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Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review

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  • Rahim, Sahar
  • Wang, Zhen
  • Ju, Ping
Abstract
Over the past decade, escalating trends toward renewable energy resources, electrified transportation, magnifying load demand, erratic energy reserve capacities, dynamic demand response programs, and fast ubiquitous connectivity models have amplified the complexity of energy predicaments owing to the acute intensification of operational and technical uncertainties in the energy grid’s evolutionary phases, one of the pressing challenges that need to be properly addressed. For risk hedging and circumventing the impact of ambiguous parameters, several experts and decision-makers have developed uncertainty modeling approaches for optimization problems under uncertainty. This article first offers a generic overview of traditional uncertainty modeling techniques (such as probabilistic techniques, possibilistic techniques, hybrid probabilistic–possibilistic methods, information gap decision theory, and interval-based analysis) to highlight the significance of robust optimization (RO) method, a state-of-the-art deterministic set-based uncertainty methodology used to optimize a system having uncertain inputs. For this reason – a most popular and pertinent uncertainty modeling technique, the RO approach is precisely introduced to study and recapitulate its remarkable features, decisive modules, and shortcomings. Next, the preceding research on the RO’s contributions in the domain of the power grid is reviewed over three key enablers: Decentralization, Decarbonization, and Digitalization. More specifically, the literature on microgrid, virtual power plant, co/trigeneration, renewable energy with storage units, electric mobility, demand response, and security threats are covered in this survey. Finally, a rigorous discussion on foremost prospects, research gaps, and future directions is quantified. This strategic study can be utilized by researchers, engineers, and power industrialists to anticipate open research areas and unprecedented opportunities related to the application of the RO uncertainty handling method in the futuristic power grid.

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  • Rahim, Sahar & Wang, Zhen & Ju, Ping, 2022. "Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review," Applied Energy, Elsevier, vol. 319(C).
    • Handle: RePEc:eee:appene:v:319:y:2022:i:c:s0306261922005165
    DOI: 10.1016/j.apenergy.2022.119140
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    as
    1. Hajebrahimi, Ali & Kamwa, Innocent & Huneault, Maurice, 2018. "A novel approach for plug-in electric vehicle planning and electricity load management in presence of a clean disruptive technology," Energy, Elsevier, vol. 158(C), pages 975-985.
    2. Craparo, Emily & Karatas, Mumtaz & Singham, Dashi I., 2017. "A robust optimization approach to hybrid microgrid operation using ensemble weather forecasts," Applied Energy, Elsevier, vol. 201(C), pages 135-147.
    3. Shams, Mohammad H. & Shahabi, Majid & MansourLakouraj, Mohammad & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Adjustable robust optimization approach for two-stage operation of energy hub-based microgrids," Energy, Elsevier, vol. 222(C).
    4. Di Silvestre, Maria Luisa & Favuzza, Salvatore & Riva Sanseverino, Eleonora & Zizzo, Gaetano, 2018. "How Decarbonization, Digitalization and Decentralization are changing key power infrastructures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 483-498.
    5. Tingli Cheng & Minyou Chen & Yingxiang Wang & Bo Li & Muhammad Arshad Shehzad Hassan & Tao Chen & Ruilin Xu, 2018. "Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage," Complexity, Hindawi, vol. 2018, pages 1-13, June.
    6. Romero-Quete, David & Garcia, Javier Rosero, 2019. "An affine arithmetic-model predictive control approach for optimal economic dispatch of combined heat and power microgrids," Applied Energy, Elsevier, vol. 242(C), pages 1436-1447.
    7. Li, Yanbin & Zhang, Feng & Li, Yun & Wang, Yuwei, 2021. "An improved two-stage robust optimization model for CCHP-P2G microgrid system considering multi-energy operation under wind power outputs uncertainties," Energy, Elsevier, vol. 223(C).
    8. Guevara, Esnil & Babonneau, Fréderic & Homem-de-Mello, Tito & Moret, Stefano, 2020. "A machine learning and distributionally robust optimization framework for strategic energy planning under uncertainty," Applied Energy, Elsevier, vol. 271(C).
    9. Hu, Chenlian & Liu, Xiao & Lu, Jie & Wang, Chi-Hwa, 2020. "Distributionally robust optimization for power trading of waste-to-energy plants under uncertainty," Applied Energy, Elsevier, vol. 276(C).
    10. 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).
    11. Muhammad Riaz & Sadiq Ahmad & Irshad Hussain & Muhammad Naeem & Lucian Mihet-Popa, 2022. "Probabilistic Optimization Techniques in Smart Power System," Energies, MDPI, vol. 15(3), pages 1-39, January.
    12. Ruifeng Shi & Shaopeng Li & Changhao Sun & Kwang Y. Lee, 2018. "Adjustable Robust Optimization Algorithm for Residential Microgrid Multi-Dispatch Strategy with Consideration of Wind Power and Electric Vehicles," Energies, MDPI, vol. 11(8), pages 1-22, August.
    13. Tsao, Yu-Chung & Thanh, Vo-Van, 2021. "Toward blockchain-based renewable energy microgrid design considering default risk and demand uncertainty," Renewable Energy, Elsevier, vol. 163(C), pages 870-881.
    14. Xu Andy Sun & Antonio J. Conejo, 2021. "Robust Optimization in Short-Term Power System Operations," International Series in Operations Research & Management Science, in: Robust Optimization in Electric Energy Systems, chapter 0, pages 239-279, Springer.
    15. Kang, Jidong & Ng, Tsan Sheng & Su, Bin, 2020. "Optimizing electricity mix for CO2 emissions reduction: A robust input-output linear programming model," European Journal of Operational Research, Elsevier, vol. 287(1), pages 280-292.
    16. A. L. Soyster, 1973. "Technical Note—Convex Programming with Set-Inclusive Constraints and Applications to Inexact Linear Programming," Operations Research, INFORMS, vol. 21(5), pages 1154-1157, October.
    17. Gorissen, Bram L. & Yanıkoğlu, İhsan & den Hertog, Dick, 2015. "A practical guide to robust optimization," Omega, Elsevier, vol. 53(C), pages 124-137.
    18. Nayeem Chowdhury & Fabrizio Pilo & Giuditta Pisano, 2020. "Optimal Energy Storage System Positioning and Sizing with Robust Optimization," Energies, MDPI, vol. 13(3), pages 1-20, January.
    19. Shi, Ruifeng & Li, Shaopeng & Zhang, Penghui & Lee, Kwang Y., 2020. "Integration of renewable energy sources and electric vehicles in V2G network with adjustable robust optimization," Renewable Energy, Elsevier, vol. 153(C), pages 1067-1080.
    20. 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.
    21. Pinto, Rafael S. & Unsihuay-Vila, Clodomiro & Tabarro, Fabricio H., 2021. "Coordinated operation and expansion planning for multiple microgrids and active distribution networks under uncertainties," Applied Energy, Elsevier, vol. 297(C).
    22. Ernst Roos & Dick den Hertog, 2020. "Reducing Conservatism in Robust Optimization," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 1109-1127, October.
    23. Chen, C. & Li, Y.P. & Huang, G.H., 2013. "An inexact robust optimization method for supporting carbon dioxide emissions management in regional electric-power systems," Energy Economics, Elsevier, vol. 40(C), pages 441-456.
    24. Zubo, Rana.H.A. & Mokryani, Geev & Rajamani, Haile-Selassie & Aghaei, Jamshid & Niknam, Taher & Pillai, Prashant, 2017. "Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1177-1198.
    25. Farhan Aadil & Khalid Bashir Bajwa & Salabat Khan & Nadeem Majeed Chaudary & Adeel Akram, 2016. "CACONET: Ant Colony Optimization (ACO) Based Clustering Algorithm for VANET," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-21, May.
    26. Majidi, M. & Mohammadi-Ivatloo, B. & Soroudi, A., 2019. "Application of information gap decision theory in practical energy problems: A comprehensive review," Applied Energy, Elsevier, vol. 249(C), pages 157-165.
    27. Ju, Liwei & Tan, Zhongfu & Yuan, Jinyun & Tan, Qingkun & Li, Huanhuan & Dong, Fugui, 2016. "A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response," Applied Energy, Elsevier, vol. 171(C), pages 184-199.
    28. 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.
    29. Xu Andy Sun & Antonio J. Conejo, 2021. "Robust Optimization in Electric Energy Systems," International Series in Operations Research and Management Science, Springer, number 978-3-030-85128-6, December.
    30. Moretti, Luca & Martelli, Emanuele & Manzolini, Giampaolo, 2020. "An efficient robust optimization model for the unit commitment and dispatch of multi-energy systems and microgrids," Applied Energy, Elsevier, vol. 261(C).
    31. Baringo, Luis & Boffino, Luigi & Oggioni, Giorgia, 2020. "Robust expansion planning of a distribution system with electric vehicles, storage and renewable units," Applied Energy, Elsevier, vol. 265(C).
    32. Lai, Kexing & Illindala, Mahesh & Subramaniam, Karthikeyan, 2019. "A tri-level optimization model to mitigate coordinated attacks on electric power systems in a cyber-physical environment," Applied Energy, Elsevier, vol. 235(C), pages 204-218.
    33. Ferreira, R.S. & Barroso, L.A. & Carvalho, M.M., 2012. "Demand response models with correlated price data: A robust optimization approach," Applied Energy, Elsevier, vol. 96(C), pages 133-149.
    34. 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.
    35. Papadis, Elisa & Tsatsaronis, George, 2020. "Challenges in the decarbonization of the energy sector," Energy, Elsevier, vol. 205(C).
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