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How to deal with uncertainties in electric power systems? A review

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  • Jordehi, A. Rezaee

Abstract

In electric power systems, there exist many diverse uncertain parameters such as loads, electricity price, wind power generation and photovoltaic power generation. In power system studies, appropriate modeling and handling of these uncertain parameters is essential. In this paper, the sources of uncertainties in power systems are described and different uncertainty handling methods in power systems are classified and reviewed in details, mentioning the merits and demerits of each method. Based on the conducted review, some directions for future research are delineated.

Suggested Citation

  • Jordehi, A. Rezaee, 2018. "How to deal with uncertainties in electric power systems? A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 145-155.
    • Handle: RePEc:eee:rensus:v:96:y:2018:i:c:p:145-155
    DOI: 10.1016/j.rser.2018.07.056
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    1. Zare, Kazem & Moghaddam, Mohsen Parsa & Sheikh El Eslami, Mohammad Kazem, 2010. "Electricity procurement for large consumers based on Information Gap Decision Theory," Energy Policy, Elsevier, vol. 38(1), pages 234-242, January.
    2. Santos, Maria João & Ferreira, Paula & Araújo, Madalena, 2016. "A methodology to incorporate risk and uncertainty in electricity power planning," Energy, Elsevier, vol. 115(P2), pages 1400-1411.
    3. Liu, Fan & Bie, Zhaohong & Liu, Shiyu & Ding, Tao, 2017. "Day-ahead optimal dispatch for wind integrated power system considering zonal reserve requirements," Applied Energy, Elsevier, vol. 188(C), pages 399-408.
    4. Reddy, S. Surender, 2017. "Optimal scheduling of thermal-wind-solar power system with storage," Renewable Energy, Elsevier, vol. 101(C), pages 1357-1368.
    5. Narayan, Apurva & Ponnambalam, Kumaraswamy, 2017. "Risk-averse stochastic programming approach for microgrid planning under uncertainty," Renewable Energy, Elsevier, vol. 101(C), pages 399-408.
    6. Kayal, Partha & Chanda, C.K., 2015. "Optimal mix of solar and wind distributed generations considering performance improvement of electrical distribution network," Renewable Energy, Elsevier, vol. 75(C), pages 173-186.
    7. Brett Korteling & Suraje Dessai & Zoran Kapelan, 2013. "Erratum to: Using Information-Gap Decision Theory for Water Resources Planning Under Severe Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(4), pages 1173-1174, March.
    8. Qingshan Xu & Yifan Ding & Aixia Zheng, 2017. "An Optimal Dispatch Model of Wind-Integrated Power System Considering Demand Response and Reliability," Sustainability, MDPI, vol. 9(5), pages 1-20, May.
    9. Brett Korteling & Suraje Dessai & Zoran Kapelan, 2013. "Using Information-Gap Decision Theory for Water Resources Planning Under Severe Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(4), pages 1149-1172, March.
    10. 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.
    11. Lu, Yuehong & Wang, Shengwei & Yan, Chengchu & Huang, Zhijia, 2017. "Robust optimal design of renewable energy system in nearly/net zero energy buildings under uncertainties," Applied Energy, Elsevier, vol. 187(C), pages 62-71.
    12. Zamani, Ali Ghahgharaee & Zakariazadeh, Alireza & Jadid, Shahram, 2016. "Day-ahead resource scheduling of a renewable energy based virtual power plant," Applied Energy, Elsevier, vol. 169(C), pages 324-340.
    13. Hemmati, Reza & Hooshmand, Rahmat-Allah & Khodabakhshian, Amin, 2014. "Market based transmission expansion and reactive power planning with consideration of wind and load uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 1-10.
