A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 7 Issue 3
Apr.  2020

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 11.8, Top 4% (SCI Q1)
    CiteScore: 17.6, Top 3% (Q1)
    Google Scholar h5-index: 77, TOP 5
Turn off MathJax
Article Contents
Qing Yang, Gang Chen and Ting Wang, "ADMM-based Distributed Algorithm for Economic Dispatch in Power Systems With Both Packet Drops and Communication Delays," IEEE/CAA J. Autom. Sinica, vol. 7, no. 3, pp. 842-852, May 2020. doi: 10.1109/JAS.2020.1003156
Citation: Qing Yang, Gang Chen and Ting Wang, "ADMM-based Distributed Algorithm for Economic Dispatch in Power Systems With Both Packet Drops and Communication Delays," IEEE/CAA J. Autom. Sinica, vol. 7, no. 3, pp. 842-852, May 2020. doi: 10.1109/JAS.2020.1003156

ADMM-based Distributed Algorithm for Economic Dispatch in Power Systems With Both Packet Drops and Communication Delays

doi: 10.1109/JAS.2020.1003156
Funds:  This work was supported by the National Natural Science Foundation of China (61673077)
More Information
  • By virtue of alternating direction method of multipliers (ADMM), Newton-Raphson method, ratio consensus approach and running sum method, two distributed iterative strategies are presented in this paper to address the economic dispatch problem (EDP) in power systems. Different from most of the existing distributed ED approaches which neglect the effects of packet drops or/and time delays, this paper takes into account both packet drops and time delays which frequently occur in communication networks. Moreover, directed and possibly unbalanced graphs are considered in our algorithms, over which many distributed approaches fail to converge. Furthermore, the proposed schemes can address the EDP with local constraints of generators and nonquadratic convex cost functions, not just quadratic ones required in some existing ED approaches. Both theoretical analyses and simulation studies are provided to demonstrate the effectiveness of the proposed schemes.

     

  • loading
  • [1]
    C. E. Lin, S. T. Chen, and C. L. Huang, “A direct Newton-Raphson economic dispatch,” IEEE Trans. Power Syst., vol. 7, no. 3, pp. 1149–1154, Aug. 1992. doi: 10.1109/59.207328
    [2]
    J. Zhao, S. X. Liu, M. C. Zhou, X. W. Guo, and L. Qi, “Modified cuckoo search algorithm to solve economic power dispatch optimization problems,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 4, pp. 794–806, Jul. 2018. doi: 10.1109/JAS.2018.7511138
    [3]
    C.-L. Chiang, “Improved genetic algorithm for power economic dispatch of units with valve-point effects and multiple fuels,” IEEE Trans. Power Syst., vol. 20, no. 4, pp. 1690–1699, Nov. 2005. doi: 10.1109/TPWRS.2005.857924
    [4]
    Z.-L. Gaing, “Particle swarm optimization to solving the economic dispatch considering the generator constraints,” IEEE Trans. Power Syst., vol. 18, no. 3, pp. 1187–1195, Aug. 2003. doi: 10.1109/TPWRS.2003.814889
    [5]
    Y. F. Tang, C. Luo, J. Yang and H. B. He, “A chance constrained optimal reserve scheduling approach for economic dispatch considering wind penetration,” IEEE/CAA J. Autom. Sinica, vol. 4, no. 2, pp. 186–194, Apr. 2017. doi: 10.1109/JAS.2017.7510499
    [6]
    G. Binetti, M. Abouheaf, F. Lewis, D. Naso, and A. Davoudi, “Distributed solution for the economic dispatch problem,” in Proc. 21st MED, 2013, pp. 243–250.
    [7]
    G. Chen and E. N. Feng, “Distributed secondary control and optimal power sharing in microgrids,” IEEE/CAA J. Autom. Sinica, vol. 2, no. 3, pp. 304–312, 2015. doi: 10.1109/JAS.2015.7152665
    [8]
    Z. Zhang and M.-Y. Chow, “Convergence analysis of the incremental cost consensus algorithm under different communication network topologies in a smart grid,” IEEE Trans. Power Syst., vol. 27, no. 4, pp. 1761–1768, Nov. 2012. doi: 10.1109/TPWRS.2012.2188912
    [9]
    G. Chen, J. Ren, and E. N. Feng, “Distributed finite-time economic dispatch of a network of energy resources,” IEEE Trans. Smart Grid, vol. 8, no. 2, pp. 822–832, Mar. 2017.
    [10]
    Q. Li, D. W. Gao, H. Zhang, Z. Wu, and F.-Y. Wang, “Consensus-based distributed economic dispatch control method in power systems,” IEEE Trans. Smart Grid, vol. 10, no. 1, pp. 941–954, Jan. 2019. doi: 10.1109/TSG.2017.2756041
    [11]
    G. Chen, and Z. Y. Zhao, “Delay effects on consensus-based distributed economic dispatch algorithm in microgrid,” IEEE Trans. Power Syst., vol. 33, no. 1, pp. 602–612, Jan. 2018. doi: 10.1109/TPWRS.2017.2702179
    [12]
    S. P. Yang, S. C. Tan, and J. X. Xu, “Consensus based approach for economic dispatch problem in a smart grid,” IEEE Trans. Power Syst., vol. 28, no. 4, pp. 4416–4426, Nov. 2013. doi: 10.1109/TPWRS.2013.2271640
    [13]
    T. Yang, D. Wu, Y. N. Sun, and J. M. Lian, “Minimum-time consensus-based approach for power system applications,,” IEEE Trans. Ind. Electron., vol. 63, no. 2, pp. 1318–1328, Feb. 2016. doi: 10.1109/TIE.2015.2504050
    [14]
    F. H. Guo, C. Y. Wen, J. F. Mao, and Y.-D. Song, “Distributed economic dispatch for smart grids with random wind power,” IEEE Trans. Smart Grid, vol. 7, no. 3, pp. 1572–1583, May 1572.
    [15]
    H. Xing, Y. T. Mou, M. Y. Fu, and Z. Y. Lin, “Distributed bisection method for economic power dispatch in smart grid,” IEEE Trans. Power Syst., vol. 30, no. 6, pp. 3024–3035, Nov. 2015. doi: 10.1109/TPWRS.2014.2376935
    [16]
    L. Xiao and S. Boyd, “Optimal scaling of a gradient method for distributed resource allocation,” J. Optim. Theory Appl., vol. 129, no. 3, pp. 469–488, Jun. 2006. doi: 10.1007/s10957-006-9080-1
    [17]
    V. Loia, and A. Vaccaro, “Decentralized economic dispatch in smart grids by selforganizing dynamic agents,” IEEE Trans. Syst.,Man,Cybern. A,Syst., vol. 44, no. 4, pp. 397–408, Apr. 2014. doi: 10.1109/TSMC.2013.2258909
    [18]
    A. Cherukuri and J. Cortés, “Distributed generator coordination for initialization and anytime optimization in economic dispatch,” IEEE Trans. Control Netw. Syst., vol. 2, no. 3, pp. 226–237, Sep. 2015. doi: 10.1109/TCNS.2015.2399191
    [19]
    J. F. Wu, T. Yang, D. Wu, K. Kalsi, and K. H. Johansson, “Distributed optimal dispatch of distributed energy resources over lossy communication networks,” IEEE Trans. Smart Grid, vol. 8, no. 6, pp. 3125–3137, Nov. 2017. doi: 10.1109/TSG.2017.2720761
    [20]
    T. Yang, J. Lu, D. Wu, J. F. Wu, G. D. Shi, Z. Y. Meng, and K. H. Johansson, “A distributed algorithm for economic dispatch over time-varying directed networks with delays,” IEEE Trans. Ind. Electron., vol. 64, no. 6, pp. 5095–5106, Jun. 2017. doi: 10.1109/TIE.2016.2617832
    [21]
    G. Chen and Q. Yang, “An ADMM-based distributed algorithm for economic dispatch in islanded microgrids,” IEEE Trans. Ind. Inform., vol. 14, no. 9, pp. 3892–3903, Sep. 2018. doi: 10.1109/TII.2017.2785366
    [22]
    B. A. Robbins and A. D. Dominguez-Garcia, “Optimal reactive power dispatch for voltage regulation in unbalanced distribution systems,” IEEE Trans. Power Syst., vol. 31, no. 4, pp. 2903–2913, Jul. 2016. doi: 10.1109/TPWRS.2015.2451519
    [23]
    S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, “Distributed optimization and statistical learning via the alternating direction method,” Found. Trends Mach. Learn, vol. 3, no. 1, pp. 1–122, 2011.
    [24]
    J. Mota, J. Xavier, P. Aguiar, and M. Pschel, “A proof of convergence for the alternating direction method of multipliers applied to polyhedral-constrained functions,” Mathematics, 2011.
    [25]
    C. N. Hadjicostis and T. Charalambous, “Average consensus in the presence of delays in directed graph topologies,” IEEE Trans. Autom. Control, vol. 59, no. 3, pp. 763–768, Mar. 2014. doi: 10.1109/TAC.2013.2275669
    [26]
    C. N. Hadjicostis, N. H. Vaidya, and A. D. Dominguez-Garcia, “Robust distributed average consensus via exchange of running sums,” IEEE Trans. Autom. Control, vol. 61, no. 6, pp. 1492–1507, Jun. 2016. doi: 10.1109/TAC.2015.2471695
    [27]
    S. Boyd, and L. Vandenberghe, Convex Optimization. Cambridge, UK: Cambridge University Press, 2004.
    [28]
    D. Bertsekas, A. Nedić, and A. E. Ozdaglar, Convex Analysis and Optimization. Belmont, MA, USA: Athena Scientific, 2003.
    [29]
    L. H. Wu, Y. N. Wang, X. F. Yuan, and S. W. Zhou, “Environmental/economic power dispatch problem using multi-objective differential evolution algorithm,” Elect. Power Syst. Res., vol. 80, no. 9, pp. 1171–1181, May 2010. doi: 10.1016/j.jpgr.2010.03.010

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(7)  / Tables(2)

    Article Metrics

    Article views (1283) PDF downloads(65) Cited by()

    Highlights

    • This paper for the first time presents an ADMM-based distributed algorithm to solve the EDP with both packet drops and communication delays.
    • Different from most of the existing studies on the EDP which require the communication graphs to be undirected, the proposed schemes can solve the EDP on general digraphs.
    • The general convex cost functions are considered in this paper and both the coupled equality constraint and local constraints of generators are taken into account.

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return