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Strategic decision-making of distribution network operator with multi-microgrids considering demand response program

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  • Jalali, Mehdi
  • Zare, Kazem
  • Seyedi, Heresh

Abstract

In this paper, the operation scheduling of future distribution network is discussed under assumption of multi-microgrids. The economic operation scheduling of distribution network operator in the presence of autonomous microgrids is formulated as a game problem. Due to participation of multiple players with different objective functions, the multi follower bi-level programming is intended in the energy management scheme. From the distribution network operator's perspective, the decision-making strategy seeks to minimize the operation costs of distribution network operator. Distribution network operator interconnecting with upstream grid and interaction with microgrids, schedules distributed energy resources and loads in economical matter to operate in optimal operation point. On the other hand, microgrid owners fed electrical loads interacting with the other microgrids and distribution network operator implementing demand response program during the scheduling horizon to acquire maximum profit. Therefore, the key focus of this approach is decision-making of distribution network operator which will be affected, not only by the reactions of microgrids, but also by the exchanging power between the microgrids. The paper discusses the theoretical background, architecture and algorithms of the proposed multi follower bi-level programming, and demonstrates the performance of distribution network operator and microgrids by means of simulation on the radial distribution test system.

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  • Jalali, Mehdi & Zare, Kazem & Seyedi, Heresh, 2017. "Strategic decision-making of distribution network operator with multi-microgrids considering demand response program," Energy, Elsevier, vol. 141(C), pages 1059-1071.
    • Handle: RePEc:eee:energy:v:141:y:2017:i:c:p:1059-1071
    DOI: 10.1016/j.energy.2017.09.145
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    as
    1. Wang, Chengshan & Liu, Yixin & Li, Xialin & Guo, Li & Qiao, Lei & Lu, Hai, 2016. "Energy management system for stand-alone diesel-wind-biomass microgrid with energy storage system," Energy, Elsevier, vol. 97(C), pages 90-104.
    2. Deihimi, Ali & Keshavarz Zahed, Babak & Iravani, Reza, 2016. "An interactive operation management of a micro-grid with multiple distributed generations using multi-objective uniform water cycle algorithm," Energy, Elsevier, vol. 106(C), pages 482-509.
    3. Ren, Ye & Suganthan, P.N. & Srikanth, N., 2015. "Ensemble methods for wind and solar power forecasting—A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 82-91.
    4. Alipour, Manijeh & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2014. "Short-term scheduling of combined heat and power generation units in the presence of demand response programs," Energy, Elsevier, vol. 71(C), pages 289-301.
    5. Ting-Chia Ou & Kai-Hung Lu & Chiou-Jye Huang, 2017. "Improvement of Transient Stability in a Hybrid Power Multi-System Using a Designed NIDC (Novel Intelligent Damping Controller)," Energies, MDPI, vol. 10(4), pages 1-16, April.
    6. Fang, Xinli & Ma, Shihao & Yang, Qiang & Zhang, Jintao, 2016. "Cooperative energy dispatch for multiple autonomous microgrids with distributed renewable sources and storages," Energy, Elsevier, vol. 99(C), pages 48-57.
    7. Hu, Ming-Che & Lu, Su-Ying & Chen, Yen-Haw, 2016. "Stochastic programming and market equilibrium analysis of microgrids energy management systems," Energy, Elsevier, vol. 113(C), pages 662-670.
    8. Jie Lu & Chenggen Shi & Guangquan Zhang & Da Ruan, 2007. "An Extended Branch And Bound Algorithm For Bilevel Multi-Follower Decision Making In A Referential-Uncooperative Situation," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 6(02), pages 371-388.
    9. Hong, Chih-Ming & Ou, Ting-Chia & Lu, Kai-Hung, 2013. "Development of intelligent MPPT (maximum power point tracking) control for a grid-connected hybrid power generation system," Energy, Elsevier, vol. 50(C), pages 270-279.
    10. Patrao, Iván & Figueres, Emilio & Garcerá, Gabriel & González-Medina, Raúl, 2015. "Microgrid architectures for low voltage distributed generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 415-424.
    11. Torriti, Jacopo & Hassan, Mohamed G. & Leach, Matthew, 2010. "Demand response experience in Europe: Policies, programmes and implementation," Energy, Elsevier, vol. 35(4), pages 1575-1583.
    12. Izadbakhsh, Maziar & Gandomkar, Majid & Rezvani, Alireza & Ahmadi, Abdollah, 2015. "Short-term resource scheduling of a renewable energy based micro grid," Renewable Energy, Elsevier, vol. 75(C), pages 598-606.
    13. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    14. Radhakrishnan, Bharat Menon & Srinivasan, Dipti, 2016. "A multi-agent based distributed energy management scheme for smart grid applications," Energy, Elsevier, vol. 103(C), pages 192-204.
    15. Rabiee, Abdorreza & Sadeghi, Mohammad & Aghaeic, Jamshid & Heidari, Alireza, 2016. "Optimal operation of microgrids through simultaneous scheduling of electrical vehicles and responsive loads considering wind and PV units uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 721-739.
    Full references (including those not matched with items on IDEAS)

