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The Optimal Dispatching Strategy of Microgrid Group Based on Distributed Cooperative Architecture

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Recent Featured Applications of Artificial Intelligence Methods. LSMS 2020 and ICSEE 2020 Workshops (LSMS 2020, ICSEE 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1303))

Abstract

This paper establishes a distributed optimization operation model of microgrid group to solve the problem of privacy security and economic conflict among different stakeholders. Firstly, the factors affecting the operation cost are analyzed from the perspective of the internal equipment and external active/reactive power transactions of the microgrid. Then, each node in the microgrid group takes the overall operating cost as the optimal objective, and particle swarm optimization (PSO) algorithm is used to optimize the model. Furthermore, the collaborative optimization algorithm is adopted to reach an agreement of the respective optimization results through the exchange of key information among different node agents, and the optimal dispatching strategy is obtained independently. Finally, the model is applied to the improved 30-node microgrid group system. The results show that the model and algorithm can reduce the operating cost of the microgrid group, ensure the maximum benefit of the individual subject, and achieve the optimal operation of the multi-microgrid system.

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References

  1. Chen, Q., Keyou, W., Guojie, L., Bei, H., Shaojun, X., Wei, Z.: Hierarchical and distributed optimal scheduling of AC/DC hybrid active distribution network. Proc. CSEE 37(7), 1909–1917 (2017)

    Google Scholar 

  2. Antoniadou-Plytaria, K.E., Kouveliotis-Lysikatos, I.N., Georgilakis, P.S., Hatziargyriou, N.D.: Distributed and decentralized voltage control of smart distribution networks: models, methods, and future research. IEEE Trans. Smart Grid 8(6), 2999–3008 (2017)

    Article  Google Scholar 

  3. Arefifar, S.A., Ordonez, M., Mohamed, Y.A.R.I.: Energy management in multi-microgrid systems-development and assessment. IEEE Trans. Power Syst. 3(2), 910–922 (2017)

    Google Scholar 

  4. Li, J., Liu, Y., Wu, L.: Optimal operation for community based multi-party microgrid in grid-connected and islanded modes. IEEE Trans Smart Grid 9(2), 756–765 (2018)

    Google Scholar 

  5. Nikmehr, N., Najafi Ravadanegh, S.: Optimal power dispatch of multi-microgrids at future smart distribution grids. IEEE Trans Smart Grid 6(4), 1648–1657 (2015)

    Article  Google Scholar 

  6. Rahbar, K., Chai, C.C., Zhang, R.: Energy cooperation optimization in microgrids with renewable energy integration. IEEE Trans. Smart Grid 9(2), 1482–1497 (2018)

    Article  Google Scholar 

  7. Yanqian, Z., Xiaodong, D., Yang, Z.: Research on optimally coordinating dispatching of multi microgrid based on bi-level optimization theory. Shaanxi Electric Power 44(12), 1–5+28 (2016)

    Google Scholar 

  8. Chiu, W.Y., Sun, H., Poor, H.V.: A multiobjective approach to multimicrogrid system design. IEEE Trans. Smart Grid 6(5), 2263–2272 (2015)

    Article  Google Scholar 

  9. Lu, T., Wang, Z., Ai, Q., Lee, W.J.: Interactive model for energy management of clustered microgrids. IEEE Trans. Ind. Appl. 53(3), 1739–1750 (2017)

    Article  Google Scholar 

  10. Yonzhi, Z., Hao, W., Yining, L.: Dynamic dispatch of multi-microgrid for neighboring Islands based on MCS-PSO algorithm. Autom. Electric Power Syst. 38(9), 204–210 (2014)

    Google Scholar 

  11. Bui, V.H., Hussain, A., Kim, H.M.: A multiagent-based hierarchical energy management strategy for multi-microgrids considering adjustable power and demand response. IEEE Trans. Smart Grid 9(2), 1323–1333 (2018)

    Article  Google Scholar 

  12. Wang, Y., Mao, S., Nelms, R.M.: On hierarchical power scheduling for the Macrogrid and cooperative microgrids. IEEE Trans. Ind. Inform. 11(6), 1574–1584 (2015)

    Article  Google Scholar 

  13. Liu, W., Gu, W., Xu, Y., Wang, Y., Zhang, K.: General distributed secondary control for multi-microgrids with both PQ-controlled and droop-controlled distributed generators. IET Gen. Tran. Dist. 31(2), 707–718 (2017)

    Article  Google Scholar 

  14. Marzband, M., Parhizi, N., Savaghebi, M., Guerrero, J.M.: Distributed smart decision-making for a multimicrogrid system based on a hierarchical interactive architecture. IEEE Trans. Energy Conv. 31(2), 637–648 (2016)

    Article  Google Scholar 

  15. Ran, H., Qian, A., Ziqing, J.: Bi-level game strategy for multi-agent with incomplete information in regional integrated energy system. Autom. Electric Power Syst. 42(4), 194–201 (2018)

    Google Scholar 

  16. Hong, L., Jifeng, L., Shaoyun, G.: Coordinated scheduling of grid-connected integrated energy microgrid based on multi-agent game and reinforcement learning. Autom. Electr. Power Syst. 43(1), 40–50 (2019)

    Google Scholar 

  17. Gregoratti, D., Matamoros, J.: Distributed energy trading: the multiple-microgrid case. IEEE Trans. Ind. Electr. 62(4), 2551–2559 (2015)

    Article  Google Scholar 

  18. Wang, T., O’Neill, D., Kamath, H.: Dynamic control and optimization of distributed energy resources in a microgrid. IEEE Trans. Smart Grid 6(6), 2884–2894 (2015)

    Article  Google Scholar 

  19. Xu, Y., Zhang, W., Hug, G., Kar, S., Li, Z.: Cooperative control of distributed energy storage systems in a microgrid. IEEE Trans. Smart Grid 6(1), 238–248 (2015)

    Article  Google Scholar 

  20. Zhou, D., Blaabjerg, F.: Bandwidth oriented proportional-integral controller design for back-to-back power converters in DFIG wind turbine system. IET Renew. Power Gen. 11(7), 941–951 (2017)

    Article  Google Scholar 

  21. Olfati-Saber, R., Fax, J.A., Murray, R.M.: Consensus and cooperation in networked multi-agent systems. Proc. IEEE 95(1), 215–233 (2007)

    Article  MATH  Google Scholar 

  22. Utkarsh, K., Trivedi, A., Srinivasan, D., Reindl, T.: A consensus-based distributed computational intelligence technique for real-time optimal control in smart distribution grids. IEEE Trans. Merging Topics Comput. Intell. 1(1), 51–60 (2017)

    Article  Google Scholar 

  23. Qiming, F., Jichun, L., Yangfang, Y., Qi, W., Shichao, N., Lifeng, K.: Multi-local grid optimization economic dispatch with different types of energy. Power Syst. Technol. 43(2), 452–461 (2019)

    Google Scholar 

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Acknowledgement

Supported by Natural Science Foundation of China (No. 61773253, 61533010), Key Project of Science and Technology Commission of Shanghai Municipality under Grant No. 16010500300.

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Authors and Affiliations

  1. Shanghai Key Laboratory of Power Station Automation Technology, Shanghai University, Shanghai, 200444, China

    Xue Li, Yunpeng Zhang, Dajun Du, Zhourong Zhang & Meng Xia

Authors
  1. Xue Li
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  2. Yunpeng Zhang
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  3. Dajun Du
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  4. Zhourong Zhang
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  5. Meng Xia
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Corresponding author

Correspondence to Yunpeng Zhang .

Editor information

Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Minrui Fei

  2. University of Leeds, Leeds, UK

    Kang Li

  3. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Zhile Yang

  4. Shanghai University, Shanghai, China

    Qun Niu

  5. Shanghai University, Shanghai, China

    Xin Li

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Li, X., Zhang, Y., Du, D., Zhang, Z., Xia, M. (2020). The Optimal Dispatching Strategy of Microgrid Group Based on Distributed Cooperative Architecture. In: Fei, M., Li, K., Yang, Z., Niu, Q., Li, X. (eds) Recent Featured Applications of Artificial Intelligence Methods. LSMS 2020 and ICSEE 2020 Workshops. LSMS ICSEE 2020 2020. Communications in Computer and Information Science, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-6378-6_2

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  • DOI: https://doi.org/10.1007/978-981-33-6378-6_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-6377-9

  • Online ISBN: 978-981-33-6378-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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