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Distributed cooperative control algorithm for optimal power sharing for AC microgrids using Cournot game theory

  • S.I. : ATCI 2020
  • Published:
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Abstract

Research on the optimal power allocation of large-scale distributed generator (DG) units based on user power generation to access microgrids (MGs) in a multi-agent system framework has recently become the focus of modern grid and energy concerns. In this paper, according to the Cournot oligopoly game, the Nash equilibrium point between the power generation company and power generation user of the MG operating in island mode is obtained. According to the obtained Nash equilibrium point, the optimal ratio of power generated by the power generation company and by the power generation user in the model is calculated. At the same time, to achieve the maximum benefit and stable operation of the MG, a distributed cooperative control algorithm based on consensus theory is proposed. This control algorithm can cause each DG to generate power according to the total consumption load. The optimal power generation ratio distribution based on the Nash equilibrium point eliminates the steady-state frequency deviation of each DG in the MG, thereby ensuring the user’s power quality. The simulation results show that the control algorithm can achieve the above research goals.

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References

  1. Lai J, Lu X, Yu X, Monti A (2019) Cluster-oriented distributed cooperative control for multiple AC microgrids. IEEE Trans Ind Inform 15(11):5906–5918

    Article  Google Scholar 

  2. Olivares DE, Sani AM, Etemadi AH et al (2014) Trends in microgrid control. IEEE Trans Smart Grid 5(4):1905–1919

    Article  Google Scholar 

  3. Wu D, Tang F, Dragicevic T, Vasquez JC, Guerrero JM (2014) Autonomous active power control for islanded AC microgrids with photovoltaic generation and energy storage system. IEEE Trans Energy Convers 29(4):882–892

    Article  Google Scholar 

  4. Mahmood H, Michaelson D, Jiang J (2014) Accurate reactive power sharing in an islanded microgrid using adaptive virtual impedances. IEEE Trans Power Electron 30(3):1605–1617

    Article  Google Scholar 

  5. Lai J, Lu X, Yu X, Monti A et al (2020) Distributed voltage regulation for cyber-physical microgrids with coupling delays and slow switching topologies. IEEE Trans Syst Man Cybern Syst 50(1):100–110

    Article  Google Scholar 

  6. Lu X, Lai J (2020) Distributed cluster cooperation for multiple DC MGs over two-layer switching topologies. IEEE Trans Smart Grid. https://doi.org/10.1109/TSG.2020.3005595 (to be published)

    Article  Google Scholar 

  7. Han Y, Shen P, Zhao X, Guerrero JM (2016) An enhanced power sharing scheme for voltage unbalance and harmonics compensation in an islanded AC microgrid. IEEE Trans Energy Convers 31(3):1037–1050

    Article  Google Scholar 

  8. Guerrero JM, Vasquez JC, Matas J et al (2010) Hierarchical control of droop-controlled AC and DC microgrids—a general approach toward standardization. IEEE Trans Ind Electron 58(1):158–172

    Article  Google Scholar 

  9. Han Y, Li H, Shen P et al (2016) Review of active and reactive power sharing strategies in hierarchical controlled microgrids. IEEE Trans Power Electron 32(3):2427–2451

    Article  Google Scholar 

  10. Che L, Khodayar ME, Shahidehpour M (2014) Adaptive protection system for microgrids: protection practices of a functional microgrid system. IEEE Electrific Mag 2(1):66–80

    Article  Google Scholar 

  11. Shahidehpour M, Khodayar M (2013) Cutting campus energy costs with hierarchical control: the economical and reliable operation of a microgrid. IEEE Electrific Mag 1(1):40–56

    Article  Google Scholar 

  12. Lai J, Lu X, Yu X, Monti A (2020) Stochastic distributed secondary control for AC microgrids via event-triggered communication. IEEE Trans Smart Grid 11(4):2746–2759

    Article  Google Scholar 

  13. Zhang Z, Chow MY (2012) Convergence analysis of the incremental cost consensus algorithm under different communication network topologies in a smart grid. IEEE Trans Power Syst 27(4):1761–1768

    Article  Google Scholar 

  14. Quesada J, Sebastin R, Castro M et al (2014) Control of inverters in a low voltage microgrid with distributed battery energy storage. Part I: primary control. Electr Power Syst Res 114:126–135

    Article  Google Scholar 

  15. Simpson-Porco JW, Shafiee Q, Dörfler F et al (2015) Secondary frequency and voltage control of islanded microgrids via distributed averaging. IEEE Trans Ind Electron 62(11):7025–7038

    Article  Google Scholar 

  16. Lu X, Lai J, Yu X (2020) A novel secondary power management strategy for multiple AC microgrids with cluster-oriented two-layer cooperative framework. IEEE Trans Ind Inform. https://doi.org/10.1109/TII.2020.2985905 (to be published)

    Article  Google Scholar 

  17. Guo F, Wen C, Mao J et al (2014) Distributed secondary voltage and frequency restoration control of droop-controlled inverter-based microgrids. IEEE Trans Ind Electron 62(7):4355–4364

    Article  Google Scholar 

  18. Lai J, Lu X (2020) Nonlinear mean-square power sharing control for AC microgrids under distributed event detection. IEEE Trans Ind Inform. https://doi.org/10.1109/TII.2020.2969458 (to be published)

    Article  Google Scholar 

  19. Cheng M, Liu N (2017) Distributed energy management method for PV-assistant charging stations network: a non-cooperative game approach. In: 2017 12th IEEE conference on industrial electronics and applications (ICIEA). pp 439–443

  20. Fu Y, Zhang Z, Li Z et al (2019) Energy management for hybrid AC/DC distribution system with microgrid clusters using non-cooperative game theory and robust optimization. IEEE Trans Smart Grid 11(2):1510–1525

    Article  Google Scholar 

  21. Nekouei E, Alpcan T, Chattopadhyay D (2014) Game-theoretic frameworks for demand response in electricity markets. IEEE Trans Smart Grid 6(2):748–758

    Article  Google Scholar 

  22. Sola M, Vitetta GM (2014) Demand-side management in a smart micro-grid: a distributed approach based on bayesian game theory. In: 2014 IEEE international conference on smart grid communications. pp 656–661

  23. Brill E, Gonen A, Fligel E et al (2009) Empirical results about the nash-cournot equilibrium. In: 2009 IEEE international conference on industrial engineering and engineering management. pp 130–134

  24. Dörfler F, Bullo F (2012) Exploring synchronization in complex oscillator networks. In: 2012 IEEE 51st IEEE conference on decision and control. pp 7157–7170

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant Nos. 61873195, 61773158, and 51707071; by the Natural Science Foundation of Hunan Province under Grant No. 2018JJ2051; by the Fundamental Research Funds for the Central Universities under Grant 2042019kf0186.

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  1. The School of Electrical Engineering and Automation, Wuhan University, Wuhan, 430072, China

    Hong Zhou & Chang Yu

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  1. Hong Zhou
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  2. Chang Yu
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Correspondence to Chang Yu.

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Zhou, H., Yu, C. Distributed cooperative control algorithm for optimal power sharing for AC microgrids using Cournot game theory. Neural Comput & Applic 33, 973–983 (2021). https://doi.org/10.1007/s00521-020-05315-6

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  • DOI: https://doi.org/10.1007/s00521-020-05315-6

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