IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v99y2016icp48-57.html
   My bibliography  Save this article

Cooperative energy dispatch for multiple autonomous microgrids with distributed renewable sources and storages

Author

Listed:
  • Fang, Xinli
  • Ma, Shihao
  • Yang, Qiang
  • Zhang, Jintao

Abstract

The increasing number of intermittent renewable DGs (distributed generators) penetrating into current MGs (microgrids) brings direct challenges in operation, e.g. voltage raise effect, power quality, protection and stability, energy management, e.g. DG-demand matching energy utilization efficiency, as well as power supply security of CLs (critical loads). This paper presents a collective energy dispatch solution to optimally coordinate DGs, distributed SUs (storage units) and critical demands across multiple AMGs (autonomous MGs) based on a “tree stem-leaves” approach. The energy distribution network consisting of multiple AMGs are modeled mathematically as a weighted matrix simultaneously considering power loss and reliability statistics. The revised MST (minimum spanning tree) algorithm is adopted to identify the optimal DG-CL and SU-CL mappings (“tree stems”) for energy supply, and the LMI (linear matrix inequality) algorithm determines the NLs (non-critical loads) to be supplied and added to the “stems” as “tree leaves”. Such energy network structure formed by “stem” and “leaves” can vary over time in case that significant changes are identified during MG operation (e.g. DG and demand dynamics), and the functionalities can be implemented through intelligent system management tools, e.g. multi-agent systems. As a result, it can consistently lead to optimal energy management with significantly improved CL supply security, global DG utilization efficiency, and generation-demand matching performance. The suggested solution is verified by carrying out a set of simulation experiments for a range of network scenarios (e.g. various renewable penetration ratios) based on IEEE 33-bus network model, and the numerical result clearly confirms the effectiveness and technical benefits.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:99:y:2016:i:c:p:48-57
    DOI: 10.1016/j.energy.2016.01.036
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216000578
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2016.01.036?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. Fang, Xinli & Yang, Qiang & Wang, Jianhui & Yan, Wenjun, 2016. "Coordinated dispatch in multiple cooperative autonomous islanded microgrids," Applied Energy, Elsevier, vol. 162(C), pages 40-48.
    2. Rodrigues, E.M.G. & Godina, R. & Santos, S.F. & Bizuayehu, A.W. & Contreras, J. & Catalão, J.P.S., 2014. "Energy storage systems supporting increased penetration of renewables in islanded systems," Energy, Elsevier, vol. 75(C), pages 265-280.
    3. Rekik, Mouna & Abdelkafi, Achraf & Krichen, Lotfi, 2015. "A micro-grid ensuring multi-objective control strategy of a power electrical system for quality improvement," Energy, Elsevier, vol. 88(C), pages 351-363.
    4. Niknam, Taher & Golestaneh, Faranak & Shafiei, Mehdi, 2013. "Probabilistic energy management of a renewable microgrid with hydrogen storage using self-adaptive charge search algorithm," Energy, Elsevier, vol. 49(C), pages 252-267.
    5. Basir Khan, M. Reyasudin & Jidin, Razali & Pasupuleti, Jagadeesh & Shaaya, Sharifah Azwa, 2015. "Optimal combination of solar, wind, micro-hydro and diesel systems based on actual seasonal load profiles for a resort island in the South China Sea," Energy, Elsevier, vol. 82(C), pages 80-97.
    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. Zhang, Xiaoshun & Yu, Tao & Xu, Zhao & Fan, Zhun, 2018. "A cyber-physical-social system with parallel learning for distributed energy management of a microgrid," Energy, Elsevier, vol. 165(PA), pages 205-221.
    2. José Luis Ruiz Duarte & Neng Fan, 2022. "Operation of a Power Grid with Embedded Networked Microgrids and Onsite Renewable Technologies," Energies, MDPI, vol. 15(7), pages 1-24, March.
    3. Zhao, Zhigao & Yang, Jiandong & Chung, C.Y. & Yang, Weijia & He, Xianghui & Chen, Man, 2021. "Performance enhancement of pumped storage units for system frequency support based on a novel small signal model," Energy, Elsevier, vol. 234(C).
    4. Baghaee, H.R. & Mirsalim, M. & Gharehpetian, G.B. & Talebi, H.A., 2016. "Reliability/cost-based multi-objective Pareto optimal design of stand-alone wind/PV/FC generation microgrid system," Energy, Elsevier, vol. 115(P1), pages 1022-1041.
    5. 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.
    6. Nawaz, Arshad & Zhou, Min & Wu, Jing & Long, Chengnian, 2022. "A comprehensive review on energy management, demand response, and coordination schemes utilization in multi-microgrids network," Applied Energy, Elsevier, vol. 323(C).
    7. 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.
    8. Farihan Mohamad & Jiashen Teh, 2018. "Impacts of Energy Storage System on Power System Reliability: A Systematic Review," Energies, MDPI, vol. 11(7), pages 1-23, July.
    9. Xiuyun Wang & Shaoxin Chen & Yibing Zhou & Jian Wang & Yang Cui, 2018. "Optimal Dispatch of Microgrid with Combined Heat and Power System Considering Environmental Cost," Energies, MDPI, vol. 11(10), pages 1-23, September.

