IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v245y2022ics0360544222001311.html
   My bibliography  Save this article

A sustainable framework for multi-microgrids energy management in automated distribution network by considering smart homes and high penetration of renewable energy resources

Author

Listed:
  • Mansouri, S.A.
  • Ahmarinejad, A.
  • Nematbakhsh, E.
  • Javadi, M.S.
  • Esmaeel Nezhad, A.
  • Catalão, J.P.S.

Abstract

This paper presents a new framework for the scheduling of microgrids and distribution feeder reconfiguration (DFR), taking into consideration the uncertainties due to the load demand, market price, and renewable power generation. The model is implemented on the modified IEEE 118-bus test system, including microgrids and smart homes. The problem has been formulated as a two-stage model, which at the first stage, the day-ahead self-scheduling of each microgrid is carried out as a two-objective optimization problem. The two objectives include the minimization of the total operating cost and maximization of the consumer's comfort index. Then, the solution, obtained from the first stage is delivered to the distribution system operator (DSO). Then, at the second stage, the DSO determines the optimal configuration of the system with the aim of minimizing operating costs of the main grid and the penalty of deviating from microgrid scheduling. Note that the penalty is due to the difference in power exchange requested by the microgrids from the power exchange finalized by the DSO. The presented two-stage optimization problem is modeled in a mixed-integer linear programing (MILP) framework with four case studies, and solved in GAMS by using the GURUBI solver. The simulation results show that in the cases the DSO is able to reconfigure the system, the deviation from the optimal scheduling of microgrids would be considerably lower than the cases with fixed system configuration.

