access icon free Distribution networks planning using decomposition optimisation technique

This study proposes an efficient planning method for distribution networks in order to minimise power loss and maximise reliability taking into account the distributed generation, transformers load tap changer and capacitors location and size. This multi-criteria model is subjected to several technical constraints and full AC-optimal power flow (OPF). The planning process is running by means of a multi-criteria analysis in which three objectives are considered: the minimisation of the system's power loss; the minimisation of capacitor placement and size cost; and the minimisation of energy not supplied cost, maximising reliability. For solving this problem, decomposition techniques were chosen. This way, the problem was divided into two parts – one called the master sub-problem and another called slave sub-problem. The master sub-problem (decision sub-problem) determines the radial topology of the distribution network and was formulated as a mixed-integer quadratic constraint problem. The slave sub-problem is used to define the feasibility of the decision sub-problem solution by solving an OPF, giving information required to formulate the linear cuts and formulated as a non-linear programming problem. These cuts link the master and the slave sub-problems. The methodology is programmed in the software General Algebraic Modelling System and it is applied to a 70-bus distribution network.

Inspec keywords: nonlinear programming; integer programming; load flow; power distribution planning; distributed power generation

Other keywords: distribution networks planning; nonlinear programming problem; power loss; distributed generation; capacitor location; mixed-integer quadratic constraint problem; AC-optimal power flow; radial topology; slave sub-problem; transformers load tap changer; decomposition optimisation technique; capacitor size; master sub-problem

Subjects: Distributed power generation; Distribution networks; Power system planning and layout; Optimisation techniques

References

    1. 1)
    2. 2)
      • 13. Khodr, H.M., Matos, M.A., Pereira, J.: ‘Distribution optimal power flow’. IEEE Lausanne Power Tech, 2007, 2007, pp. 14411446.
    3. 3)
    4. 4)
    5. 5)
      • 21. Mohammadian, L., Hagh, M.T., Babaei, E., Khani, S.: ‘Using PSO for optimal planning, and reducing loss of distribution networks’. Proc. of 17th Conf. on Electrical Power Distribution Networks, 2012, pp. 16.
    6. 6)
    7. 7)
      • 30. ARKI Consulting and Development A/S: ‘GAMS/CONOPT’ (Bagsvaerd, Denmark, 2001).
    8. 8)
    9. 9)
    10. 10)
    11. 11)
      • 17. Syahputra, R., Robandi, I., Ashari, M.: ‘Reconfiguration of distribution network with DG using fuzzy multi-objective method’. Int. Conf. on InnovationManagement and Technology Research, 2012, pp. 316321.
    12. 12)
      • 3. Rosendo, J.A., Gomez-Exposito, A., Tévar, G., Rodríguez, M.: ‘Evaluation and improvement of supply reliability indices for distribution networks’. Transmission and Distribution Exposition Conf. 2008 IEEE PES Powering Toward the Future, PIMS 2008, 2008.
    13. 13)
    14. 14)
    15. 15)
    16. 16)
      • 31. https://www.cia.gov/library/publications/the-world-factbook/rankorder/2207rank.html (accessed September 2014).
    17. 17)
      • 23. GAMS: http://www.gams.com/solvers/solvers.htm (accessed September 2014).
    18. 18)
      • 22. GAMS: http://www.gams.com/ (accessed September 2014).
    19. 19)
      • 32. http://research.cs.wisc.edu/math-prog/matlab.html (accessed September 2014).
    20. 20)
      • 19. Tanuj, M.S.: ‘Power factor improvement in radial distribution systems using bionic random search algorithm’, Int. J. Innov. Res. Stud., 2013, 2, pp. 377–387.
    21. 21)
      • 16. Sun, H.S.H., Ding, Y.D.Y.: ‘Network reconfiguration of distribution system using fuzzy preferences multi-objective approach’. Second Int. Asia Conf. on Informatics Control, Automation, and Robotics (CAR), 2010, 2010, p. 3.
    22. 22)
      • 4. Ganesh, V., Sivanagaraju, S.R.T.: ‘Feeder reconfiguration for loss reduction in unbalanced distribution system using genetic algorithm’, Int. J. Electr. Electron. Eng., 2009, 3, pp. 754762.
    23. 23)
    24. 24)
      • 10. Ajaja, A., Galiana, F.D.: ‘Distribution network reconfiguration for loss reduction using MILP’. Innovations in Smart Grid Technologies, 2012, pp. 1620.
    25. 25)
      • 29. GAMS Development Corporation: ‘GAMS-the solver manuals, GAMS user notes’ GAMS (Washington DC, 2001).
    26. 26)
    27. 27)
      • 5. Merlin, A., Back, H.: ‘Search for a minimal-loss operating spanning tree configuration in an urban power distribution system’. Fifth Power Systems Computation Conf., 1975, pp. 118.
    28. 28)
      • 26. Li, Y., McCalley, J.: ‘A general benders decomposition structure for power system decision problems’, 2008, pp. 72–77.
    29. 29)
    30. 30)
    31. 31)
      • 28. Conejo, A.J.: ‘Decomposition techniques in mathematical programming’ (Springer, Berlin, London, 2006).
    32. 32)
      • 27. Mohammad, S., Yong, F.: ‘Benders decomposition: applying Benders decomposition to power systems’. IEEE Power Energy Mag., 2005, 3, (2), pp. 20–21.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2014.0860
Loading

Related content

content/journals/10.1049/iet-gtd.2014.0860
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading