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Stochastic optimal sizing of distributed energy resources for a cost-effective and resilient Microgrid

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  • Wu, Di
  • Ma, Xu
  • Huang, Sen
  • Fu, Tao
  • Balducci, Patrick

Abstract

Recent developments and advances in distributed energy resources (DERs) make them more affordable, accessible, and prevalent in microgrids. Research on designing and operating a microgrid with various DERs has received increasing attention during the past few years. This paper proposes a two-stage stochastic mixed-integer programming method for jointly determining optimal sizes of various DERs, considering both economic benefits and resilience performance. The proposed method explicitly models the interaction between DER sizing at the planning stage and hourly or sub-hourly microgrid dispatch at the operating stage in both grid-connected and island modes, considering stochastic grid disturbances, load, and renewable generation. A formulation method is then proposed to convert the stochastic sizing problem to an equivalent mix-integer linear programming problem, which can be efficiently solved even with a large number of system operating conditions. Using the proposed stochastic sizing method, a resource planning analysis for a military base in the U.S. is presented. It is found that the proposed method can effectively determine the optimal DER sizes to meet a required resilience goal at the maximum net-benefit. Impacts of several key factors including tariff rates, discount rate, and survivability level on optimal DER sizes are analyzed through case studies.

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  • Wu, Di & Ma, Xu & Huang, Sen & Fu, Tao & Balducci, Patrick, 2020. "Stochastic optimal sizing of distributed energy resources for a cost-effective and resilient Microgrid," Energy, Elsevier, vol. 198(C).
    • Handle: RePEc:eee:energy:v:198:y:2020:i:c:s0360544220303911
    DOI: 10.1016/j.energy.2020.117284
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    14. Nur Najihah Abu Bakar & Josep M. Guerrero & Juan C. Vasquez & Najmeh Bazmohammadi & Muzaidi Othman & Brian Dalby Rasmussen & Yusuf A. Al-Turki, 2022. "Optimal Configuration and Sizing of Seaport Microgrids including Renewable Energy and Cold Ironing—The Port of Aalborg Case Study," Energies, MDPI, vol. 15(2), pages 1-18, January.
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    16. Fawad Azeem & Ashfaq Ahmad & Taimoor Muzaffar Gondal & Jehangir Arshad & Ateeq Ur Rehman & Elsayed M. Tag Eldin & Muhammad Shafiq & Habib Hamam, 2022. "Load Management and Optimal Sizing of Special-Purpose Microgrids Using Two Stage PSO-Fuzzy Based Hybrid Approach," Energies, MDPI, vol. 15(17), pages 1-19, September.
    17. Wu, Di & Wang, Dexin & Ramachandran, Thiagarajan & Holladay, Jamie, 2022. "A techno-economic assessment framework for hydrogen energy storage toward multiple energy delivery pathways and grid services," Energy, Elsevier, vol. 249(C).
    18. Zakernezhad, Hamid & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Multi-level optimization framework for resilient distribution system expansion planning with distributed energy resources," Energy, Elsevier, vol. 214(C).
    19. Muhyaddin Rawa & Abdullah Abusorrah & Yusuf Al-Turki & Saad Mekhilef & Mostafa H. Mostafa & Ziad M. Ali & Shady H. E. Abdel Aleem, 2020. "Optimal Allocation and Economic Analysis of Battery Energy Storage Systems: Self-Consumption Rate and Hosting Capacity Enhancement for Microgrids with High Renewable Penetration," Sustainability, MDPI, vol. 12(23), pages 1-25, December.
    20. Guodong Liu & Zhi Li & Yaosuo Xue & Kevin Tomsovic, 2022. "Microgrid Assisted Design for Remote Areas," Energies, MDPI, vol. 15(10), pages 1-23, May.
    21. Essayeh, Chaimaa & Morstyn, Thomas, 2023. "Optimal sizing for microgrids integrating distributed flexibility with the Perth West smart city as a case study," Applied Energy, Elsevier, vol. 336(C).
    22. Huang, Bowen & Huang, Sen & Ma, Xu & Katipamula, Srinivas & Wu, Di & Lutes, Robert, 2023. "Stochastic scheduling for commercial building cooling systems: considering uncertainty in zone temperature prediction," Applied Energy, Elsevier, vol. 346(C).

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