Skip to main content
Log in

Research on distribution network reconfiguration based on microgrid

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

Micro-grids have been considered as a vital part of power system. The distribution system is gradually showing the characteristics of multi-source initiative. The distribution network reconfiguration with microgrid changes the topology of the network by controlling the state of the switch, and optimizes the predetermined indicators under the premise of safe, economic and stable operation. This paper describes a hierarchical distribution network reconfiguration strategy with microgrid, which can reduce the number of operation of the switch and the network loss. This strategy ensures rapid power supply recovery. In the process of reconstruction, this paper uses the immune clonal selection differential evolution algorithm. The simulation examples are included to display the performance of the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Chiou JP, Chang CF, Su CT (2005) variable scaling hybrid differential evolution for solving network reconfiguration system. IEEE Trans Power Systems 20(2):668–674

    Article  Google Scholar 

  • Dasgupta D, Attoh-Okine N (1997) Immunity based systems: a survey. Proc IEEE Int Conf Syst 7(5):369–374

    Google Scholar 

  • Evangelopoulos VA, Geor Gilakis PS (2014) Optimal distributed generation placement under uncertainties based on point estimate method embedded genetic algorithm. IET Gen Transm Distrib 8(3):389–400

    Google Scholar 

  • Fei D, Loparo KA (2015) Hierarchical decentralized network reconfiguration for smart distribution systems—Part II: problem formulation and algorithm development. IEEE Trans Power Syst 30:744–752

    Article  Google Scholar 

  • Hsuyy H (1992) Voltage control using a combined integer linear programming and a rule-based approach. IEEE Trans Power Syst 7(2):744–748

    Article  Google Scholar 

  • Imran AM, Kowsalya M, Kothari DP (2014) A novel integration technique for optimal network reconfiguration and distributed generation placement in power distribution networks. Electr Power Energy Syst 63:461–472

    Article  Google Scholar 

  • Kuo H-C, Hsu Y-Y (1993) Distribution system load estimation and service restoration using a fussy set approach. IEEE Trans Power Deliv 8(4):1950–1957

    Article  Google Scholar 

  • Lasseter RH, Paigi P (2004) Microgrid: a conceptual solution. In: Power electronics specialists conference, pp 4285–4290

  • Li YW, Vilathgamuwa DM, Loh PC (2004) Design, analysis, and real-time testing of a controller for multi-bus microgrid system. IEEE Trans Power Electron 19(2):1195–1204

    Article  Google Scholar 

  • Li-Jue L, Cai ZX, Chen H (2006) Immunity clone algorithm with particle swarm evolution. J Cent South Univ Technol 13(6):703–707

    Article  Google Scholar 

  • Nara K, Shiose A, Kitagawa M (1992) Implementation of genetic algorithm for distribution systems loss minimum re-configuration. IEEE Trans Power Syst 7(3):1044–1051

    Article  Google Scholar 

  • Niknam T, Fard AK, Baziar A (2012) Multi-objective stochastic distribution feeder reconfiguration problem considering hydrogen and thermal energy production by fuel cell power plants. Energy 42:563–573

    Article  Google Scholar 

  • Prasad K, Ranjan R, Sahoo NC, Chaturvedi A (2005) Optimal reconfiguration of radial distribution systems using a fuzzy mutated genetic algorithm. IEEE Trans Power Deliv 20(2):1211–1213

    Article  Google Scholar 

  • RainerStorn KP (1997) Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11(4):341–349

    Article  MathSciNet  Google Scholar 

  • Shilpa K, Ganga A (2014) Loss minimization techniques used indistribution network. Renew Sustain Energy Rev 29(1):184–200

    Google Scholar 

  • Tan S, Xu J, Panda SK (2012) Optimization of distribution network incorporating microgrid using vaccine-AIS. In: IEEE Industry electronics society conf (IECON), pp 1381–1386

  • Timmis J, Knight T (2001) Artificial immunes system: using the immune system as inspiration for data mining. Heuristic approach 12(5):209–215

    Google Scholar 

  • Wang X, Li X (2012) Fault recovery of micro-grid based on network reconfiguration. In: IEEE power and energy engineering conf (APPEEC), pp 1–4

  • Wei L, Xiaolong J, Yunfei M (2014) A novel reconfiguration strategy for active distribution network considering maximum power supply capability. Appl Mech Mater 448:2747–2752

    Google Scholar 

  • Zeineldin HH, Bhattacharya K, El-aadany EF (2006) Impact of intentional islanding of distributed generation on electricity market prices. IEE Proc Gen Transm Distrib 53(2):147–154

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xuejie Wang.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, X., Ji, Y., Wang, J. et al. Research on distribution network reconfiguration based on microgrid. J Ambient Intell Human Comput 11, 3607–3615 (2020). https://doi.org/10.1007/s12652-019-01542-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-019-01542-5

Navigation