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access icon free Fully distributed economic dispatch of distributed generators in active distribution networks considering losses

The increased complexity of the modern distribution system caused by the installation of a large number of distributed energy resources, dictates the necessity for novel, decentralised schemes for the grid operation. In this study, a fully distributed method for the economic dispatch (ED) problem is proposed that takes into account distribution losses. The solution is reached using only local computations and exchange of messages between adjacent nodes without the need of a central coordinating entity. The algorithm presents plug-and-play capabilities and is self-triggered. More specifically, the ED is formulated as a resource allocation problem and a fully distributed algorithm is employed to acquire the solution that is based on the replicator equation model. It takes into account the technical constraints of the generators and it is extended in order to integrate the distributed calculation of active power losses using distributed estimation of the loss penalty factors. Guarantees for the convergence and optimality of the proposed algorithm are provided along with numerical results that demonstrate the effectiveness and efficiency of the algorithm.

References

    1. 1)
    2. 2)
    3. 3)
      • 31. Anderson, B., Mou, S., Morse, A.S., et al: ‘Decentralized gradient algorithm for solution of a linear equation’, arXiv preprint arXiv:1509.04538, 2015.
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
      • 8. Xing, H., Mou, Y., Fu, M., et al: ‘Distributed algorithm for economic power dispatch including transmission losses’. European Control Conf. (ECC), 2015, Linz, 2015, pp. 10761081.
    9. 9)
    10. 10)
      • 20. Pantoja, A., Quijano, N.: ‘Distributed optimization using population dynamics with a local replicator equation’. Decision and Control (CDC), 2012 IEEE 51st Annual Conference on, 10–13 December 2012, pp. 37903795.
    11. 11)
      • 33. Sánchez-Ayala, G., Agüerc, J.R., Elizondo, D., et al: ‘Current trends on applications of PMUs in distribution systems’. Innovative Smart Grid Technologies (ISGT), 2013 IEEE PES, Washington, DC, 2013, pp. 16.
    12. 12)
    13. 13)
      • 6. Chen, K., Xie, J., Wang, L., et al: ‘A fully distributed economic dispatch strategy for power systems considering flexible loads’. 34th Chinese Control Conf. (CCC), 2015, Hangzhou, July 2015, pp. 66026607.
    14. 14)
    15. 15)
    16. 16)
      • 36. Koukoula, D.I., Hatziargyriou, N.D.: ‘Gossip algorithms for decentralized congestion management of distribution grids’, IEEE Trans. Sustain. Energy, PP, (99), pp. 110.
    17. 17)
      • 18. De Brabandere, K., Vanthournout, K., Driesen, J., et al: ‘Control of microgrids’. Power Engineering Society General Meeting, 2007, 24–28 June 2007, pp. 17.
    18. 18)
    19. 19)
      • 12. Domínguez-García, A.D., Hadjicostis, C.N.: ‘Distributed algorithms for control of demand response and distributed energy resources’. 50th IEEE Conf. on Decision and Control and European Control Conf. (CDC-ECC), 2011, Orlando, FL, 2011, pp. 2732.
    20. 20)
      • 30. Soder, L.: ‘Estimation of reduced electrical distribution losses depending on dispersed small scale energy production’. Proc. 12th Power Systems Computation Conf., 1996, vol. 2.
    21. 21)
    22. 22)
      • 24. Kouveliotis-Lysikatos, I., Hatziargyriou, N.: ‘Decentralized economic dispatch of distributed generators based on population dynamics’. 18th Int. Conf. on Intelligent System Application to Power Systems (ISAP), 2015, Porto, 2015, pp. 16.
    23. 23)
    24. 24)
      • 5. Kar, S., Hug, G.: ‘Distributed robust economic dispatch in power systems: A consensus + innovations approach’. Power and Energy Society General Meeting, 2012, San Diego, CA, 2012, pp. 18.
    25. 25)
      • 10. Xing, H., Lin, Z., Fu, M.: ‘An ADMM + consensus based distributed algorithm for dynamic economic power dispatch in smart grid’. 34th Chinese Control Conf. (CCC), 2015, Hangzhou, 2015, pp. 90489053.
    26. 26)
      • 14. Mudumbai, R., Dasgupta, S., Cho, B.: ‘Distributed control for optimal economic dispatch of power generators’. 29th Chinese Control Conf. (CCC), 2010, 29–31 July 2010, pp. 49434947.
    27. 27)
      • 26. Hofbauer, J., Sigmund, K.: ‘Evolutionary games and population dynamics’ (Cambridge University Press, 1998).
    28. 28)
    29. 29)
    30. 30)
    31. 31)
      • 23. Pantoja, A., Quijano, N., Passino, K.M.: ‘Dispatch of distributed generators under local-information constraints’. American Control Conf. (ACC), 2014, Portland, OR, 2014, pp. 26822687.
    32. 32)
    33. 33)
      • 27. Rees, T.: ‘An Introduction to Evolutionary Game Theory’, 1996.
    34. 34)
      • 4. Zhang, Z., Chow, M.-Y.: ‘Incremental cost consensus algorithm in a smart grid environment’. Power and Energy Society General Meeting, 2011, 24–29 July 2011, pp. 16.
    35. 35)
      • 25. Zhu, J.: ‘Optimization of power system operation’ (Wiley-IEEE Press, 2009), vol. 49.
    36. 36)
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