Skip to main content
Log in

Optimal UPQC location in power distribution network via merging genetic and dragonfly algorithm

  • Special Issue
  • Published:
Evolutionary Intelligence Aims and scope Submit manuscript

Abstract

Nowadays, flexible alternating current transmission system devices, particularly unified power quality conditioner (UPQC) are found to have significant impacts on stability of rising power system. In power systems, several intellectual optimization methods were exploited to position the UPQC. However, those optimization models fail to offer more reliability and feedback signal. Hence, this paper presents a power quality improvement model, which is based on a hybrid algorithm that links genetic algorithm (GA) and DragonFly algorithm (DA). In the current research work, the optimal solution is determined based on the crossover operation of GA in dragonfly algorithm (DA), and hence, the adopted model is named as Genetically Modified DA algorithm. Moreover, the proposed model discovers the optimal location of UPQC device by focusing on the UPQC cost, power losses, and Voltage stability Index. The proposed model is carried out in IEEE 69, and IEEE 33 test bus systems. In addition, the performance of implemented model is distinguished over other conventional models such as artificial bee colony, firefly, grey wolf optimization, whale optimization algorithm, worst solution linked whale optimization algorithm update (WS-WU), GA and DA. The performance of the proposed model is effectively proved by performance and convergence analysis.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Lakshmi S, Ganguly S (2017) Energy loss minimization with open unified power quality conditioner placement in radial distribution networks using particle swarm optimization. In: 2017 7th international conference on power systems (ICPS), Pune, pp. 55–60

  2. Shafiullah Md, Rana MdJ, Shahriar MS, Zahir MdH (2019) Low-frequency oscillation damping in the electric network through the optimal design of UPFC coordinated PSS employing MGGP. Measurement 138:118–131

    Article  Google Scholar 

  3. Sarker J, Goswami SK (2016) Optimal location of unified power quality conditioner in distribution system for power quality improvement. Electr Power Energy Syst 83:309–324

    Article  Google Scholar 

  4. Lakshmi S, Ganguly S (2018) Simultaneous optimisation of photovoltaic hosting capacity and energy loss of radial distribution networks with open unified power quality conditioner allocation. IET Renew Power Gener 12(12):1382–1389

    Article  Google Scholar 

  5. Lakshmi Shubh, Ganguly Sanjib (2019) Multi-objective planning for the allocation of PV-BESS integrated open UPQC for peak load shaving of radial distribution networks. J Energy Storage 22:208–218

    Article  Google Scholar 

  6. Lakshmi S, Ganguly S (2018) Modelling and allocation of open-UPQC-integrated PV generation system to improve the energy efficiency and power quality of radial distribution networks. IET Renew Power Gener 12(5):605–613

    Article  Google Scholar 

  7. Gowtham N, Shankar S (2018) UPQC: a custom power device for power quality improvement. Mater Today Proc 5(1):965–972

    Article  Google Scholar 

  8. Bhosale SS, Bhosale YN, Chavan UM, Malvekar SA (2018) Power quality improvement by using UPQC: a review. In: 2018 International conference on control, power, communication and computing technologies (ICCPCCT), pp 375–380

  9. Zeb K, Uddin W, Khan MA, Ali Z, Ali MU, Christofides N, Kim HJ (2018) A comprehensive review on inverter topologies and control strategies for grid connected photovoltaic system. Renew Sustain Energy Rev 94:1120–1141

    Article  Google Scholar 

  10. Ambati BB, Khadkikar V (2014) Optimal sizing of UPQC considering VA loading and maximum utilization of power-electronic converters. IEEE Trans Power Deliv 29(3):1490–1498

    Article  Google Scholar 

  11. Correa Monteiro F, Aredes M, Pinto JG, Exposto BF, Afonso JL (2016) Control algorithms based on the active and non-active currents for a UPQC without series transformers. IET Power Electron 9(9):1985–1994

    Article  Google Scholar 

  12. Senthilnathan K, Annapoorani I (2016) Implementation of unified power quality conditioner (UPQC) based on current source converters for distribution grid and performance monitoring through LabVIEW Simulation Interface Toolkit server: a cyber physical model. IET Gener Transm Distrib 10(11):2622–2630

    Article  Google Scholar 

  13. Ye J, Gooi HB, Wu F (2018) Optimization of the size of UPQC system based on data-driven control design. IEEE Trans Smart Grid 9(4):2999–3008

    Article  Google Scholar 

  14. Devassy S, Singh B (2017) Modified pq-theory-based control of solar-PV-integrated UPQC-S. IEEE Trans Ind Appl 53(5):5031–5040

    Article  Google Scholar 

  15. Devassy S, Singh B (2018) Design and performance analysis of three-phase solar PV integrated UPQC. IEEE Trans Ind Appl 54(1):73–81

    Article  Google Scholar 

  16. Devassy S, Singh B (2017) Control of solar photovoltaic integrated UPQC operating in polluted utility conditions. IET Power Electron 10(12):1413–1421