Suggested Citation

  • Mansouri, S.A. & Ahmarinejad, A. & Nematbakhsh, E. & Javadi, M.S. & Esmaeel Nezhad, A. & Catalão, J.P.S., 2022. "A sustainable framework for multi-microgrids energy management in automated distribution network by considering smart homes and high penetration of renewable energy resources," Energy, Elsevier, vol. 245(C).
    • Handle: RePEc:eee:energy:v:245:y:2022:i:c:s0360544222001311
    DOI: 10.1016/j.energy.2022.123228
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222001311
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.123228?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zareen, N. & Mustafa, M.W. & Sultana, U. & Nadia, R. & Khattak, M.A., 2015. "Optimal real time cost-benefit based demand response with intermittent resources," Energy, Elsevier, vol. 90(P2), pages 1695-1706.
    2. Javadi, Mohammad Sadegh & Esmaeel Nezhad, Ali & Jordehi, Ahmad Rezaee & Gough, Matthew & Santos, Sérgio F. & Catalão, João P.S., 2022. "Transactive energy framework in multi-carrier energy hubs: A fully decentralized model," Energy, Elsevier, vol. 238(PB).
    3. Shanghua Guo & Jian Lin & Yuming Zhao & Longjun Wang & Gang Wang & Guowei Liu, 2020. "A Reliability-Based Network Reconfiguration Model in Distribution System with DGs and ESSs Using Mixed-Integer Programming," Energies, MDPI, vol. 13(5), pages 1-15, March.
    4. Rocha, Helder R.O. & Honorato, Icaro H. & Fiorotti, Rodrigo & Celeste, Wanderley C. & Silvestre, Leonardo J. & Silva, Jair A.L., 2021. "An Artificial Intelligence based scheduling algorithm for demand-side energy management in Smart Homes," Applied Energy, Elsevier, vol. 282(PA).
    5. Bishwajit Dey & Fausto Pedro García Márquez & Sourav Kr. Basak, 2020. "Smart Energy Management of Residential Microgrid System by a Novel Hybrid MGWOSCACSA Algorithm," Energies, MDPI, vol. 13(13), pages 1-23, July.
    6. Safaie, Amir Abbas & Alizadeh Bidgoli, Mohsen & Javadi, Saeid, 2022. "A multi-objective optimization framework for integrated electricity and natural gas networks considering smart homes in downward under uncertainties," Energy, Elsevier, vol. 239(PC).
    7. Behzadi, Amirmohammad & Arabkoohsar, Ahmad, 2020. "Feasibility study of a smart building energy system comprising solar PV/T panels and a heat storage unit," Energy, Elsevier, vol. 210(C).
    8. Alizadeh Bidgoli, Mohsen & Ahmadian, Ali, 2022. "Multi-stage optimal scheduling of multi-microgrids using deep-learning artificial neural network and cooperative game approach," Energy, Elsevier, vol. 239(PB).
    9. Tan, Bifei & Chen, Haoyong, 2020. "Multi-objective energy management of multiple microgrids under random electric vehicle charging," Energy, Elsevier, vol. 208(C).
    10. Akter, M.N. & Mahmud, M.A. & Haque, M.E. & Oo, Amanullah M.T., 2020. "An optimal distributed energy management scheme for solving transactive energy sharing problems in residential microgrids," Applied Energy, Elsevier, vol. 270(C).
    11. Kumar, K. Prakash & Saravanan, B., 2017. "Recent techniques to model uncertainties in power generation from renewable energy sources and loads in microgrids – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 348-358.
    12. Wang, Jidong & Liu, Jianxin & Li, Chenghao & Zhou, Yue & Wu, Jianzhong, 2020. "Optimal scheduling of gas and electricity consumption in a smart home with a hybrid gas boiler and electric heating system," Energy, Elsevier, vol. 204(C).
    13. Leonori, Stefano & Martino, Alessio & Frattale Mascioli, Fabio Massimo & Rizzi, Antonello, 2020. "Microgrid Energy Management Systems Design by Computational Intelligence Techniques," Applied Energy, Elsevier, vol. 277(C).
    14. Nikmehr, Nima, 2020. "Distributed robust operational optimization of networked microgrids embedded interconnected energy hubs," Energy, Elsevier, vol. 199(C).
    15. Bandeiras, F. & Pinheiro, E. & Gomes, M. & Coelho, P. & Fernandes, J., 2020. "Review of the cooperation and operation of microgrid clusters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    16. Mukhopadhyay, Bineeta & Das, Debapriya, 2020. "Multi-objective dynamic and static reconfiguration with optimized allocation of PV-DG and battery energy storage system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    17. Adefarati, T. & Bansal, R.C., 2019. "Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources," Applied Energy, Elsevier, vol. 236(C), pages 1089-1114.
