Skip to main content

Reliability Evaluation of Distribution System with Network Reconfiguration and Distributed Generations

  • Chapter
  • First Online:
Sustainable Power Systems

Abstract

This chapter titled “Reliability Evaluation of Distribution System with Network Reconfiguration and Distributed Generations” proposes reliability and power loss evaluation of distribution system using network reconfiguration tool and optimal DG siting and sizing. The objectives are reliability improvement and power loss reduction subjected to various operating constraints. The renewable DG technologies including the synchronous machine-based biomass generator are considered in distribution system expansion planning. The network reconfiguration with DGs and tie-switch placement for the reliability improvement and loss minimization is proposed. Tie-switches are placed at terminal nodes with geographical constraints and their all possible binary combinations are considered. DGs sizing for the predefined DGs are calculated using integer programming for objective viz. reliability improvement and minimization of losses with penetration level taken for less than total load. Power loss is calculated using forward/backward sweep distribution load flow algorithm in all the cases analyzed. A search-based reconfiguration algorithm has been formulated for finding the optimal switch configuration for the radial distribution system with DG. The optimal DG placement and DG sizing for combined objectives of reliability improvement and loss minimization, using fuzzy logic approach is proposed in two steps. Out of four DG variables, type, and number are taken as fixed variables and size and location are considered as variables in the formulation. In the first step, for all DGs combination, their optimal sizes are calculated using nonlinear optimization tool with the improved reliability and real power loss reduction objectives. SAIDI and SAIFI indices are used for the reliability evaluation in this case. In the formulation three indices, power loss, SAIDI and SAIFI are used with weighing factors and taken as combined objective. A combined network reconfiguration and optimal DG siting and sizing is carried out for the objectives viz. real power loss reduction and reliability improvement for various penetration levels and various loading conditions. It is observed that optimal sitting and sizing of the DGs improve the system performance in terms of real power loss reduction and improvement in the system reliability. Different objectives give different optimal locations and sizes but based on the physical constraints, the final decisions are to be made. The present work may be a guideline to the planners and policy makers for planning the DGs in the distribution systems.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Gonen T (1986) Electric power distribution system. McGraw Hill, Inc.

    Google Scholar 

  2. Billinton R, Allan RN (1996) Reliability evaluation of power systems, 2nd edn. Plenum, New York

    Google Scholar 

  3. Borges CLT, Falcao DM (2006) Optimal distributed generation allocation for reliability, losses and voltage improvement. Int J Electr Power Energy Syst 28(6):413–420

    Google Scholar 

  4. Soroudi A, Afrasiab M (2012) Binary PSO-based dynamic multi-objective model for distributed generation planning under uncertainty. IET Renew Power Gener 6(2):67–78

    Article  Google Scholar 

  5. Moradi MH, Abedini M (2012) A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. Int J Electr Power Energy Syst 34(1):66–74

    Article  Google Scholar 

  6. Ettehadi M, Ghasemi H, Vaez-Zadeh S (2013) Voltage stability-based DG placement in distribution networks. IEEE Trans Power Del 28(1):171–178

    Google Scholar 

  7. Amanulla B, Chakrabarti S, Singh SN (2012) Reconfiguration of power distribution systems considering reliability and power loss. IEEE Trans Power Del 27(2):918–926

    Article  Google Scholar 

  8. Mao Y, Miu KN (2003) Switch placement to improve system reliability for radial distribution systems with distributed generation. IEEE Trans Power Syst 18(4):1346–1352

    Google Scholar 

  9. Han L, Zhou R, Deng X (2009) An analytical method for DG placements considering reliability improvements. In: IEEE PES GM, July 2009, pp 1–5

    Google Scholar 

  10. Rao RS, Narasimham SVL, Raju MR, Rao AR (2011) Optimal network reconfiguration of large-scale distribution system using harmony search algorithm. IEEE Trans Power Syst 26(3):1080–1088

    Google Scholar 

  11. Rao RS, Ravindra K, Satish K, Narasimham SVL (2013) Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation. IEEE Trans Power Syst 28(1):317–325

    Article  Google Scholar 

  12. Georgilakis PS, Hatziargyriou ND (2013) Optimal distributed generation placement in power distribution networks: models, methods, and future research. IEEE Trans Power Syst 28(3):3420–3428

    Article  Google Scholar 

  13. IEEE Application Guide for IEEE Std 1547, IEEE Standard for Interconnecting Distributed Resources With Electric Power Systems 2008

