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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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    1. Li, Yanfu & Zio, Enrico, 2012. "Uncertainty analysis of the adequacy assessment model of a distributed generation system," Renewable Energy, Elsevier, vol. 41(C), pages 235-244.
    2. Mohammadi, Sirus & Mozafari, Babak & Solimani, Soodabeh & Niknam, Taher, 2013. "An Adaptive Modified Firefly Optimisation Algorithm based on Hong's Point Estimate Method to optimal operation management in a microgrid with consideration of uncertainties," Energy, Elsevier, vol. 51(C), pages 339-348.
    3. Mallol-Poyato, R. & Salcedo-Sanz, S. & Jiménez-Fernández, S. & Díaz-Villar, P., 2015. "Optimal discharge scheduling of energy storage systems in MicroGrids based on hyper-heuristics," Renewable Energy, Elsevier, vol. 83(C), pages 13-24.
    4. Baziar, Aliasghar & Kavousi-Fard, Abdollah, 2013. "Considering uncertainty in the optimal energy management of renewable micro-grids including storage devices," Renewable Energy, Elsevier, vol. 59(C), pages 158-166.
    5. Canizes, Bruno & Soares, João & Vale, Zita & Khodr, H.M., 2012. "Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems," Energy, Elsevier, vol. 45(1), pages 1007-1017.
    6. Edmund K Burke & Michel Gendreau & Matthew Hyde & Graham Kendall & Gabriela Ochoa & Ender Özcan & Rong Qu, 2013. "Hyper-heuristics: a survey of the state of the art," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(12), pages 1695-1724, December.
    7. Soares, João & Fotouhi Ghazvini, Mohammad Ali & Vale, Zita & de Moura Oliveira, P.B., 2016. "A multi-objective model for the day-ahead energy resource scheduling of a smart grid with high penetration of sensitive loads," Applied Energy, Elsevier, vol. 162(C), pages 1074-1088.
    8. Niknam, Taher & Golestaneh, Faranak & Malekpour, Ahmadreza, 2012. "Probabilistic energy and operation management of a microgrid containing wind/photovoltaic/fuel cell generation and energy storage devices based on point estimate method and self-adaptive gravitational," Energy, Elsevier, vol. 43(1), pages 427-437.
    9. Basu, Ashoke Kumar & Chowdhury, S.P. & Chowdhury, S. & Paul, S., 2011. "Microgrids: Energy management by strategic deployment of DERs—A comprehensive survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4348-4356.
    10. Mohamed Abd el Motaleb, Ahmad & Kazim Bekdache, Sarah & Barrios, Lázaro Alvarado, 2016. "Optimal sizing for a hybrid power system with wind/energy storage based in stochastic environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1149-1158.
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