IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v236y2021ics0360544221017722.html
   My bibliography  Save this article

Fast microgrids formation of distribution network with high penetration of DERs considering reliability

Author

Listed:
  • Yang, Tongxu
  • Zhang, Limei
  • Zhen, Linteng
  • Liu, Yongfu
  • Song, Qianqian
  • Tang, Wei

Abstract

Microgrids (MGs) formation of distribution network with high penetration of distributed energy resources (DERs) affects not only the improvement of power supply reliability, but also the utilization efficiency of renewable resources. Here a fast partition method constructing MGs is proposed by combining depth search with a modified imperial competition algorithm (MICA). For the purpose of decreasing search space as well as assuring DERs maximum utilization, Candidate Island is investigated to determine the maximum reachability boundary of MGs in island mode. When in the dilemma of constructing Isolated Island (i.e., MGs with single DERs) or Jointed Island (i.e., MGs with multiple DERs), the reliability calculation method for MGs with multiple DERs and multisystem is available here. Also, the principle of MGs construction is presented by considering load grade, voltage loss and reliability. On this basis, MICA is employed to carry out the construction of MGs by competing for the intersection among multiple MGs and evolve the optimal island with high reliability accordingly. Furthermore, the parallel strategy improving the efficiency of island partition is given to guarantee an immediate response in abnormal, emergent and fault states. IEEE RBTS Bus 6 with additional DERs and several modified distribution networks with multiple DERs verified the effectiveness of the proposed method.