    Article  Google Scholar 

  17. Ye J, Gooi HB, Wu F (2018) Optimal design and control implementation of UPQC based on variable phase angle control method. IEEE Trans Ind Inf 14(7):3109–3123

    Article  Google Scholar 

  18. Khadem SK, Basu M, Conlon MF (2015) Intelligent islanding and seamless reconnection technique for microgrid with UPQC. IEEE J Emerg Sel Top Power Electron 3(2):483–492

    Article  Google Scholar 

  19. Axente I, Ganesh JN, Basu M, Conlon MF, Gaughan K (2010) A 12-kVA DSP-controlled laboratory prototype UPQC capable of mitigating unbalance in source voltage and load current. IEEE Trans Power Electron 25(6):1471–1479

    Article  Google Scholar 

  20. Vinnakoti S, Kota VR (2018) Implementation of artificial neural network based controller for a five-level converter based UPQC. Alex Eng J 57(3):1475–1488

    Article  Google Scholar 

  21. Patel A, Mathur HD, Bhanot S (2018) An improved control method for unified power quality conditioner with unbalanced load. Int J Electr Power Energy Syst 100:129–138

    Article  Google Scholar 

  22. Khadem SK, Basu M, Conlon MF (2016) A comparative analysis of placement and control of UPQC in DG integrated grid connected network. Sustain Energy Grids Netw 6:46–57

    Article  Google Scholar 

  23. Fernández JR, López-Campos JA, Segade A, Vilán JA (2018) A genetic algorithm for the characterization of hyperelastic materials. Appl Math Comput 329:239–250

    MathSciNet  MATH  Google Scholar 

  24. Jafari M, Chaleshtari MHB (2017) Using dragonfly algorithm for optimization of orthotropic infinite plates with a quasi-triangular cut-out. Eur J Mech A/Solids 66:1–14

    Article  MathSciNet  Google Scholar 

  25. Gaddala K, Raju S (2020) Merging lion with crow search algorithm for optimal location and sizing of UPQC in distribution network. J Control Autom Electr Syst 2020:1–16

    Google Scholar 

  26. Mirjalili Seyedali, Lewis Andrew (2016) The whale optimization algorithm. Adv Eng Softw 95:51–67

    Article  Google Scholar 

  27. Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46–61

    Article  Google Scholar 

  28. Wang H, Wang W, Zhou X, Sun H, Cui Z (2017) Firefly algorithm with neighborhood attraction. Inf Sci 382–383:374–387

    Article  Google Scholar 

  29. Kıran MS, Fındık O (2015) A directed artificial bee colony algorithm”. Appl Soft Comput 26:454–462

    Article  Google Scholar 

  30. Biswas S, Goswami SK, Chatterjee A (2014) Optimal distributed generation placement in shunt capacitor compensated distribution systems considering voltage sag and harmonics distortions. IET Gener Transm Distrib 8(5):783–797

    Article  Google Scholar 

  31. Taher SA, Afsari SA (2012) Optimal location and sizing of UPQC in distribution networks using differential evolution algorithm. Math Probl Eng 2012:1–20

    Article  MathSciNet  Google Scholar 

  32. Kumarasabapathy N, Manoharan PS (2015) MATLAB simulation of UPQC for power quality mitigation using an ant colony based fuzzy control technique. Sci World J 2015:1–9

    Article  Google Scholar 

  33. Marotkar DS, Zade P, Kapur V (2015) Design of microstrip patch antenna with asymetric sai shape DGS for Bandwidth enhancement. In: Applied electromagnetics conference (AEMC), IEEE, pp 1–2

  34. Marotkar DS, Zade P (2016) Bandwidth enhancement of microstrip patch antenna using defected ground structure. In: 2016 international conference on electrical, electronics, and optimization techniques (ICEEOT), Chennai, pp 1712–1716. https://doi.org/10.1109/iceeot.2016.7754978

  35. Kumaraswamy B, Poonacha PG (2017) Modified square difference function using fourier series approximation for pitch estimation. In: 2017 international conference on algorithms, methodology, models and applications in emerging technologies (ICAMMAET), pp 1–8

  36. Kumar SBV, Rao PV, Sharath HA, Sachin BM, Ravi US, Monica BV (2018) Review on VLSI design using optimization and self-adaptive particle swarm optimization. J King Saud Univ Comput Inf Sci. https://doi.org/10.1016/j.jksuci.2018.01.001

    Article  Google Scholar 

  37. Mahammad Shareef SK, Srinivasa Rao R (2018) Optimal reactive power dispatch under unbalanced conditions using hybrid swarm intelligence. Comput Electr Eng 69:183–193

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kaladhar Gaddala.

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

Gaddala, K., Sangameswara Raju, P. Optimal UPQC location in power distribution network via merging genetic and dragonfly algorithm. Evol. Intel. 15, 1219–1232 (2022). https://doi.org/10.1007/s12065-020-00364-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12065-020-00364-1

Keywords