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A Systematic Review of Uncertainty Handling Approaches for Electric Grids Considering Electrical Vehicles

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  • Anna Auza

    (Associação para o Desenvolvimento da Aerodinâmica Industrial—ADAI, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal
    Faculty of Economics, University of Coimbra, Av. Dr. Dias da Silva 165, 3004-512 Coimbra, Portugal)

  • Ehsan Asadi

    (Associação para o Desenvolvimento da Aerodinâmica Industrial—ADAI, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal)

  • Behrang Chenari

    (Associação para o Desenvolvimento da Aerodinâmica Industrial—ADAI, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal)

  • Manuel Gameiro da Silva

    (Associação para o Desenvolvimento da Aerodinâmica Industrial—ADAI, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal)

Abstract

This paper systematically reviews the techniques and dynamics to study uncertainty modelling in the electric grids considering electric vehicles with vehicle-to-grid integration. Uncertainty types and the most frequent uncertainty modelling approaches for electric vehicles are outlined. The modelling approaches discussed in this paper are Monte Carlo, probabilistic scenarios, stochastic, point estimate method and robust optimisation. Then, Scopus is used to search for articles, and according to these categories, data from articles are extracted. The findings suggest that the probabilistic techniques are the most widely applied, with Monte Carlo and scenario analysis leading. In particular, 19% of the cases benefit from Monte Carlo, 15% from scenario analysis, and 10% each from robust optimisation and the stochastic approach, respectively. Early articles consider robust optimisation relatively more frequent, possibly due to the lack of historical data, while more recent articles adopt the Monte Carlo simulation approach. The uncertainty handling techniques depend on the uncertainty type and human resource availability in aggregate but are unrelated to the generation type. Finally, future directions are given.

Suggested Citation

  • Anna Auza & Ehsan Asadi & Behrang Chenari & Manuel Gameiro da Silva, 2023. "A Systematic Review of Uncertainty Handling Approaches for Electric Grids Considering Electrical Vehicles," Energies, MDPI, vol. 16(13), pages 1-25, June.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:13:p:4983-:d:1180612
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    References listed on IDEAS

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    1. Lin, Haiyang & Fu, Kun & Wang, Yu & Sun, Qie & Li, Hailong & Hu, Yukun & Sun, Bo & Wennersten, Ronald, 2019. "Characteristics of electric vehicle charging demand at multiple types of location - Application of an agent-based trip chain model," Energy, Elsevier, vol. 188(C).
    2. Jordehi, A. Rezaee & Javadi, Mohammad Sadegh & Catalão, João P.S., 2021. "Day-ahead scheduling of energy hubs with parking lots for electric vehicles considering uncertainties," Energy, Elsevier, vol. 229(C).
    3. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2018. "Optimal operation of an energy management system for a grid-connected smart building considering photovoltaics’ uncertainty and stochastic electric vehicles’ driving schedule," Applied Energy, Elsevier, vol. 210(C), pages 1188-1206.
    4. Norouzi, Mohammadali & Aghaei, Jamshid & Pirouzi, Sasan & Niknam, Taher & Fotuhi-Firuzabad, Mahmud, 2022. "Flexibility pricing of integrated unit of electric spring and EVs parking in microgrids," Energy, Elsevier, vol. 239(PB).
    5. DeForest, Nicholas & MacDonald, Jason S. & Black, Douglas R., 2018. "Day ahead optimization of an electric vehicle fleet providing ancillary services in the Los Angeles Air Force Base vehicle-to-grid demonstration," Applied Energy, Elsevier, vol. 210(C), pages 987-1001.
    6. Jiao, Zihao & Ran, Lun & Zhang, Yanzi & Ren, Yaping, 2021. "Robust vehicle-to-grid power dispatching operations amid sociotechnical complexities," Applied Energy, Elsevier, vol. 281(C).
    7. Huang, Shoujun & Abedinia, Oveis, 2021. "Investigation in economic analysis of microgrids based on renewable energy uncertainty and demand response in the electricity market," Energy, Elsevier, vol. 225(C).
    8. Wang, Yubo & Shi, Wenbo & Wang, Bin & Chu, Chi-Cheng & Gadh, Rajit, 2017. "Optimal operation of stationary and mobile batteries in distribution grids," Applied Energy, Elsevier, vol. 190(C), pages 1289-1301.
    9. Kanakadhurga, Dharmaraj & Prabaharan, Natarajan, 2022. "Peer-to-Peer trading with Demand Response using proposed smart bidding strategy," Applied Energy, Elsevier, vol. 327(C).
    10. Li, Yipu & Su, Hao & Zhou, Yun & Chen, Lixia & Shi, Yiwei & Li, Hengjie & Feng, Donghan, 2023. "Two-stage real-time optimal electricity dispatch strategy for urban residential quarter with electric vehicles’ charging load," Energy, Elsevier, vol. 268(C).
    11. Bitencourt, Leonardo & Dias, Bruno & Soares, Tiago & Borba, Bruno & Quirós-Tortós, Jairo, 2023. "e-Carsharing siting and sizing DLMP-based under demand uncertainty," Applied Energy, Elsevier, vol. 330(PB).
    12. Jian-Tang Liao & Hao-Wei Huang & Hong-Tzer Yang & Desheng Li, 2021. "Decentralized V2G/G2V Scheduling of EV Charging Stations by Considering the Conversion Efficiency of Bidirectional Chargers," Energies, MDPI, vol. 14(4), pages 1-17, February.
    13. Keon Baek & Woong Ko & Jinho Kim, 2019. "Optimal Scheduling of Distributed Energy Resources in Residential Building under the Demand Response Commitment Contract," Energies, MDPI, vol. 12(14), pages 1-19, July.
    14. 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.
    15. Tostado-Véliz, Marcos & Rezaee Jordehi, Ahmad & Amir Mansouri, Seyed & Jurado, Francisco, 2022. "Day-ahead scheduling of 100% isolated communities under uncertainties through a novel stochastic-robust model," Applied Energy, Elsevier, vol. 328(C).
    16. Ehsan, Ali & Yang, Qiang, 2019. "State-of-the-art techniques for modelling of uncertainties in active distribution network planning: A review," Applied Energy, Elsevier, vol. 239(C), pages 1509-1523.
    17. Kandpal, Bakul & Pareek, Parikshit & Verma, Ashu, 2022. "A robust day-ahead scheduling strategy for EV charging stations in unbalanced distribution grid," Energy, Elsevier, vol. 249(C).
    18. Liao, Zitong & Taiebat, Morteza & Xu, Ming, 2021. "Shared autonomous electric vehicle fleets with vehicle-to-grid capability: Economic viability and environmental co-benefits," Applied Energy, Elsevier, vol. 302(C).
    19. George-Williams, H. & Wade, N. & Carpenter, R.N., 2022. "A probabilistic framework for the techno-economic assessment of smart energy hubs for electric vehicle charging," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    20. Lidan Chen & Yao Zhang & Antonio Figueiredo, 2019. "Spatio-Temporal Model for Evaluating Demand Response Potential of Electric Vehicles in Power-Traffic Network," Energies, MDPI, vol. 12(10), pages 1-20, May.
    21. Qiu, Dawei & Wang, Yi & Sun, Mingyang & Strbac, Goran, 2022. "Multi-service provision for electric vehicles in power-transportation networks towards a low-carbon transition: A hierarchical and hybrid multi-agent reinforcement learning approach," Applied Energy, Elsevier, vol. 313(C).
    22. Sheng Ding & Chengmei Xu & Yao Rao & Zhaofang Song & Wangwang Yang & Zexu Chen & Zitong Zhang, 2022. "A Time-Varying Potential Evaluation Method for Electric Vehicle Group Demand Response Driven by Small Sample Data," Sustainability, MDPI, vol. 14(9), pages 1-21, April.
    23. Sajad Aliakbari Sani & Olivier Bahn & Erick Delage & Rinel Foguen Tchuendom, 2022. "Robust Integration of Electric Vehicles Charging Load in Smart Grid’s Capacity Expansion Planning," Dynamic Games and Applications, Springer, vol. 12(3), pages 1010-1041, September.
    24. Narongkorn Uthathip & Pornrapeepat Bhasaputra & Woraratana Pattaraprakorn, 2021. "Stochastic Modelling to Analyze the Impact of Electric Vehicle Penetration in Thailand," Energies, MDPI, vol. 14(16), pages 1-23, August.
    25. Mehrjerdi, Hasan, 2021. "Resilience oriented vehicle-to-home operation based on battery swapping mechanism," Energy, Elsevier, vol. 218(C).
    26. Nezamoddini, Nasim & Wang, Yong, 2016. "Risk management and participation planning of electric vehicles in smart grids for demand response," Energy, Elsevier, vol. 116(P1), pages 836-850.
    27. Khardenavis, Amaiya & Hewage, Kasun & Perera, Piyaruwan & Shotorbani, Amin Mohammadpour & Sadiq, Rehan, 2021. "Mobile energy hub planning for complex urban networks: A robust optimization approach," Energy, Elsevier, vol. 235(C).
    28. Alqahtani, Mohammed & Hu, Mengqi, 2022. "Dynamic energy scheduling and routing of multiple electric vehicles using deep reinforcement learning," Energy, Elsevier, vol. 244(PA).
    29. Yilu Wang & Zixuan Jia & Jianing Li & Xiaoping Zhang & Ray Zhang, 2021. "Optimal Bi-Level Scheduling Method of Vehicle-to-Grid and Ancillary Services of Aggregators with Conditional Value-at-Risk," Energies, MDPI, vol. 14(21), pages 1-16, October.
    30. Àlex Alonso-Travesset & Diederik Coppitters & Helena Martín & Jordi de la Hoz, 2023. "Economic and Regulatory Uncertainty in Renewable Energy System Design: A Review," Energies, MDPI, vol. 16(2), pages 1-30, January.
    31. 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.
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    1. Kwanghun Chung & Jong-Hyun Ryu, 2024. "Economic Value Assessment of Vehicle-to-Home (V2H) Operation under Various Environmental Conditions," Energies, MDPI, vol. 17(15), pages 1-16, August.

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