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Expansion planning for active distribution networks considering deployment of smart management technologies

Expansion planning for active distribution networks considering deployment of smart management technologies

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In this study, a multi-stage long-term expansion planning model for an active distribution network (ADN) is presented, with the aim of minimising the investment and operation cost in a coordinated manner over an established horizon. The planning model optimises the following alternatives: upgrading the capacities of substations, reinforcing and/or constructing cable circuits, placing voltage regulators (VRs) and/or static VAR generators, and determining the connection points for distributed generators (DGs). The investment decisions are optimised over the entire planning horizon which can be further divided into multiple periods, and the operation strategies, e.g. active management of DG as well as ADN topology reconfiguration, are determined according to the profiles of representative scenarios. To relieve the computational burden, the original model is properly simplified as a mixed-integer quadratic constrained programming problem through linearisation and approximation techniques, and the solution optimality is guaranteed after invoking the off-the-shell solver. A 24-node test system is employed to validate the effectiveness of the proposed model.

References

    1. 1)
      • 1. Kothari, D.P., Nagrath, I.J.: ‘Modern power system analysis’ (Tata McGraw-Hill, New York, 2011).
    2. 2)
      • 2. Tabares, A., Franco, J., Lavorato, M., et al: ‘Multistage long-term expansion planning of electrical distribution systems considering multiple alternatives’, IEEE Trans. Power Syst., 2016, 31, (3), pp. 19001914.
    3. 3)
      • 3. Mohtashami, S., Pudjianto, D., Strbac, G.: ‘Strategic distribution network planning with smart grid technologies’, IEEE Trans. Smart Grid, 2017, 8, (6), pp. 26562664.
    4. 4)
      • 4. Shen, X., Shahidehpour, M., Han, Y., et al: ‘Multi-stage planning of active distribution networks considering the co-optimization of operation strategies’, IEEE Trans. Smart Grid, 2018, 9, (2), pp. 14251433.
    5. 5)
      • 5. Asensio, M., Munoz-Delgado, G., Contreras, J.: ‘A bi-level approach to distribution network and renewable energy expansion planning considering demand’, IEEE Trans. Power Syst., 2017, 32, (6), pp. 42984309.
    6. 6)
      • 6. Mansor, N., Levi, V.: ‘Integrated planning of distribution networks considering utility planning concepts’, IEEE Trans. Power Syst., 2017, 32, (6), pp. 46564672.
    7. 7)
      • 7. Parada, V., Ferland, J., Arias, M., et al: ‘Optimization of electrical distribution feeders using simulated annealing’, IEEE Trans. Power Deliv., 2014, 19, (2), pp. 11351141.
    8. 8)
      • 8. Zhao, C., Li, J., Zhang, Y., et al: ‘Optimal location planning of renewable distributed generation units in distribution networks: an analytical approach’, IEEE Trans. Power Syst., 2018, 33, (3), pp. 27422753.
    9. 9)
      • 9. Koutsoukis, N., Georgilakis, P., Hatziargyriou, N.: ‘Multistage coordinated planning of active distribution networks’, IEEE Trans. Power Syst., 2018, 33, (1), pp. 3244.
    10. 10)
      • 10. Zhang, X., Che, L., Shahidehpour, M., et al: ‘Reliability-based optimal planning of electricity and natural gas interconnection for multiple energy hubs’, IEEE Trans. Smart Grid, 2017, 8, (4), pp. 16581667.
    11. 11)
      • 11. Munoz-Delgado, G., Contreras, J., Arroyo, J.: ‘Multistage generation and network expansion planning in distribution systems considering uncertainty and reliability’, IEEE Trans. Power Syst., 2016, 31, (5), pp. 37153728.
    12. 12)
      • 12. Delgado, G., Contreras, J., Arriyo, J.: ‘Distribution network expansion planning with an explicit formulation for reliability assessment’, IEEE Trans. Power Syst., 2018, 33, (3), pp. 25832596.
    13. 13)
      • 13. Alkaabi, S., Khadkikar, V., Zeineldin, H.: ‘Incorporating PV inverter control schemes for planning active distribution networks’, IEEE Trans. Sustain. Energy, 2015, 6, (4), pp. 12241233.
    14. 14)
      • 14. Xing, H., Cheng, H., Zeng, P.: ‘Active distribution network expansion planning integrating dispersed energy storage systems’, IET Gener. Transm. Distrib., 2016, 10, (5), pp. 638644.
    15. 15)
      • 15. Dzamarija, M., Keane, A.: ‘Firm and non-firm wind generation planning considering distribution network sterilization’, IEEE Trans. Smart Grid, 2013, 4, (4), pp. 21622173.
    16. 16)
      • 16. Khodaei, A., Shahidehpour, M., Wu, L., et al: ‘Coordination of short-term operation constraints in multi-area expansion planning’, IEEE Trans. Power Syst., 2012, 27, (4), pp. 22422250.
    17. 17)
      • 17. Cortes, C., Contreras, S., Shahidehpour, M.: ‘Microgrid topology planning for enhancing the reliability of active distribution networks’, IEEE Trans. Smart Grid, 2017, doi: 10.1109/TSG.2017.2709699.
    18. 18)
      • 18. Dias, F.M., Canizes, B., Knodr, H.: ‘Distribution networks planning using decomposition optimization technique’, IET Gener. Transm. Distrib., 2015, 9, (12), pp. 14091420.
    19. 19)
      • 19. Che, L., Zhang, X., Shahidehpour, M., et al: ‘Optimal interconnection planning of community microgrids with renewable energy sources’, IEEE Trans. Smart Grid, 2017, 8, (3), pp. 10541063.
    20. 20)
      • 20. Shu, J., Wu, L., Li, Z., et al: ‘A new method for spatial power network planning in complicated environments’, IEEE Trans. Power Syst., 2012, 27, (1), pp. 381389.
    21. 21)
      • 21. Taylor, J.A., Hover, F.S.: ‘Convex models of distribution system reconfiguration’, IEEE Trans. Power Syst., 2012, 27, (3), pp. 14071413.
    22. 22)
      • 22. El-Zonkoly, A.M.: ‘Multistage expansion planning for distribution networks including unit commitment’, IET Gener. Transm. Distrib., 2013, 7, (7), pp. 766778.
    23. 23)
      • 23. Li, N., Chen, L., Low, S.: ‘Exact convex relaxation of OPF for radial networks using branch flow model’. 2012 IEEE Third Int. Conf. SmartGridComm, Tainan, Taiwan, 2012, pp. 17.
    24. 24)
      • 24. Rahimiyan, M., Baringo, L., Conejo, A.J.: ‘Energy management of a cluster of interconnected price-responsive demands’, IEEE Trans. Power Syst., 2014, 29, (2), pp. 645655.
    25. 25)
      • 25. Nguyen, D.T., Le, L.B.: ‘Risk-constrained profit maximization for microgrid aggregators with demand response’, IEEE Trans. Smart Grid, 2015, 6, (1), pp. 135146.
    26. 26)
      • 26. Lavorato, M., Franco, J.F., Rider, M.J., et al: ‘Imposing radiality constraints in distribution system optimization problems’, IEEE Trans. Power Syst., 2012, 27, (1), pp. 172180.
    27. 27)
      • 27. Franco, F., Rider, M.J., Lavorato, M., et al: ‘A mixed-integer LP model for the reconfiguration of radial electric distribution systems considering distributed generation’, Electr. Power Syst. Res., 2013, 97, (97), pp. 5160.
    28. 28)
      • 28. Achterberg, T.: ‘SCIP: solving constraints integer programs’, Program. Comput., 2009, 1, (1), pp. 141.
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