AIMS Energy, 2016, 4(3): 461-480. doi: 10.3934/energy.2016.3.461 Research article Topical Section

Export file:

Format

RIS(for EndNote,Reference Manager,ProCite)
BibTex
Text

Content

Citation Only
Citation and Abstract

Reconfiguration of distribution system using a binary programming model

Department of Electrical Engineering, University of Newcastle, Callaghan, NSW-2308, Australia.
† Research is supported by the Australian research council.

Received: , Accepted: , Published:

Topical Section: Smart Grids and Networks

Abstract Full Text(HTML) Figure/Table Related pages

Distribution system reconfiguration aims to choose a switching combination of branches of the system that optimize certain performance criteria of power supply while maintaining some specified constraints. The ability to automatically reconfigure the network quickly and reliably is a key requirement of self-healing networks which is an important part of the future Smart Grid system. We present a unified mathematical framework, which allows us to consider different objectives of distribution system reconfiguration problems in a flexible manner, and investigate its performance. The resulting optimization problem is in quadratic form which can be solved efficiently by using a quadratic mixed integer programming (QMIP) solver. The proposed method has been applied for reconfiguring different standard test distribution systems.

Figure/Table

Supplementary

Article Metrics

References

1. GUROBI Optimization, 2012. Available from: http://www.gurobi.com/.

2. Abur A (1996) A modified linear programming method for distribution system reconfiguration. Int J Elec Power 18: 469-474.

3. Ajaja A, Galiana F (2012) Distribution network reconfiguration for loss reduction using milp. IEEE PES ISGT , 1-6.

4. Baran M, Wu F (1989) Network reconfiguration in distribution systems for loss reduction and load balancing. IEEE Trans Power Deliver 4: 1401-1407.

5. Brown R (2008) Impact of smart grid on distribution system design. Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE. 1-4.

6. Carreno E, Romero R, Padilha-Feltrin A (2008) An efficient codification to solve distribution network reconfiguration for loss reduction problem. IEEE Trans Power Syst 23: 1542-1551.

7. Chiang HD, Jean-Jumeau R (1990) Optimal network reconfigurations in distribution systems. i. a new formulation and a solution methodology. IEEE Trans Power Deliver 5: 1902-1909.

8. Ciric R, Popovic D (2000) Multi-objective distribution network restoration using heuristic approach and mix integer programming method. Int J Elec Power 22: 497-505.

9. Das D (2006) Reconfiguration of distribution system using fuzzy multi-objective approach. Int J Elec Power 28: 331-338.

10. E Afzalan MS, Taghikhani MA (2012) Optimal placement and sizing of dg in radial distribution networks using sfla. Int J Energy Engin 3: 2163-1891.

11. Enacheanu B, Raison B, Caire R, et al. (2008) Radial network reconfiguration using genetic algorithm based on the matroid theory. IEEE Trans Power Syst 23: 186-195.

12. Franco JF, Rider MJ, Lavorato M, et al. (2013) A mixed-integer {LP} model for the reconfiguration of radial electric distribution systems considering distributed generation. Electr Pow Syst Res 97: 51-60.

13. Gomes F, Carneiro JS, Pereira J, et al. (2005) A new heuristic reconfiguration algorithm for large distribution systems. IEEE Trans Power Syst 20: 1373-1378.

14. Gomes F, Carneiro S, Pereira J, et al. (2006) A new distribution system reconfiguration approach using optimum power flow and sensitivity analysis for loss reduction. IEEE Trans Power Syst 21: 1616-1623.

15. Goswami S, Basu S (1992) A new algorithm for the reconfiguration of distribution feeders for loss minimization. IEEE Trans Power Deliver 7: 1484-1491.

16. Guimaraes MAN, Castro CA (2005) Reconfiguration of distribution systems for loss reduction using tabu search. 15th PSCC, 1-10.

17. Ipakchi A, Albuyeh F (2009) Grid of the future. IEEE Power Energy M 7: 52-62.

18. Khodr H, Martinez-Crespo J, Matos M, et al. (2009) Distribution systems reconfiguration based on opf using benders decomposition. IEEE Trans Power Deliver 24: 2166-2176.

19. Mahboubi-Moghaddam E, Narimani MR, Khooban MH, et al. (2016) Multi-objective distribution feeder reconfiguration to improve transient stability, and minimize power loss and operation cost using an enhanced evolutionary algorithm at the presence of distributed generations. Int J Elec Power 76: 35-43.

20. Mantawy A, Abdel-Magid Y, Selim S (1999) Integrating genetic algorithms, tabu search, and simulated annealing for the unit commitment problem. IEEE Trans Power Syst 14: 829-836.

21. Matos M, Melo P (2001) Loss minimization in distribution networks with multiple load scenarios. In Power Tech Proceedings, 2001 IEEE Porto 3, 5.

22. McDermott T, Drezga I, Broadwater R (1999) A heuristic nonlinear constructive method for distribution system reconfiguration. IEEE Trans Power Syst 14: 478-483.

23. Merlin A, Back H (1975) Search for a Minimal-Loss Operating Spanning Tree Configuration in an Urban Power Distribution System. Proc. 5th Power System Computation Conference (PSCC) (Cambridge, U.K.).

24. Milani AE, Haghifam MR (2013a) An evolutionary approach for optimal time interval determination in distribution network reconfiguration under variable load. Math Comput Model 57: 68-77.

25. Milani AE, Haghifam MR (2013b) A new probabilistic approach for distribution network reconfiguration: Applicability to real networks. Mathematical and Computer Modelling 57: 169-179.

26. Momoh J, Caven A (2003) Distribution system reconfiguration scheme using integer interior point programming technique. Transmission and Distribution Conference and Exposition, 2003 IEEE PES 1: 234-241.

27. Moradzadeh B, Tomsovic K (2012) Mixed integer programming-based reconfiguration of a distribution system with battery storage. North American Power Symposium (NAPS), 2012, 1-6.

28. Nagata T, Sasaki H, Yokoyama R (1995) Power system restoration by joint usage of expert system and mathematical programming approach. IEEE Trans Power Syst 10: 1473-1479.

29. Narimani M, Vahed A, Azizipanah-Abarghooee R, et al. (2014) Enhanced gravitational search algorithm for multi-objective distribution feeder reconfiguration considering reliability, loss and operational cost. IET Gener Transm Dis 8: 55-69.

30. Shirmohammadi D, Hong H (1989) Reconfiguration of electric distribution networks for resistive line losses reduction. IEEE Trans Power Deliver 4: 1492-1498.

31. Wu YK, Lee CY, Liu LC, et al. (2010) Study of reconfiguration for the distribution system with distributed generators. IEEE Trans Power Deliver 25: 1678-1685.

32. Xiaodan Y, Hongjie J, Chengshan W, et al. (2009) Network reconfiguration for distribution system with micro-grids. Sustainable Power Generation and Supply, 2009. SUPERGEN ’09. International Conference on, 1-4.

33. Xyngi I, Ishchenko A, Popov M, et al. (2009) Transient stability analysis of a distribution network with distributed generators. IEEE Trans Power Syst 24: 1102-1104.

34. Yen JY (1971) Finding the k shortest loopless paths in a network. Management Science 17, 712-716.

35. Zimmerman R, Murillo-S´ a andnchez C, Thomas R (2011) Matpower: Steady-state operations, planning, and analysis tools for power systems research and education. IEEE Trans Power Syst 26: 12-19.

Copyright Info: © 2016, Md Mashud Hyder, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Article outline

Show full outline