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access icon free A scenario-based robust investment planning model for multi-type distributed generation under uncertainties

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References

    1. 1)
      • 1. El-khattam, W., Hegazy, Y.G., Salama, M.M.A.: ‘An integrated distributed generation optimization model for distribution system planning’, IEEE Trans. Power Syst., 2005, 20, (2), pp. 11581165.
    2. 2)
      • 2. Ehsan, A., Yang, Q.: ‘Optimal integration and planning of renewable distributed generation in the power distribution networks: a review of analytical techniques’, Appl. Energy, 2018, 210, pp. 4459.
    3. 3)
      • 3. Yang, Q., Barria, J.A., Green, T.C.: ‘Communication infrastructures for distributed control of power distribution networks’, IEEE Trans. Ind. Inf., 2011, 7, (2), pp. 316327.
    4. 4)
      • 4. Santos, S.F., Fitiwi, D.Z., Bizuayehu, A.W., et al: ‘Novel multi-stage stochastic DG investment planning with recourse’, IEEE Trans. Sustain. Energy, 2016, 3029, pp. 164178.
    5. 5)
      • 5. Khodaei, A., Bahramirad, S., Shahidehpour, M.: ‘Microgrid planning under uncertainty’, IEEE Trans. Power Syst., 2014, 30, (5), pp. 24172425.
    6. 6)
      • 6. Shivaie, M., Ameli, M.T., Sepasian, M.S., et al: ‘A multistage framework for reliability-based distribution expansion planning considering distributed generations by a self-adaptive global-based harmony search algorithm’, Reliab. Eng. Syst. Saf., 2015, 139, pp. 6881.
    7. 7)
      • 7. Li, J., Ye, L., Zeng, Y., et al: ‘A scenario-based robust transmission network expansion planning method for consideration of wind power uncertainties’, CSEE J. Power Energy Syst., 2016, 2, (1), pp. 1118.
    8. 8)
      • 8. Kirthiga, M.V., Daniel, S.A., Gurunathan, S.: ‘A methodology for transforming an existing distribution network into a sustainable autonomous micro-grid’, IEEE Trans. Sustain. Energy, 2013, 4, (1), pp. 3141.
    9. 9)
      • 9. Munoz-Delgado, G., Contreras, J., Arroyo, J.M.: ‘Joint expansion planning of distributed generation and distribution networks’, IEEE Trans. Power Syst., 2015, 30, (5), pp. 25792590.
    10. 10)
      • 10. Sadeghi, M., Kalantar, M.: ‘Multi types DG expansion dynamic planning in distribution system under stochastic conditions using covariance matrix adaptation evolutionary strategy and Monte-Carlo simulation’, Energy Convers. Manag., 2014, 87, pp. 455471.
    11. 11)
      • 11. Montoya-Bueno, S., Munoz, J.I., Contreras, J.: ‘A stochastic investment model for renewable generation in distribution systems’, IEEE Trans. Sustain. Energy, 2015, 6, (4), pp. 14661474.
    12. 12)
      • 12. Ganguly, S., Samajpati, D.: ‘Distributed generation allocation on radial distribution networks under uncertainties of load and generation using genetic algorithm’, IEEE Trans. Sustain. Energy, 2015, 6, (3), pp. 688697.
    13. 13)
      • 13. Ahmadigorji, M., Amjady, N.: ‘A multiyear DG-incorporated framework for expansion planning of distribution networks using binary chaotic shark smell optimization algorithm’, Energy, 2016, 102, pp. 199215.
    14. 14)
      • 14. Lofberg, J.: ‘YALMIP: a toolbox for modeling and optimization in MATLAB’. 2004 IEEE Int. Conf. Computer Aided Control Systems Design, New Orleans, LA, USA, September 2004, pp. 284289.
    15. 15)
      • 15. IBM Corp., IBM: ‘V12. 1: user's manual for CPLEX’, Int. Bus. Mach. Corp., 2009, 12, (1), p. 481.
    16. 16)
      • 16. Kaut, M., Wallace, S.W.: ‘A heuristic for moment-matching’, Comput. Optim. Appl., 2003, 24, pp. 169185.
    17. 17)
      • 17. Wu, T., Yang, Q., Bao, Z., et al: ‘Coordinated energy dispatching in microgrid with wind power generation and plug-in electric vehicles’, IEEE Trans. Smart Grid, 2013, 4, (3), pp. 14531463.
    18. 18)
      • 18. Ehsan, A., Yang, Q.: ‘Robust distribution system planning considering the uncertainties of renewable distributed generation and electricity demand’. 1st IEEE Conf. on Energy Internet and Energy System Integration, Beijing, November 2017.
    19. 19)
      • 19. Wei, H., Sasaki, H., Kubokawa, J., et al: ‘Large scale hydrothermal optimal power flow problems based on interior point nonlinear programming’, IEEE Trans. Power Syst., 2000, 15, (1), pp. 396403.
    20. 20)
      • 20. Santos, S.F., Fitiwi, D.Z., Bizuayehu, A.W., et al: ‘Optimal integration of RES-based DGs with reactive power support capabilities in distribution network systems’. 13th IEEE Int. Conf. on the European Energy Market, Porto, July 2016, pp. 15.
    21. 21)
      • 21. Hung, D.Q., Mithulananthan, N., Lee, K.Y.: ‘Determining PV penetration for distribution systems with time-varying load models’, IEEE Trans. Power Syst., 2014, 29, (6), pp. 30483057.
    22. 22)
      • 22. Blank, L., Tarquin, A.: ‘Engineering Economy’ (McGraw-Hill, New York, NY, USA, 2012).
    23. 23)
      • 23. Mohammadi, M., Hosseinian, S.H., Gharehpetian, G.B.: ‘GA-based optimal sizing of microgrid and DG units under pool and hybrid electricity markets’, Int. J. Electr. Power Energy Syst., 2012, 35, (1), pp. 8392.
    24. 24)
      • 24. Taylor, J.A., Hover, F.S.: ‘Convex models of distribution system reconfiguration’, IEEE Trans. Power Syst., 2012, 27, (3), pp. 14071413.
    25. 25)
      • 25. Romero, R., Franco, J.F., Leao, F.B., et al: ‘A new mathematical model for the restoration problem in balanced radial distribution systems’, IEEE Trans. Power Syst., 2016, 31, (2), pp. 12591268.
    26. 26)
      • 26. Bazilian, M., Onyeji, I., Liebreich, M., et al: ‘Re-considering the economics of photovoltaic power’, Renew. Energy, 2013, 53, pp. 329338.
    27. 27)
      • 27. Generation: ‘Electric Reliability Council of Texas, Inc.’. Available at http://www.ercot.com/gridinfo/generation, accessed 20 October 2017.
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