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Coordination between smart distribution networks and multi-microgrids considering demand side management: A trilevel framework

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  • Li, Longxi

Abstract

This paper addresses the dilemma of coordination among three kinds of stakeholders, namely, the smart distribution networks, microgrids, and customers with demand response resources under a comprehensive trilevel framework. The interaction among these stakeholders, which are regarded as subjects of individual interest, leads to a complex energy generation, storage, transaction, and consumption problem. Based on the assumption that the customers always provide the best response to the signals of leaders, the trilevel problem is transformed into a bilevel problem by replacing the lowest level problem with its optimality conditions. Next, two coordination schemes are formulated to analyze the interactions between the smart distribution network and microgrids with demand response resources. The first scheme is a full cooperative coordination framework, in which the smart distribution network and microgrids jointly activate the resources located under the distribution networks. The second scheme is an ancillary service framework in the sense that the smart distribution network acts as a service subject to balance the supply and demand of the networks, and charges the management fee for transmission service. This scheme can achieve rapid convergence in a distributed manner, expose little information, and protect the privacy of the selfish participants. For each coordination scheme, a detailed mathematical model and solution method are formed. Illustrative examples highlight the feasibility and applicability of the schemes and provide references for the government in making decision with respect to the problems of coordination among the smart distribution networks, microgrids, and customers.