    18. Wang, Yi & Rousis, Anastasios Oulis & Strbac, Goran, 2020. "On microgrids and resilience: A comprehensive review on modeling and operational strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    19. Ding, Tao & Lin, Yanling & Bie, Zhaohong & Chen, Chen, 2017. "A resilient microgrid formation strategy for load restoration considering master-slave distributed generators and topology reconfiguration," Applied Energy, Elsevier, vol. 199(C), pages 205-216.
    20. Ghasemi, Ahmad & Jamshidi Monfared, Houman & Loni, Abdolah & Marzband, Mousa, 2021. "CVaR-based retail electricity pricing in day-ahead scheduling of microgrids," Energy, Elsevier, vol. 227(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lv, Chaoxian & Liang, Rui & Zhang, Ge & Zhang, Xiaotong & Jin, Wei, 2023. "Energy accommodation-oriented interaction of active distribution network and central energy station considering soft open points," Energy, Elsevier, vol. 268(C).
    2. Muhammad Umair Safder & Mohammad J. Sanjari & Ameer Hamza & Rasoul Garmabdari & Md. Alamgir Hossain & Junwei Lu, 2023. "Enhancing Microgrid Stability and Energy Management: Techniques, Challenges, and Future Directions," Energies, MDPI, vol. 16(18), pages 1-28, September.
    3. Lu, Xi & Xia, Shiwei & Gu, Wei & Chan, Ka Wing, 2022. "A model for balance responsible distribution systems with energy storage to achieve coordinated load shifting and uncertainty mitigation," Energy, Elsevier, vol. 249(C).
    4. Marcelino, C.G. & Leite, G.M.C. & Wanner, E.F. & Jiménez-Fernández, S. & Salcedo-Sanz, S., 2023. "Evaluating the use of a Net-Metering mechanism in microgrids to reduce power generation costs with a swarm-intelligent algorithm," Energy, Elsevier, vol. 266(C).
    5. Mohammed M. Alhaider & Ziad M. Ali & Mostafa H. Mostafa & Shady H. E. Abdel Aleem, 2023. "Economic Viability of NaS Batteries for Optimal Microgrid Operation and Hosting Capacity Enhancement under Uncertain Conditions," Sustainability, MDPI, vol. 15(20), pages 1-24, October.
    6. Tong, Ziqiang & Mansouri, Seyed Amir & Huang, Shoujun & Rezaee Jordehi, Ahmad & Tostado-Véliz, Marcos, 2023. "The role of smart communities integrated with renewable energy resources, smart homes and electric vehicles in providing ancillary services: A tri-stage optimization mechanism," Applied Energy, Elsevier, vol. 351(C).
    7. Zhou, Kaile & Fei, Zhineng & Hu, Rong, 2023. "Hybrid robust decentralized optimization of emission-aware multi-energy microgrids considering multiple uncertainties," Energy, Elsevier, vol. 265(C).
    8. Kermani, Mostafa & Chen, Peiyuan & Göransson, Lisa & Bongiorno, Massimo, 2022. "A comprehensive optimal energy control in interconnected microgrids through multiport converter under N−1 criterion and demand response program," Renewable Energy, Elsevier, vol. 199(C), pages 957-976.
    9. Tostado-Véliz, Marcos & Kamel, Salah & Aymen, Flah & Rezaee Jordehi, Ahmad & Jurado, Francisco, 2022. "A Stochastic-IGDT model for energy management in isolated microgrids considering failures and demand response," Applied Energy, Elsevier, vol. 317(C).
    10. Cristina Sousa & Evaldo Costa, 2022. "Types of Policies for the Joint Diffusion of Electric Vehicles with Renewable Energies and Their Use Worldwide," Energies, MDPI, vol. 15(20), pages 1-19, October.
    11. Mansouri, Seyed Amir & Rezaee Jordehi, Ahmad & Marzband, Mousa & Tostado-Véliz, Marcos & Jurado, Francisco & Aguado, José A., 2023. "An IoT-enabled hierarchical decentralized framework for multi-energy microgrids market management in the presence of smart prosumers using a deep learning-based forecaster," Applied Energy, Elsevier, vol. 333(C).
    12. Silva, Jéssica Alice A. & López, Juan Camilo & Guzman, Cindy Paola & Arias, Nataly Bañol & Rider, Marcos J. & da Silva, Luiz C.P., 2023. "An IoT-based energy management system for AC microgrids with grid and security constraints," Applied Energy, Elsevier, vol. 337(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Villanueva-Rosario, Junior Alexis & Santos-García, Félix & Aybar-Mejía, Miguel Euclides & Mendoza-Araya, Patricio & Molina-García, Angel, 2022. "Coordinated ancillary services, market participation and communication of multi-microgrids: A review," Applied Energy, Elsevier, vol. 308(C).
    2. He, Shuaijia & Gao, Hongjun & Chen, Zhe & Liu, Junyong & Zhao, Liang & Wu, Gang & Xu, Song, 2022. "Low-carbon distribution system planning considering flexible support of zero-carbon energy station," Energy, Elsevier, vol. 244(PB).
    3. Zhang, Li & Gao, Yan & Zhu, Hongbo & Tao, Li, 2022. "Bi-level stochastic real-time pricing model in multi-energy generation system: A reinforcement learning approach," Energy, Elsevier, vol. 239(PA).