    14. Simão, H.P. & Powell, W.B. & Archer, C.L. & Kempton, W., 2017. "The challenge of integrating offshore wind power in the U.S. electric grid. Part II: Simulation of electricity market operations," Renewable Energy, Elsevier, vol. 103(C), pages 418-431.
    15. Kabir, M.N. & Mishra, Y. & Bansal, R.C., 2016. "Probabilistic load flow for distribution systems with uncertain PV generation," Applied Energy, Elsevier, vol. 163(C), pages 343-351.
    16. Yanzhe Hu & Yang Li & Mengjie Xu & Li Zhou & Mingjian Cui, 2017. "A Chance-Constrained Economic Dispatch Model in Wind-Thermal-Energy Storage System," Energies, MDPI, vol. 10(3), pages 1-21, March.
    17. Qingwu Gong & Jiazhi Lei & Hui Qiao & Jingjing Qiu, 2017. "Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution," Sustainability, MDPI, vol. 9(4), pages 1-15, March.
    18. Wu, Weidong & Rao, S.S., 2007. "Uncertainty analysis and allocation of joint tolerances in robot manipulators based on interval analysis," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 54-64.
    19. Mehdizadeh, Ali & Taghizadegan, Navid & Salehi, Javad, 2018. "Risk-based energy management of renewable-based microgrid using information gap decision theory in the presence of peak load management," Applied Energy, Elsevier, vol. 211(C), pages 617-630.
    20. Archer, C.L. & Simão, H.P. & Kempton, W. & Powell, W.B. & Dvorak, M.J., 2017. "The challenge of integrating offshore wind power in the U.S. electric grid. Part I: Wind forecast error," Renewable Energy, Elsevier, vol. 103(C), pages 346-360.
    21. Moradi, Mohammad H. & Eskandari, Mohsen, 2014. "A hybrid method for simultaneous optimization of DG capacity and operational strategy in microgrids considering uncertainty in electricity price forecasting," Renewable Energy, Elsevier, vol. 68(C), pages 697-714.
    22. Soroudi, Alireza & Amraee, Turaj, 2013. "Decision making under uncertainty in energy systems: State of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 376-384.
    23. Aghaei, Jamshid & Nezhad, Ali Esmaeel & Rabiee, Abdorreza & Rahimi, Ehsan, 2016. "Contribution of Plug-in Hybrid Electric Vehicles in power system uncertainty management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 450-458.
    24. Esmaeili, Mobin & Sedighizadeh, Mostafa & Esmaili, Masoud, 2016. "Multi-objective optimal reconfiguration and DG (Distributed Generation) power allocation in distribution networks using Big Bang-Big Crunch algorithm considering load uncertainty," Energy, Elsevier, vol. 103(C), pages 86-99.
    25. Aien, Morteza & Hajebrahimi, Ali & Fotuhi-Firuzabad, Mahmud, 2016. "A comprehensive review on uncertainty modeling techniques in power system studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1077-1089.
    26. Shojaabadi, Saeed & Abapour, Saeed & Abapour, Mehdi & Nahavandi, Ali, 2016. "Simultaneous planning of plug-in hybrid electric vehicle charging stations and wind power generation in distribution networks considering uncertainties," Renewable Energy, Elsevier, vol. 99(C), pages 237-252.
    27. Piao, M.J. & Li, Y.P. & Huang, G.H. & Nie, S., 2015. "Risk analysis for Shanghai's electric power system under multiple uncertainties," Energy, Elsevier, vol. 87(C), pages 104-119.
    28. Moradi-Dalvand, M. & Mohammadi-Ivatloo, B. & Amjady, N. & Zareipour, H. & Mazhab-Jafari, A., 2015. "Self-scheduling of a wind producer based on Information Gap Decision Theory," Energy, Elsevier, vol. 81(C), pages 588-600.
    29. Kamankesh, Hamidreza & Agelidis, Vassilios G. & Kavousi-Fard, Abdollah, 2016. "Optimal scheduling of renewable micro-grids considering plug-in hybrid electric vehicle charging demand," Energy, Elsevier, vol. 100(C), pages 285-297.
    30. Soares, João & Borges, Nuno & Fotouhi Ghazvini, Mohammad Ali & Vale, Zita & de Moura Oliveira, P.B., 2016. "Scenario generation for electric vehicles' uncertain behavior in a smart city environment," Energy, Elsevier, vol. 111(C), pages 664-675.
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