Suggested Citation

  • Li, Longxi, 2021. "Coordination between smart distribution networks and multi-microgrids considering demand side management: A trilevel framework," Omega, Elsevier, vol. 102(C).
  • Handle: RePEc:eee:jomega:v:102:y:2021:i:c:s0305048320306800
    DOI: 10.1016/j.omega.2020.102326
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    1. Sheikhahmadi, P. & Bahramara, S. & Moshtagh, J. & Yazdani Damavandi, M., 2018. "A risk-based approach for modeling the strategic behavior of a distribution company in wholesale energy market," Applied Energy, Elsevier, vol. 214(C), pages 24-38.
    2. Yu, Mengmeng & Hong, Seung Ho, 2017. "Incentive-based demand response considering hierarchical electricity market: A Stackelberg game approach," Applied Energy, Elsevier, vol. 203(C), pages 267-279.
    3. 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.
    4. Hirsch, Adam & Parag, Yael & Guerrero, Josep, 2018. "Microgrids: A review of technologies, key drivers, and outstanding issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 402-411.
    5. Sinha, Surabhi & Sinha, S. B., 2002. "KKT transformation approach for multi-objective multi-level linear programming problems," European Journal of Operational Research, Elsevier, vol. 143(1), pages 19-31, November.
    6. Behrangrad, Mahdi, 2015. "A review of demand side management business models in the electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 270-283.
    7. Monfared, Houman Jamshidi & Ghasemi, Ahmad & Loni, Abdolah & Marzband, Mousa, 2019. "A hybrid price-based demand response program for the residential micro-grid," Energy, Elsevier, vol. 185(C), pages 274-285.
    8. Nwulu, Nnamdi I. & Xia, Xiaohua, 2017. "Optimal dispatch for a microgrid incorporating renewables and demand response," Renewable Energy, Elsevier, vol. 101(C), pages 16-28.
    9. Imani, Mahmood Hosseini & Ghadi, M. Jabbari & Ghavidel, Sahand & Li, Li, 2018. "Demand Response Modeling in Microgrid Operation: a Review and Application for Incentive-Based and Time-Based Programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 486-499.
    10. Mazzoni, Stefano & Ooi, Sean & Nastasi, Benedetto & Romagnoli, Alessandro, 2019. "Energy storage technologies as techno-economic parameters for master-planning and optimal dispatch in smart multi energy systems," Applied Energy, Elsevier, vol. 254(C).
    11. Aussel, Didier & Brotcorne, Luce & Lepaul, Sébastien & von Niederhäusern, Léonard, 2020. "A trilevel model for best response in energy demand-side management," European Journal of Operational Research, Elsevier, vol. 281(2), pages 299-315.
    12. Tang, Rui & Wang, Shengwei & Li, Hangxin, 2019. "Game theory based interactive demand side management responding to dynamic pricing in price-based demand response of smart grids," Applied Energy, Elsevier, vol. 250(C), pages 118-130.
    13. Hélène Le Cadre & Ilyès Mezghani & Anthony Papavasiliou, 2019. "A game-theoretic analysis of transmission-distribution system operator coordination," LIDAM Reprints CORE 2996, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Jin, Ming & Feng, Wei & Marnay, Chris & Spanos, Costas, 2018. "Microgrid to enable optimal distributed energy retail and end-user demand response," Applied Energy, Elsevier, vol. 210(C), pages 1321-1335.
    15. Ma, Tengfei & Wu, Junyong & Hao, Liangliang & Lee, Wei-Jen & Yan, Huaguang & Li, Dezhi, 2018. "The optimal structure planning and energy management strategies of smart multi energy systems," Energy, Elsevier, vol. 160(C), pages 122-141.
    16. Le Cadre, Hélène & Mezghani, Ilyès & Papavasiliou, Anthony, 2019. "A game-theoretic analysis of transmission-distribution system operator coordination," European Journal of Operational Research, Elsevier, vol. 274(1), pages 317-339.
    17. Kuiken, Dirk & Más, Heyd F., 2019. "Integrating demand side management into EU electricity distribution system operation: A Dutch example," Energy Policy, Elsevier, vol. 129(C), pages 153-160.
    18. Faria, P. & Vale, Z., 2011. "Demand response in electrical energy supply: An optimal real time pricing approach," Energy, Elsevier, vol. 36(8), pages 5374-5384.
    19. Lee V. White & Nicole D. Sintov, 2018. "Inaccurate consumer perceptions of monetary savings in a demand-side response programme predict programme acceptance," Nature Energy, Nature, vol. 3(12), pages 1101-1108, December.
    20. Zhang, Bingying & Li, Qiqiang & Wang, Luhao & Feng, Wei, 2018. "Robust optimization for energy transactions in multi-microgrids under uncertainty," Applied Energy, Elsevier, vol. 217(C), pages 346-360.
    21. Xie, Min & Ji, Xiang & Hu, Xintong & Cheng, Peijun & Du, Yuxin & Liu, Mingbo, 2018. "Autonomous optimized economic dispatch of active distribution system with multi-microgrids," Energy, Elsevier, vol. 153(C), pages 479-489.
    22. Li, Longxi & Mu, Hailin & Li, Nan & Li, Miao, 2016. "Economic and environmental optimization for distributed energy resource systems coupled with district energy networks," Energy, Elsevier, vol. 109(C), pages 947-960.
    23. Fontaine, Pirmin & Minner, Stefan, 2014. "Benders Decomposition for Discrete–Continuous Linear Bilevel Problems with application to traffic network design," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 163-172.
    24. Timo Lohmann & Steffen Rebennack, 2017. "Tailored Benders Decomposition for a Long-Term Power Expansion Model with Short-Term Demand Response," Management Science, INFORMS, vol. 63(6), pages 2027-2048, June.
    25. Shamekhi Amiri, A. & Torabi, S. Ali & Ghodsi, R., 2018. "An iterative approach for a bi-level competitive supply chain network design problem under foresight competition and variable coverage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 99-114.
    26. 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.
    27. Alexander Mitsos, 2010. "Global solution of nonlinear mixed-integer bilevel programs," Journal of Global Optimization, Springer, vol. 47(4), pages 557-582, August.
    28. Liu, Yixin & Guo, Li & Wang, Chengshan, 2018. "A robust operation-based scheduling optimization for smart distribution networks with multi-microgrids," Applied Energy, Elsevier, vol. 228(C), pages 130-140.
    29. Jamasb, Tooraj & Thakur, Tripta & Bag, Baidyanath, 2018. "Smart electricity distribution networks, business models, and application for developing countries," Energy Policy, Elsevier, vol. 114(C), pages 22-29.
    30. 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.
    31. Gärttner, Johannes & Flath, Christoph M. & Weinhardt, Christof, 2018. "Portfolio and contract design for demand response resources," European Journal of Operational Research, Elsevier, vol. 266(1), pages 340-353.
    32. Mazidi, Peyman & Tohidi, Yaser & Ramos, Andres & Sanz-Bobi, Miguel A., 2018. "Profit-maximization generation maintenance scheduling through bi-level programming," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1045-1057.
    33. Guo, Peiyang & Li, Victor O.K. & Lam, Jacqueline C.K., 2017. "Smart demand response in China: Challenges and drivers," Energy Policy, Elsevier, vol. 107(C), pages 1-10.
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