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Recent techniques to model uncertainties in power generation from renewable energy sources and loads in microgrids – A review

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  • Kumar, K. Prakash
  • Saravanan, B.

Abstract

Renewable energy, particularly solar and wind energies are associated with high degree of uncertainty due to climatic conditions. A proper modelling and analytical treatment of these uncertainties play a key role in taking operational and financial decisions by the microgrid operator. A number of models are proposed and tested successfully in literature to model these energy uncertainties. This article presents a survey of some of the latest analytical and approximation techniques reported in literature to model the uncertainties in microgrid environment. The article mainly focuses on the methods which are applied in particular to the study of uncertainties in Renewable energy availability, heat demand and load demand. Different models, their main features, relative merits and demerits, application in literature, etc are reviewed and presented in form of a table for a quick view. The review shows the inadequacy of uncertainty modelling methods applicable to Renewable sources, both in terms of number and accuracy. It also envisages the scope and need for more flexible models for specific applications.

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  • Kumar, K. Prakash & Saravanan, B., 2017. "Recent techniques to model uncertainties in power generation from renewable energy sources and loads in microgrids – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 348-358.
    • Handle: RePEc:eee:rensus:v:71:y:2017:i:c:p:348-358
    DOI: 10.1016/j.rser.2016.12.063
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    14. Mansouri, S.A. & Ahmarinejad, A. & Nematbakhsh, E. & Javadi, M.S. & Esmaeel Nezhad, A. & Catalão, J.P.S., 2022. "A sustainable framework for multi-microgrids energy management in automated distribution network by considering smart homes and high penetration of renewable energy resources," Energy, Elsevier, vol. 245(C).
    15. Qiu, Haifeng & Gu, Wei & Liu, Pengxiang & Sun, Qirun & Wu, Zhi & Lu, Xi, 2022. "Application of two-stage robust optimization theory in power system scheduling under uncertainties: A review and perspective," Energy, Elsevier, vol. 251(C).
    16. Konneh, Keifa Vamba & Masrur, Hasan & Konneh, David A. & Senjyu, Tomonobu, 2022. "Independent or complementary power system configuration: A decision making approach for sustainable electrification of an urban environment in Sierra Leone," Energy, Elsevier, vol. 239(PD).
    17. Md Shafiul Alam & Fahad Saleh Al-Ismail & Mohammad Ali Abido, 2021. "PV/Wind-Integrated Low-Inertia System Frequency Control: PSO-Optimized Fractional-Order PI-Based SMES Approach," Sustainability, MDPI, vol. 13(14), pages 1-21, July.
    18. Hasan, Kazi Nazmul & Preece, Robin & Milanović, Jovica V., 2019. "Existing approaches and trends in uncertainty modelling and probabilistic stability analysis of power systems with renewable generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 168-180.
    19. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
    20. Tapia, John Frederick D., 2021. "Optimal synthesis of multi-product energy systems under neutrosophic environment," Energy, Elsevier, vol. 229(C).
    21. Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.
    22. Qiu, Haifeng & Gu, Wei & Pan, Jing & Xu, Bin & Xu, Yinliang & Fan, Miao & Wu, Zhi, 2018. "Multi-interval-uncertainty constrained robust dispatch for AC/DC hybrid microgrids with dynamic energy storage degradation," Applied Energy, Elsevier, vol. 228(C), pages 205-214.
    23. Jianxiao Wang & Liudong Chen & Zhenfei Tan & Ershun Du & Nian Liu & Jing Ma & Mingyang Sun & Canbing Li & Jie Song & Xi Lu & Chin-Woo Tan & Guannan He, 2023. "Inherent spatiotemporal uncertainty of renewable power in China," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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