable Portfolio Optimization with Higher-Order Moments of Risk," Sustainability, MDPI, vol. 12(5), pages 1-14, March.
    8. Wang, Yudong & Wu, Chongfeng & Wei, Yu, 2011. "Can GARCH-class models capture long memory in WTI crude oil markets?," Economic Modelling, Elsevier, vol. 28(3), pages 921-927, May.
    9. Swidan, Hassan & Merkert, Rico & Kwon, Oh Kang, 2019. "Designing optimal jet fuel hedging strategies for airlines – Why hedging will not always reduce risk exposure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 20-36.
    10. Tinta, Abdoulganiour Almame, 2023. "Energy substitution in Africa: Cross-regional differentiation effects," Energy, Elsevier, vol. 263(PA).
    11. Fan, Ying & Zhang, Yue-Jun & Tsai, Hsien-Tang & Wei, Yi-Ming, 2008. "Estimating 'Value at Risk' of crude oil price and its spillover effect using the GED-GARCH approach," Energy Economics, Elsevier, vol. 30(6), pages 3156-3171, November.
    12. Lisi, Francesco & Grossi, Luigi & Quaglia, Federico, 2023. "Evaluation of Cost-at-Risk related to the procurement of resources in the ancillary services market. The case of the Italian electricity market," Energy Economics, Elsevier, vol. 121(C).
    13. Ana Rita Silva & Ana Estanqueiro, 2022. "From Wind to Hybrid: A Contribution to the Optimal Design of Utility-Scale Hybrid Power Plants," Energies, MDPI, vol. 15(7), pages 1-19, April.
    14. Aloui, Chaker & Mabrouk, Samir, 2010. "Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models," Energy Policy, Elsevier, vol. 38(5), pages 2326-2339, May.
    15. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    16. Khaki, Audil & Prasad, Mason & Al-Mohamad, Somar & Bakry, Walid & Vo, Xuan Vinh, 2023. "Re-evaluating portfolio diversification and design using cryptocurrencies: Are decentralized cryptocurrencies enough?," Research in International Business and Finance, Elsevier, vol. 64(C).
    17. Kang, Sang Hoon & Kang, Sang-Mok & Yoon, Seong-Min, 2009. "Forecasting volatility of crude oil markets," Energy Economics, Elsevier, vol. 31(1), pages 119-125, January.
    18. Xiao, Dongliang & Lin, Zhenjia & Chen, Haoyong & Hua, Weiqi & Yan, Jinyue, 2024. "Windfall profit-aware stochastic scheduling strategy for industrial virtual power plant with integrated risk-seeking/averse preferences," Applied Energy, Elsevier, vol. 357(C).
    19. Kamimura, A. & Guerra, S.M.G., 2001. "Economic fluctuations and possible non-linear relations between macroeconomic variables for Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 291(1), pages 542-552.
    20. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:16:p:6089-:d:1221617. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.