    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. Fang, Xinli & Yang, Qiang & Dong, Wei, 2018. "Fuzzy decision based energy dispatch in offshore industrial microgrid with desalination process and multi-type DGs," Energy, Elsevier, vol. 148(C), pages 744-755.
    2. Zizzo, G. & Beccali, M. & Bonomolo, M. & Di Pietra, B. & Ippolito, M.G. & La Cascia, D. & Leone, G. & Lo Brano, V. & Monteleone, F., 2017. "A feasibility study of some DSM enabling solutions in small islands: The case of Lampedusa," Energy, Elsevier, vol. 140(P1), pages 1030-1046.
    3. Huang, Qisheng & Xu, Yunjian & Courcoubetis, Costas, 2020. "Stackelberg competition between merchant and regulated storage investment in wholesale electricity markets," Applied Energy, Elsevier, vol. 264(C).
    4. Jiaxin Lu & Weijun Wang & Yingchao Zhang & Song Cheng, 2017. "Multi-Objective Optimal Design of Stand-Alone Hybrid Energy System Using Entropy Weight Method Based on HOMER," Energies, MDPI, vol. 10(10), pages 1-17, October.
    5. Liao, Rih-Neng & Chen, Tsai-Hsiang & Chang, Wei-Shiou, 2016. "Fast screening techniques and process for grid interconnection of wind-storage systems," Energy, Elsevier, vol. 115(P1), pages 770-780.
    6. Fu, Xueqian & Guo, Qinglai & Sun, Hongbin & Pan, Zhaoguang & Xiong, Wen & Wang, Li, 2017. "Typical scenario set generation algorithm for an integrated energy system based on the Wasserstein distance metric," Energy, Elsevier, vol. 135(C), pages 153-170.
    7. Heo, SungKu & Byun, Jaewon & Ifaei, Pouya & Ko, Jaerak & Ha, Byeongmin & Hwangbo, Soonho & Yoo, ChangKyoo, 2024. "Towards mega-scale decarbonized industrial park (Mega-DIP): Generative AI-driven techno-economic and environmental assessment of renewable and sustainable energy utilization in petrochemical industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    8. Changyu Zhou & Guohe Huang & Jiapei Chen, 2019. "A Type-2 Fuzzy Chance-Constrained Fractional Integrated Modeling Method for Energy System Management of Uncertainties and Risks," Energies, MDPI, vol. 12(13), pages 1-21, June.
    9. Jinwoo Jeong & Heewon Shin & Hwachang Song & Byongjun Lee, 2018. "A Countermeasure for Preventing Flexibility Deficit under High-Level Penetration of Renewable Energies: A Robust Optimization Approach," Sustainability, MDPI, vol. 10(11), pages 1-16, November.
    10. 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.
    11. Bahramara, S. & Moghaddam, M. Parsa & Haghifam, M.R., 2016. "Optimal planning of hybrid renewable energy systems using HOMER: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 609-620.
    12. Vinay Kumar Jadoun & Nipun Sharma & Piyush Jha & Jayalakshmi N. S. & Hasmat Malik & Fausto Pedro Garcia Márquez, 2021. "Optimal Scheduling of Dynamic Pricing Based V2G and G2V Operation in Microgrid Using Improved Elephant Herding Optimization," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    13. Al-Zareer, Maan & Dincer, Ibrahim & Rosen, Marc A., 2017. "Analysis and assessment of novel liquid air energy storage system with district heating and cooling capabilities," Energy, Elsevier, vol. 141(C), pages 792-802.
    14. Changyu Zhou & Guohe Huang & Jiapei Chen, 2018. "A Multi-Objective Energy and Environmental Systems Planning Model: Management of Uncertainties and Risks for Shanxi Province, China," Energies, MDPI, vol. 11(10), pages 1-21, October.
    15. Poolla, Chaitanya & Ishihara, Abraham K. & Milito, Rodolfo, 2019. "Designing near-optimal policies for energy management in a stochastic environment," Applied Energy, Elsevier, vol. 242(C), pages 1725-1737.
    16. Aziz, Ali Saleh & Tajuddin, Mohammad Faridun Naim & Adzman, Mohd Rafi & Azmi, Azralmukmin & Ramli, Makbul A.M., 2019. "Optimization and sensitivity analysis of standalone hybrid energy systems for rural electrification: A case study of Iraq," Renewable Energy, Elsevier, vol. 138(C), pages 775-792.
    17. Hauge, H.H. & Presser, V. & Burheim, O., 2014. "In-situ and ex-situ measurements of thermal conductivity of supercapacitors," Energy, Elsevier, vol. 78(C), pages 373-383.
    18. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2016. "Optimal design and techno-economic analysis of an autonomous small isolated microgrid aiming at high RES penetration," Energy, Elsevier, vol. 116(P1), pages 364-379.
    19. Ahmad Khan, Aftab & Naeem, Muhammad & Iqbal, Muhammad & Qaisar, Saad & Anpalagan, Alagan, 2016. "A compendium of optimization objectives, constraints, tools and algorithms for energy management in microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1664-1683.
    20. McKenna, Russell & Merkel, Erik & Fichtner, Wolf, 2017. "Energy autonomy in residential buildings: A techno-economic model-based analysis of the scale effects," Applied Energy, Elsevier, vol. 189(C), pages 800-815.

    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:99:y:2016:i:c:p:48-57. 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.