Suggested Citation

  • Yang, Tongxu & Zhang, Limei & Zhen, Linteng & Liu, Yongfu & Song, Qianqian & Tang, Wei, 2021. "Fast microgrids formation of distribution network with high penetration of DERs considering reliability," Energy, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:energy:v:236:y:2021:i:c:s0360544221017722
    DOI: 10.1016/j.energy.2021.121524
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221017722
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.121524?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. Mohammadi-ivatloo, Behnam & Rabiee, Abbas & Soroudi, Alireza & Ehsan, Mehdi, 2012. "Imperialist competitive algorithm for solving non-convex dynamic economic power dispatch," Energy, Elsevier, vol. 44(1), pages 228-240.
    2. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2018. "Optimization of hydropower reservoirs operation balancing generation benefit and ecological requirement with parallel multi-objective genetic algorithm," Energy, Elsevier, vol. 153(C), pages 706-718.
    3. Zhang, Shenxi & Cheng, Haozhong & Li, Ke & Tai, Nengling & Wang, Dan & Li, Furong, 2018. "Multi-objective distributed generation planning in distribution network considering correlations among uncertainties," Applied Energy, Elsevier, vol. 226(C), pages 743-755.
    4. Gilani, Mohammad Amin & Kazemi, Ahad & Ghasemi, Mostafa, 2020. "Distribution system resilience enhancement by microgrid formation considering distributed energy resources," Energy, Elsevier, vol. 191(C).
    5. Ravindra, Kumudhini & Iyer, Parameshwar P., 2014. "Decentralized demand–supply matching using community microgrids and consumer demand response: A scenario analysis," Energy, Elsevier, vol. 76(C), pages 32-41.
    6. Tabar, Vahid Sohrabi & Abbasi, Vahid, 2019. "Energy management in microgrid with considering high penetration of renewable resources and surplus power generation problem," Energy, Elsevier, vol. 189(C).
    7. Nguyen, Thang Trung, 2019. "A high performance social spider optimization algorithm for optimal power flow solution with single objective optimization," Energy, Elsevier, vol. 171(C), pages 218-240.
    8. Kim, Tae Hyun & Shin, Hansol & Kwag, Kyuhyeong & Kim, Wook, 2020. "A parallel multi-period optimal scheduling algorithm in microgrids with energy storage systems using decomposed inter-temporal constraints," Energy, Elsevier, vol. 202(C).
    9. Zhang, Jingrui & Lin, Shuang & Liu, Houde & Chen, Yalin & Zhu, Mingcheng & Xu, Yinliang, 2017. "A small-population based parallel differential evolution algorithm for short-term hydrothermal scheduling problem considering power flow constraints," Energy, Elsevier, vol. 123(C), pages 538-554.
    10. Ji, Haoran & Wang, Chengshan & Li, Peng & Song, Guanyu & Wu, Jianzhong, 2018. "SOP-based islanding partition method of active distribution networks considering the characteristics of DG, energy storage system and load," Energy, Elsevier, vol. 155(C), pages 312-325.
    11. Barra, P.H.A. & Coury, D.V. & Fernandes, R.A.S., 2020. "A survey on adaptive protection of microgrids and distribution systems with distributed generators," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    12. Karimi, M. & Karami, H. & Gholami, M. & Khatibzadehazad, H. & Moslemi, N., 2018. "Priority index considering temperature and date proximity for selection of similar days in knowledge-based short term load forecasting method," Energy, Elsevier, vol. 144(C), pages 928-940.
    13. Younesi, Abdollah & Shayeghi, Hossein & Safari, Amin & Siano, Pierluigi, 2020. "Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation," Energy, Elsevier, vol. 207(C).
    14. Guan, Jinyu & Tang, Hao & Wang, Ke & Yao, Jianguo & Yang, Shengchun, 2020. "A parallel multi-scenario learning method for near-real-time power dispatch optimization," Energy, Elsevier, vol. 202(C).
    15. Rajamand, Sahbasadat, 2020. "Effect of demand response program of loads in cost optimization of microgrid considering uncertain parameters in PV/WT, market price and load demand," Energy, Elsevier, vol. 194(C).
    16. Afzali, Peyman & Keynia, Farshid & Rashidinejad, Masoud, 2019. "A new model for reliability-centered maintenance prioritisation of distribution feeders," Energy, Elsevier, vol. 171(C), pages 701-709.
    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. Amine, Hartani Mohamed & Aissa, Benhammou & Rezk, Hegazy & Messaoud, Hamouda & Othmane, Adbdelkhalek & Saad, Mekhilef & Abdelkareem, Mohammad Ali, 2023. "Enhancing hybrid energy storage systems with advanced low-pass filtration and frequency decoupling for optimal power allocation and reliability of cluster of DC-microgrids," Energy, Elsevier, vol. 282(C).
    2. Yang, Shuxia & Wang, Xiongfei & Xu, Jiayu & Tang, Mingrun & Chen, Guang, 2023. "Distribution network adaptability assessment considering distributed PV “reverse power flow” behavior - a case study in Beijing," Energy, Elsevier, vol. 275(C).