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    9. Saeid Esmaeili & Amjad Anvari-Moghaddam & Shahram Jadid, 2019. "Optimal Operational Scheduling of Reconfigurable Multi-Microgrids Considering Energy Storage Systems," Energies, MDPI, vol. 12(9), pages 1-23, May.
    10. Mishra, Mrityunjay Kumar & Al-Sumaiti, Ameena Saad & Murari, Krishna & Parida, S.K. & Jaafari, Khaled Al, 2024. "Strategic interaction among distribution network operator and residential end-users via distribution use of system charges in demand-side management environment," Applied Energy, Elsevier, vol. 364(C).
    11. Longxi Li, 2020. "Optimal Coordination Strategies for Load Service Entity and Community Energy Systems Based on Centralized and Decentralized Approaches," Energies, MDPI, vol. 13(12), pages 1-22, June.
    12. Nouri, Alireza & Khodaei, Hossein & Darvishan, Ayda & Sharifian, Seyedmehdi & Ghadimi, Noradin, 2018. "Optimal performance of fuel cell-CHP-battery based micro-grid under real-time energy management: An epsilon constraint method and fuzzy satisfying approach," Energy, Elsevier, vol. 159(C), pages 121-133.
    13. Tostado-Véliz, Marcos & Hasanien, Hany M. & Jordehi, Ahmad Rezaee & Turky, Rania A. & Jurado, Francisco, 2023. "Risk-averse optimal participation of a DR-intensive microgrid in competitive clusters considering response fatigue," Applied Energy, Elsevier, vol. 339(C).
    14. Lv, Si & Wei, Zhinong & Chen, Sheng & Sun, Guoqiang & Wang, Dan, 2021. "Integrated demand response for congestion alleviation in coupled power and transportation networks," Applied Energy, Elsevier, vol. 283(C).
    15. 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.
    16. 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).
    17. Li, Longxi, 2021. "Coordination between smart distribution networks and multi-microgrids considering demand side management: A trilevel framework," Omega, Elsevier, vol. 102(C).
    18. Hosseinnia, Hamed & Modarresi, Javad & Nazarpour, Daryoush, 2020. "Optimal eco-emission scheduling of distribution network operator and distributed generator owner under employing demand response program," Energy, Elsevier, vol. 191(C).
    19. Li, Bei & Roche, Robin & Paire, Damien & Miraoui, Abdellatif, 2019. "A price decision approach for multiple multi-energy-supply microgrids considering demand response," Energy, Elsevier, vol. 167(C), pages 117-135.
    20. Tamás Kis & András Kovács & Csaba Mészáros, 2021. "On Optimistic and Pessimistic Bilevel Optimization Models for Demand Response Management," Energies, MDPI, vol. 14(8), pages 1-22, April.
    21. Ajoulabadi, Ata & Ravadanegh, Sajad Najafi & Behnam Mohammadi-Ivatloo,, 2020. "Flexible scheduling of reconfigurable microgrid-based distribution networks considering demand response program," Energy, Elsevier, vol. 196(C).
    22. Li, Longxi & Cao, Xilin & Wang, Peng, 2021. "Optimal coordination strategy for multiple distributed energy systems considering supply, demand, and price uncertainties," Energy, Elsevier, vol. 227(C).
    23. Diptish Saha & Najmeh Bazmohammadi & Juan C. Vasquez & Josep M. Guerrero, 2023. "Multiple Microgrids: A Review of Architectures and Operation and Control Strategies," Energies, MDPI, vol. 16(2), pages 1-32, January.

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