    4. Zhou, Xu & Ma, Zhongjing & Zou, Suli & Zhang, Jinhui, 2022. "Consensus-based distributed economic dispatch for Multi Micro Energy Grid systems under coupled carbon emissions," Applied Energy, Elsevier, vol. 324(C).
    5. Alizadeh, Ali & Kamwa, Innocent & Moeini, Ali & Mohseni-Bonab, Seyed Masoud, 2023. "Energy management in microgrids using transactive energy control concept under high penetration of Renewables; A survey and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    6. Mohammadpour Shotorbani, Amin & Zeinal-Kheiri, Sevda & Chhipi-Shrestha, Gyan & Mohammadi-Ivatloo, Behnam & Sadiq, Rehan & Hewage, Kasun, 2021. "Enhanced real-time scheduling algorithm for energy management in a renewable-integrated microgrid," Applied Energy, Elsevier, vol. 304(C).
    7. Guodong Liu & Maximiliano F. Ferrari & Thomas B. Ollis & Aditya Sundararajan & Mohammed Olama & Yang Chen, 2023. "Distributed Energy Management for Networked Microgrids with Hardware-in-the-Loop Validation," Energies, MDPI, vol. 16(7), pages 1-27, March.
    8. Wu, Kunming & Li, Qiang & Chen, Ziyu & Lin, Jiayang & Yi, Yongli & Chen, Minyou, 2021. "Distributed optimization method with weighted gradients for economic dispatch problem of multi-microgrid systems," Energy, Elsevier, vol. 222(C).
    9. Álex Omar Topa Gavilema & José Domingo Álvarez & José Luis Torres Moreno & Manuel Pérez García, 2021. "Towards Optimal Management in Microgrids: An Overview," Energies, MDPI, vol. 14(16), pages 1-25, August.
    10. Qiu, Haifeng & Gu, Wei & Liu, Pengxiang & Sun, Qirun & Wu, Zhi & Lu, Xi, 2022. "Application of two-stage robust optimization theory in power system scheduling under uncertainties: A review and perspective," Energy, Elsevier, vol. 251(C).
    11. Li, Li & Dong, Mi & Song, Dongran & Yang, Jian & Wang, Qibing, 2022. "Distributed and real-time economic dispatch strategy for an islanded microgrid with fair participation of thermostatically controlled loads," Energy, Elsevier, vol. 261(PB).
    12. Taler, Dawid & Sobota, Tomasz & Jaremkiewicz, Magdalena & Taler, Jan, 2022. "Control of the temperature in the hot liquid tank by using a digital PID controller considering the random errors of the thermometer indications," Energy, Elsevier, vol. 239(PE).
    13. Wang, Chong & Ju, Ping & Wu, Feng & Pan, Xueping & Wang, Zhaoyu, 2022. "A systematic review on power system resilience from the perspective of generation, network, and load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    14. Wang, Zekai & Ding, Tao & Jia, Wenhao & Huang, Can & Mu, Chenggang & Qu, Ming & Shahidehpour, Mohammad & Yang, Yongheng & Blaabjerg, Frede & Li, Li & Wang, Kang & Chi, Fangde, 2022. "Multi-stage stochastic programming for resilient integrated electricity and natural gas distribution systems against typhoon natural disaster attacks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    15. Md Shafiullah & Akib Mostabe Refat & Md Ershadul Haque & Dewan Mabrur Hasan Chowdhury & Md Sanower Hossain & Abdullah G. Alharbi & Md Shafiul Alam & Amjad Ali & Shorab Hossain, 2022. "Review of Recent Developments in Microgrid Energy Management Strategies," Sustainability, MDPI, vol. 14(22), pages 1-30, November.
    16. Yanbin Li & Yanting Sun & Junjie Zhang & Feng Zhang, 2022. "Optimal Microgrid System Operating Strategy Considering Variable Wind Power Outputs and the Cooperative Game among Subsystem Operators," Energies, MDPI, vol. 15(18), pages 1-20, September.
    17. Zhang, Dongdong & Li, Chunjiao & Goh, Hui Hwang & Ahmad, Tanveer & Zhu, Hongyu & Liu, Hui & Wu, Thomas, 2022. "A comprehensive overview of modeling approaches and optimal control strategies for cyber-physical resilience in power systems," Renewable Energy, Elsevier, vol. 189(C), pages 1383-1406.
    18. Ziad M. Ali & Martin Calasan & Shady H. E. Abdel Aleem & Francisco Jurado & Foad H. Gandoman, 2023. "Applications of Energy Storage Systems in Enhancing Energy Management and Access in Microgrids: A Review," Energies, MDPI, vol. 16(16), pages 1-41, August.
    19. Md Jahidur Rahman & Tahar Tafticht & Mamadou Lamine Doumbia & Iqbal Messaïf, 2023. "Optimal Inverter Control Strategies for a PV Power Generation with Battery Storage System in Microgrid," Energies, MDPI, vol. 16(10), pages 1-36, May.
    20. 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).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:245:y:2022:i:c:s0360544222001311. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.