    Google Scholar 

  14. Walling RA, Saint R, Dugan RC, Burke J, Kojovic LA (2008) Summary of distributed resources impact on power delivery systems. IEEE Trans Power Del 23(3):1636–1644

    Article  Google Scholar 

  15. Wang C, Hehrir MH (2004) Analytical approaches for optimal placement of distributed generation sources in power systems. IEEE Trans Power Syst 19(4):2068–2076

    Article  Google Scholar 

  16. Acharya N, Mahat P, Mithulananthan N (2006) An analytical approach for DG allocation in primary distribution network. Int J Electr Power Energy Syst 28(10):669–678

    Article  Google Scholar 

  17. Ettehadi M, Ghasemi H, Vaez-Zadeh S (2013) Voltage stability-based DG placement in distribution networks. IEEE Trans Power Del 28(1):171–178

    Article  Google Scholar 

  18. Al Abri RS, El-Saadany EF, Atwa YM (2013) Optimal placement and sizing method to improve the voltage stability margin in a distribution system using distributed generation. IEEE Trans Power Syst 28(1):326–334

    Google Scholar 

  19. Esmaili M (2013) Placement of minimum distribution generation units observing power losses and voltage stability with network constraints. IET Gen Transm Distrib 7(8):813–821

    Article  Google Scholar 

  20. Lee SH, Park J-W (2003) Optimal placement and sizing of multiple DGs in a practical distribution system by considering power loss. IEEE Trans Ind Appl 49(5):2262–2270

    Article  Google Scholar 

  21. Kroposki B, Sen PK, Malmedal K (2003) Optimum sizing and placement of distributed and renewable energy sources in electric power distribution systems. IEEE Trans Ind Appl 49(6):2741–2752

    Article  Google Scholar 

  22. Pandi VR, Zeineldin HH, Xiao W (2013) Determining optimal location and size of distributed generation resources considering harmonic and protection coordination limits. IEEE Trans Power Syst 28(2)1245–1254

    Google Scholar 

  23. Hien NC, Mithulananthan N, Bansal RC (2013) Location and sizing of distributed generation units for loadability enhancement in primary feeder. IEEE Syst J 7(4):797–806

    Google Scholar 

  24. Tan WS, Hassan MY, Rahman HA, Abdullah Md P, Hussin F (2013) Multi-distributed generation planning using hybrid particle swarm optimisation- gravitational search algorithm including voltage rise issue. IET Gen Transm Distrib 7(9):929–942

    Google Scholar 

  25. Soroudi A, Ehsan M, Caire R, Hadjsaid N (2011) Possibilistic evaluation of distributed generations impacts on distribution networks. IEEE Trans Power Syst 26(4):2293–2301

    Article  Google Scholar 

  26. Das D (2006) A fuzzy multiobjective approach for network reconfiguration of distribution systems. IEEE Trans Power Del 21(1):202–209

    Article  Google Scholar 

  27. Zimmermann HJ (1999) Fuzzy programming and linear programming with several objectives. Proc Inst Elect Eng Gen Transm Distrib 641–648

    Google Scholar 

  28. Pavani P, Singh SN (2013) Reconfiguration of radial distribution networks with distributed generation for reliability improvement and loss minimization. In: IEEE PES GM Conference, Vancouver, Canada, July 2013

    Google Scholar 

  29. Alessio I, Ashraf L (2009) Analytic hierarchy process and expert choice: benefits and limitations. OR Insight 22(4):201–220

    Article  Google Scholar 

  30. Baran ME, Wu F (1989) Network reconfiguration in distribution system for loss reduction and load balancing. IEEE Trans Power Del 4(2):1401–1407

    Article  Google Scholar 

  31. Savier JS, Das D (2007) Impact of network reconfiguration on loss allocation of radial distribution systems. IEEE Trans Power Del 2(4):2473–2480

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S. N. Singh .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media Singapore

About this chapter

Cite this chapter

Pavani, P., Singh, S.N. (2017). Reliability Evaluation of Distribution System with Network Reconfiguration and Distributed Generations. In: Karki, N., Karki, R., Verma, A., Choi, J. (eds) Sustainable Power Systems. Reliable and Sustainable Electric Power and Energy Systems Management. Springer, Singapore. https://doi.org/10.1007/978-981-10-2230-2_4

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-2230-2_4

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2229-6

  • Online ISBN: 978-981-10-2230-2

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics