Skip to main content

Application of Distributed Generation for Reduction of Power Losses and Voltage Deviation in Electric Distribution System by Using AI Techniques

  • Conference paper
  • First Online:
Science and Technologies for Smart Cities (SmartCity360° 2020)

Abstract

Distribution Electric power system is the largest and the most complex system made by the mankind. The distribution network power system is being encountered by quickly rising load demand and it is detected that under certain critical loading circumstances, the distribution system poses maximum power losses and poor voltage profile and collapse in convinced areas. To overcome these problems integrating distributed generation (DGs) on the grid near to the load center is the better solution as compared to others. Though, for the DG to serve its purpose, its location and size have to be determined optimally. In this paper, Grid-Based Multi-Objective Harmony Search Algorithm (GrMHSA) has been utilized to determine the size and location of DG in the distribution system in Debre Markos town. By placing DG optimally, in addition to the reduction of the power loss in the distribution network, the proposed mechanism improves the node (bus) voltage profile of the system under consideration. A MATLAB program is developed to mitigate power losses and improve the voltage profile by optimally sizing and placing a DG in the distribution network. After sizing and placing the DG in the network, the total voltage deviation, active and reactive power losses are reduced by 93.42%, 81.63% and 82.45% for Debre Markos Feeder 3 and 85.20%, 84.94% and 85.73% for Debre Markos Feeder 4 respectively. The performance comparison of GrMHSA and MOPSO has been made and GrMHSA has been found better in terms of reducing voltage deviation and power losses in the system.

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 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Kayalvizhi, S., DM, V.K.: Optimal planning of active distribution networks with hybrid distributed energy resources using grid-based multi-objective harmony search algorithm. Appl. Soft Comput. 67, 387–398 (2018)

    Google Scholar 

  2. Payasi, R.P., Singh, A.K., Singh, D., Singh, N.K.: Multi-objective optimization of distributed generation with voltage step constraint. Int. J. Eng. Sci. Technol. 7(3), 33–41 (2015)

    Article  Google Scholar 

  3. Ferede, A.T., Olalekan, S.A., Abel, H.E., Ayalew, A.Y.: Power loss mitigation and voltage profile improvement with distributed generation using grid-based multi-objective harmony search algorithm. J. Electr. Electron. Eng. (JEEE) 13(2) (2020). P-ISSN 1844-6035

    Google Scholar 

  4. Nguyen, T.T., Truong, A.V.: Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm. Int. J. Electr. Power Energy Syst. 68, 233–242 (2015)

    Article  Google Scholar 

  5. Awoke, Y.A., Agajie, T.F., Hailu, E.A.: Distribution network expansion planning considering DG-penetration limit using a metaheuristic optimization technique: a case study at Debre Markos distribution network. Int. J. Electr. Eng. Inf. 12(2), 326–340 (2020)

    Google Scholar 

  6. Paliwal, P., Patidar, N.P., Nema, R.K.: Planning of grid integrated distributed generators: a review of technology, objectives and techniques. Renew. Sustain. Energy Rev. 40, 557–570 (2014)

    Article  Google Scholar 

  7. Pal, A., Chakraborty, A.K., Bhowmik, A.R.: Optimal placement and sizing of DG considering power and energy loss minimization in distribution system. Int. J. Electr. Eng. Inf. 12(3), 624–653 (2020)

    Google Scholar 

  8. Agajie, T.F., Salau, A.O., Hailu, E.A., Sood, M., Jain, S.: Optimal sizing and siting of distributed generators for minimization of power losses and voltage deviation. In: 2019 5th International Conference on Signal Processing, Computing and Control (ISPCC), pp. 292–297. IEEE, October 2019

    Google Scholar 

  9. Singh, P., Bishnoi, S.K., Meena, N.K.: Moth search optimization for optimal DERs integration in conjunction to OLTC tap operations in distribution systems. IEEE Syst. J. 14(1), 880–888 (2019)

    Article  Google Scholar 

  10. Georgilakis, P.S., Hatziargyriou, N.D.: Optimal distributed generation placement in power distribution networks: models, methods, and future research. IEEE Trans. Power Syst. 28(3), 3420–3428 (2013)

    Article  Google Scholar 

  11. Kanwar, N., Gupta, N., Niazi, K.R., Swarnkar, A.: Simultaneous allocation of distributed resources using improved teaching learning based optimization. Energy Convers. Manag. 103, 387–400 (2015)

    Article  Google Scholar 

  12. Prabha, D.R., Jayabarathi, T.: Optimal placement and sizing of multiple distributed generating units in distribution networks by invasive weed optimization algorithm. Ain Shams Eng. J. 7(2), 683–694 (2016)

    Article  Google Scholar 

  13. Meena, N.K., Parashar, S., Swarnkar, A., Gupta, N., Niazi, K.R.: Improved elephant herding optimization for multiobjective DER accommodation in distribution systems. IEEE Trans. Industr. Inf. 14(3), 1029–1039 (2017)

    Article  Google Scholar 

  14. Ogunjuyigbe, A.S.O., Ayodele, T.R., Akinola, O.O.: Impact of distributed generators on the power loss and voltage profile of sub-transmission network. J. Electr. Syst. Inf. Technol. 3(1), 94–107 (2016)

    Article  Google Scholar 

  15. Hung, D.Q., Mithulananthan, N., Bansal, R.C.: Analytical expressions for DG allocation in primary distribution networks. IEEE Trans. Energy Convers. 25(3), 814–820 (2010)

    Article  Google Scholar 

  16. Mohan, N., Ananthapadmanabha, T., Kulkarni, A.D.: A weighted multi-objective index based optimal distributed generation planning in distribution system. Procedia Technol. 21, 279–286 (2015)

    Article  Google Scholar 

  17. Hung, D.Q., Mithulananthan, N.: Multiple distributed generator placement in primary distribution networks for loss reduction. IEEE Trans. Industr. Electron. 60(4), 1700–1708 (2011)

    Article  Google Scholar 

  18. Jamil Mahfoud, R., Sun, Y., Faisal Alkayem, N., Haes Alhelou, H., Siano, P., Shafie-khah, M.: A novel combined evolutionary algorithm for optimal planning of distributed generators in radial distribution systems. Appl. Sci. 9(16), 3394 (2019)

    Article  Google Scholar 

  19. Fandi, G., Ahmad, I., Igbinovia, F.O., Muller, Z., Tlusty, J., Krepl, V.: Voltage regulation and power loss minimization in radial distribution systems via reactive power injection and distributed generation unit placement. Energies 11(6), 1399 (2018)

    Article  Google Scholar 

  20. Quadri, I.A., Bhowmick, S., Joshi, D.: A comprehensive technique for optimal allocation of distributed energy resources in radial distribution systems. Appl. Energy 211, 1245–1260 (2018)

    Article  Google Scholar 

  21. Silvestri, A., Berizzi, A., Buonanno, S.: Distributed generation planning using genetic algorithms. In: PowerTech Budapest 99. Abstract Records (Cat. No. 99EX376), p. 257. IEEE, August 1999

    Google Scholar 

  22. Kim, K.H., Lee, Y.J., Rhee, S.B., Lee, S.K., You, S.K.: Dispersed generator placement using fuzzy-GA in distribution systems. In: IEEE Power Engineering Society Summer Meeting, vol. 3, pp. 1148–1153. IEEE, July 2002

    Google Scholar 

  23. Carpinelli, G., Celli, G., Pilo, F., Russo, A.: Distributed generation siting and sizing under uncertainty. In: 2001 IEEE Porto Power Tech Proceedings (Cat. No. 01EX502), vol. 4, pp. 7-pp. IEEE, September 2001

    Google Scholar 

  24. Naik, S.N.G., Khatod, D.K., Sharma, M.P.: Analytical approach for optimal siting and sizing of distributed generation in radial distribution networks. IET Gener. Transm. Distrib. 9(3), 209–220 (2014)

    Article  Google Scholar 

  25. Ala’a, A., Alsewari, A.A., Alamri, H.S., Zamli, K.Z.: Comprehensive review of the development of the harmony search algorithm and its applications. IEEE Access 7, 14233–14245 (2019)

    Google Scholar 

  26. Ingram, G., Zhang, T.: Overview of applications and developments in the harmony search algorithm. In: Geem, Z.W. (ed.) Music-Inspired Harmony Search Algorithm, pp. 15–37. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-00185-7_2

    Chapter  Google Scholar 

  27. Assad, A.: Recent advances in harmony search algorithm. In: Recent Advances in Harmony Search Algorithm, pp. 157–165 (2019)

    Google Scholar 

  28. Aghaei, J., Muttaqi, K., Azizivahed, A., Gitizadeh, M.: Distribution expansion planning considering reliability and security of energy using modified PSO (Particle Swarm Optimization) algorithm. Energy 65, 398–411 (2014)

    Article  Google Scholar 

  29. Gantayet, A., Mohanty, S.: An analytical approach for optimal placement and sizing of Distributed Generation based on a combined voltage stability index. In: 2015 IEEE Power, Communication and Information Technology Conference (PCITC), pp. 762–767. IEEE, October 2015

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Agajie, T.F., Srinivas Rao, G.L., Hailu, E.A., Awoke, Y.A., Anteneh, T.M., Gebru, F.M. (2021). Application of Distributed Generation for Reduction of Power Losses and Voltage Deviation in Electric Distribution System by Using AI Techniques. In: Paiva, S., Lopes, S.I., Zitouni, R., Gupta, N., Lopes, S.F., Yonezawa, T. (eds) Science and Technologies for Smart Cities. SmartCity360° 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 372. Springer, Cham. https://doi.org/10.1007/978-3-030-76063-2_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-76063-2_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-76062-5

  • Online ISBN: 978-3-030-76063-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics