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Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies

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  • Ahmadi, Seyed Ehsan
  • Sadeghi, Delnia
  • Marzband, Mousa
  • Abusorrah, Abdullah
  • Sedraoui, Khaled

Abstract

This paper presents a novel decentralized bi-level stochastic optimization approach based on the progressive hedging algorithm for multi-agent systems (MAS) in multi-energy microgrids (MEMGs) to enhance network flexibility. In the proposed model, suppliers and consumers of three energy carrier of power, heat, and hydrogen are considered. This system further consists of multi-energy storage systems such as plug-in electric vehicle aggregators, thermal energy storage, and hydrogen energy storage with the application of power-to-hydrogen and hydrogen-to-power technologies. Furthermore, the Latin Hypercube Sampling method has been utilized to manage the uncertainties. In addition, a penalty function and a power exchange pricing model are evaluated by the electrical marginal price of each microgrid to determine the agreed power exchange among the MEMGs. The suggested work performs over a MAS with three MEMGs. The total profit of each microgrid is maximized over a 24-h scheduling in three diverse case studies. Ultimately, the proposed decentralized bi-level optimization approach, by converging through seven iterations, indicates an effective performance as a promising solution to a MAS-based framework. Besides, the optimal scheduling of the MEMGs were converged in the same profit for the diverse network topologies. Implementing multi-energy storage systems plays a major role in increasing total profit of MEMGs and improving the reliability performance of MAS-based structure.

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  • Ahmadi, Seyed Ehsan & Sadeghi, Delnia & Marzband, Mousa & Abusorrah, Abdullah & Sedraoui, Khaled, 2022. "Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies," Energy, Elsevier, vol. 245(C).
    • Handle: RePEc:eee:energy:v:245:y:2022:i:c:s0360544222001268
    DOI: 10.1016/j.energy.2022.123223
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    as
    1. Kabli, Mohannad & Quddus, Md Abdul & Nurre, Sarah G. & Marufuzzaman, Mohammad & Usher, John M., 2020. "A stochastic programming approach for electric vehicle charging station expansion plans," International Journal of Production Economics, Elsevier, vol. 220(C).
    2. Mohamed, Mohamed A. & Jin, Tao & Su, Wencong, 2020. "Multi-agent energy management of smart islands using primal-dual method of multipliers," Energy, Elsevier, vol. 208(C).
    3. Kopanos, Georgios M. & Georgiadis, Michael C. & Pistikopoulos, Efstratios N., 2013. "Energy production planning of a network of micro combined heat and power generators," Applied Energy, Elsevier, vol. 102(C), pages 1522-1534.
    4. Mirzaei, Mohammad Amin & Sadeghi-Yazdankhah, Ahmad & Mohammadi-Ivatloo, Behnam & Marzband, Mousa & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Integration of emerging resources in IGDT-based robust scheduling of combined power and natural gas systems considering flexible ramping products," Energy, Elsevier, vol. 189(C).
    5. Bullich-Massagué, Eduard & Díaz-González, Francisco & Aragüés-Peñalba, Mònica & Girbau-Llistuella, Francesc & Olivella-Rosell, Pol & Sumper, Andreas, 2018. "Microgrid clustering architectures," Applied Energy, Elsevier, vol. 212(C), pages 340-361.
    6. Hong, Bowen & Zhang, Weitong & Zhou, Yue & Chen, Jian & Xiang, Yue & Mu, Yunfei, 2018. "Energy-Internet-oriented microgrid energy management system architecture and its application in China," Applied Energy, Elsevier, vol. 228(C), pages 2153-2164.
    7. Karimi, Hamid & Jadid, Shahram, 2020. "Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework," Energy, Elsevier, vol. 195(C).
    8. Dini, Anoosh & Pirouzi, Sasan & Norouzi, Mohammadali & Lehtonen, Matti, 2019. "Grid-connected energy hubs in the coordinated multi-energy management based on day-ahead market framework," Energy, Elsevier, vol. 188(C).
    9. Gao, Hongjun & Xu, Song & Liu, Youbo & Wang, Lingfeng & Xiang, Yingmeng & Liu, Junyong, 2020. "Decentralized optimal operation model for cooperative microgrids considering renewable energy uncertainties," Applied Energy, Elsevier, vol. 262(C).
    10. Anvari-Moghaddam, Amjad & Rahimi-Kian, Ashkan & Mirian, Maryam S. & Guerrero, Josep M., 2017. "A multi-agent based energy management solution for integrated buildings and microgrid system," Applied Energy, Elsevier, vol. 203(C), pages 41-56.
    11. Qiu, Haifeng & You, Fengqi, 2020. "Decentralized-distributed robust electric power scheduling for multi-microgrid systems," Applied Energy, Elsevier, vol. 269(C).
    12. Zuo, Hongyan & Zhang, Bin & Huang, Zhonghua & Wei, Kexiang & Zhu, Hong & Tan, Jiqiu, 2022. "Effect analysis on SOC values of the power lithium manganate battery during discharging process and its intelligent estimation," Energy, Elsevier, vol. 238(PB).
    13. 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).
    14. Zare Oskouei, Morteza & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Shafiee, Mahmood & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "A hybrid robust-stochastic approach to evaluate the profit of a multi-energy retailer in tri-layer energy markets," Energy, Elsevier, vol. 214(C).
    15. Wang, Xiaoxue & Wang, Chengshan & Xu, Tao & Guo, Lingxu & Li, Peng & Yu, Li & Meng, He, 2018. "Optimal voltage regulation for distribution networks with multi-microgrids," Applied Energy, Elsevier, vol. 210(C), pages 1027-1036.
    16. Ghanbari, Ali & Karimi, Hamid & Jadid, Shahram, 2020. "Optimal planning and operation of multi-carrier networked microgrids considering multi-energy hubs in distribution networks," Energy, Elsevier, vol. 204(C).
    17. Yang, Kang & Li, Chunhua & Jing, Xu & Zhu, Zhiyu & Wang, Yuting & Ma, Haodong & Zhang, Yu, 2022. "Energy dispatch optimization of islanded multi-microgrids based on symbiotic organisms search and improved multi-agent consensus algorithm," Energy, Elsevier, vol. 239(PC).
    18. Li, Qiang & Gao, Mengkai & Lin, Houfei & Chen, Ziyu & Chen, Minyou, 2019. "MAS-based distributed control method for multi-microgrids with high-penetration renewable energy," Energy, Elsevier, vol. 171(C), pages 284-295.
    19. Kou, Yu & Bie, Zhaohong & Li, Gengfeng & Liu, Fan & Jiang, Jiangfeng, 2021. "Reliability evaluation of multi-agent integrated energy systems with fully distributed communication," Energy, Elsevier, vol. 224(C).
    20. Meeus, L. & Vandezande, L. & Cole, S. & Belmans, R., 2009. "Market coupling and the importance of price coordination between power exchanges," Energy, Elsevier, vol. 34(3), pages 228-234.
    21. Sadeghi, Delnia & Hesami Naghshbandy, Ali & Bahramara, Salah, 2020. "Optimal sizing of hybrid renewable energy systems in presence of electric vehicles using multi-objective particle swarm optimization," Energy, Elsevier, vol. 209(C).
    22. Nikmehr, Nima, 2020. "Distributed robust operational optimization of networked microgrids embedded interconnected energy hubs," Energy, Elsevier, vol. 199(C).
    23. Zhou, Xiaoqian & Ai, Qian & Yousif, Muhammad, 2019. "Two kinds of decentralized robust economic dispatch framework combined distribution network and multi-microgrids," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    24. Nasiri, Nima & Zeynali, Saeed & Ravadanegh, Sajad Najafi & Marzband, Mousa, 2021. "A hybrid robust-stochastic approach for strategic scheduling of a multi-energy system as a price-maker player in day-ahead wholesale market," Energy, Elsevier, vol. 235(C).
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