    3. Hartani, Mohamed Amine & Rezk, Hegazy & Benhammou, Aissa & Hamouda, Messaoud & Abdelkhalek, Othmane & Mekhilef, Saad & Olabi, A.G., 2023. "Proposed frequency decoupling-based fuzzy logic control for power allocation and state-of-charge recovery of hybrid energy storage systems adopting multi-level energy management for multi-DC-microgrid," Energy, Elsevier, vol. 278(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. Nikoobakht, Ahmad & Aghaei, Jamshid, 2022. "Resilience promotion of active distribution grids under high penetration of renewables using flexible controllers," Energy, Elsevier, vol. 257(C).
    2. Li, Shuijia & Gong, Wenyin & Wang, Ling & Yan, Xuesong & Hu, Chengyu, 2020. "Optimal power flow by means of improved adaptive differential evolution," Energy, Elsevier, vol. 198(C).
    3. Shahbazbegian, Vahid & Dehghani, Farnam & Shafiyi, Mohammad Agha & Shafie-khah, Miadreza & Laaksonen, Hannu & Ameli, Hossein, 2023. "Techno-economic assessment of energy storage systems in multi-energy microgrids utilizing decomposition methodology," Energy, Elsevier, vol. 283(C).
    4. Xu, Jiuping & Tian, Yalou & Wang, Fengjuan & Yang, Guocan & Zhao, Chuandang, 2024. "Resilience-economy-environment equilibrium based configuration interaction approach towards distributed energy system in energy intensive industry parks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    5. Zou, Dexuan & Li, Steven & Kong, Xiangyong & Ouyang, Haibin & Li, Zongyan, 2018. "Solving the dynamic economic dispatch by a memory-based global differential evolution and a repair technique of constraint handling," Energy, Elsevier, vol. 147(C), pages 59-80.
    6. Boroumandfar, Gholamreza & Khajehzadeh, Alimorad & Eslami, Mahdiyeh & Syah, Rahmad B.Y., 2023. "Information gap decision theory with risk aversion strategy for robust planning of hybrid photovoltaic/wind/battery storage system in distribution networks considering uncertainty," Energy, Elsevier, vol. 278(PA).
    7. Shen, Yueqing & Qian, Tong & Li, Weiwei & Zhao, Wei & Tang, Wenhu & Chen, Xingyu & Yu, Zeyuan, 2023. "Mobile energy storage systems with spatial–temporal flexibility for post-disaster recovery of power distribution systems: A bilevel optimization approach," Energy, Elsevier, vol. 282(C).
    8. da Silva, Fellipe Sartori & Matelli, José Alexandre, 2021. "Resilience in cogeneration systems: Metrics for evaluation and influence of design aspects," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    9. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2019. "China’s large-scale hydropower system: operation characteristics, modeling challenge and dimensionality reduction possibilities," Renewable Energy, Elsevier, vol. 136(C), pages 805-818.
    10. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    11. Constantino Dário Justo & José Eduardo Tafula & Pedro Moura, 2022. "Planning Sustainable Energy Systems in the Southern African Development Community: A Review of Power Systems Planning Approaches," Energies, MDPI, vol. 15(21), pages 1-28, October.
    12. Gong, Mingju & Zhao, Yin & Sun, Jiawang & Han, Cuitian & Sun, Guannan & Yan, Bo, 2022. "Load forecasting of district heating system based on Informer," Energy, Elsevier, vol. 253(C).
    13. Chen, Jie & Huang, Shoujun & Shahabi, Laleh, 2021. "Economic and environmental operation of power systems including combined cooling, heating, power and energy storage resources using developed multi-objective grey wolf algorithm," Applied Energy, Elsevier, vol. 298(C).
    14. Hu Hu & Kan Yang & Lyuwen Su & Zhe Yang, 2019. "A Novel Adaptive Multi-Objective Particle Swarm Optimization Based on Decomposition and Dominance for Long-term Generation Scheduling of Cascade Hydropower System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(11), pages 4007-4026, September.
    15. Dehnavi, Ehsan & Abdi, Hamdi, 2016. "Optimal pricing in time of use demand response by integrating with dynamic economic dispatch problem," Energy, Elsevier, vol. 109(C), pages 1086-1094.
    16. Singh, Pushpendra & Meena, Nand K. & Yang, Jin & Vega-Fuentes, Eduardo & Bishnoi, Shree Krishna, 2020. "Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks," Applied Energy, Elsevier, vol. 278(C).
    17. Younes Zahraoui & Ibrahim Alhamrouni & Saad Mekhilef & M. Reyasudin Basir Khan & Mehdi Seyedmahmoudian & Alex Stojcevski & Ben Horan, 2021. "Energy Management System in Microgrids: A Comprehensive Review," Sustainability, MDPI, vol. 13(19), pages 1-33, September.
    18. Amr Khaled Khamees & Almoataz Y. Abdelaziz & Makram R. Eskaros & Mahmoud A. Attia & Mariam A. Sameh, 2022. "Optimal Power Flow with Stochastic Renewable Energy Using Three Mixture Component Distribution Functions," Sustainability, MDPI, vol. 15(1), pages 1-21, December.
    19. Derakhshan, Ghasem & Shayanfar, Heidar Ali & Kazemi, Ahad, 2016. "The optimization of demand response programs in smart grids," Energy Policy, Elsevier, vol. 94(C), pages 295-306.
    20. Zhu, Jiawei & Lin, Yishuai & Lei, Weidong & Liu, Youquan & Tao, Mengling, 2019. "Optimal household appliances scheduling of multiple smart homes using an improved cooperative algorithm," Energy, Elsevier, vol. 171(C), pages 944-955.

    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:236:y:2021:i:c:s0360544221017722. 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.