Skip to main content
SpringerLink
Log in

Optimal locations and sizing of capacitors in radial distribution systems using mine blast algorithm

  • Original Paper
  • Published:
Electrical Engineering Aims and scope Submit manuscript

Abstract

In this paper, a mine blast algorithm (MBA) is proposed for optimal allocations and sizing of capacitors in various distribution systems. First, the most candidate buses for installing capacitors are suggested using loss sensitivity factors (LSF). Then, the proposed MBA is employed to deduce the size of capacitors and their locations from the elected buses. The objective function is designed to reduce the total cost and, consequently, to increase the net saving per year. The proposed algorithm is tested on 10 and 85 bus radial distribution systems. The obtained results via the proposed algorithm are compared with others to highlight their benefits. Moreover, the results are introduced to verify the effectiveness of the suggested algorithm to minimize the losses and total cost and to enhance the voltage profile and net saving for various distribution systems and loading conditions.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Abbreviations

\(P_k ,Q_k \) :

The total effective active and reactive power supplied behind the bus ‘k’

\(V_k \) :

The magnitude of voltage at bus k

\(R_{ik}, X_{ik}\) :

The resistance and reactance of transmission line between bus ‘i’ and ‘k’

\(V_i \) :

The magnitude of voltage at bus i

\(X_o \) :

The generated first shot point

\(\mathrm{LB}\) :

The lower bounds of the problem

\(\mathrm{UB}\) :

The upper bounds of the problem

\(\mathrm{rand}\) :

The uniformly distributed random number between 0 and 1

\(N_d \) :

The search space dimension equal to the number of independent variables

\(\theta \) :

The angle of the shrapnel pieces which is calculated using \(\theta =360/N_S\)

\(N_S \) :

The number of shrapnel pieces

\(N_{\mathrm{pop}} \) :

The number of initial population

\(X_{e(n+1)}^f \) :

The location of exploding mine bomb collided by shrapnel

\(d_{n+1}^f \) :

The distance of the thrown shrapnel pieces in each iteration

\(m_{n+1}^f \) :

The direction of the thrown shrapnel pieces in each iteration

F :

The function value for the X

\(\mu \) :

The exploration factor

\(K_P \) :

The cost per KW-Hours

\(P_{Loss} \) :

The total power losses after compensation

T :

The time in hours

D :

The depreciation factor.

CB :

The number of compensated buses

\(K_C \) :

The cost per Kvar

\(K_I \) :

The cost per installation

\(Q_{Ci} \) :

The value of installed reactive power in Kvar

\(K_o \) :

The operating cost

\(P_{\mathrm{Swing}}\) :

The active power of swing bus

\(Q_{\mathrm{Swing}}\) :

The reactive power of swing bus

L :

The number of transmission line in a distribution system

Pd(q) :

The demand of active power at bus q

Qd(q):

The demand of reactive power at bus q

N :

The number of total buses

\(V_{\min }\) :

The minimum voltage at bus i

\(V_{\max }\) :

The maximum voltage at bus i

PF :

Power factor

\(PF_{\min }\) :

The minimum power factor

\(PF_{\max }\) :

The maximum power factor

\(PF_{\mathrm{sys}}\) :

The power factor at swing bus

\(S_{\mathrm{Li}} \) :

The actual complex power in line i

\(S_{\mathrm{Li(rated)}}\) :

The rated line complex power in that line i

MBA:

Mine blast algorithm

LSF:

Loss sensitivity factors

SA:

Simulated annealing

TS:

Tabu search

GA:

Genetic algorithm

PSO:

Particle swarm optimization

PGSA:

Plant growth simulation algorithm

DSA:

Direct search algorithm

TLBO:

Teaching learning-based optimization

CSA:

Cuckoo search algorithm

ABC:

Artificial bee colony

ACO:

Ant colony optimization

BF:

Bacteria foraging

FA:

Firefly algorithm

HS:

Harmony search

IHA:

Improved harmony algorithm

DE:

Differential evolution

FPA:

Flower pollination algorithm

References

  1. Rao RS, Narasimham SVL, Ramakingaraju M (2011) Optimal capacitor placement in a radial distribution system using plant growth simulation algorithm. Int J Electr Power Energy Syst 33:1133–1139

    Article  Google Scholar 

  2. Jabr RA (2008) Optimal placement of capacitors in a radial network using conic and mixed integer linear programming. Electr Power Syst Res 78:941–948

    Article  Google Scholar 

  3. Wong KP (1995) Solving power system optimization problems using simulated annealing. Eng Appl Artif Intell 8(6):665–670

    Article  Google Scholar 

  4. Huang YC, Yang HT, Huang CL (1996) Solving the capacitor placement problem in a radial distribution system using tabu search approach. IEEE Trans Power Syst 11(4):1868–1873

    Article  MathSciNet  Google Scholar 

  5. Sydulu M, Reddy V (2007) Index and GA based optimal location and sizing of distribution system capacitors. IEEE Power Eng Soc Gen Meet 24–28:1–4

    Google Scholar 

  6. Prakash K (2007) Particle swarm optimization based capacitor placement on radial distribution systems. IEEE Power Eng Soc Gen Meet 24–28:1–5

    Google Scholar 

  7. Lee CS, Ayala HVH, Coelho L (2015) Capacitor placement of distribution systems using particle swarm optimization approaches. Int J Electr Power Energy Syst 64:839–851

    Article  Google Scholar 

  8. Raju M, Murthy K, Avindra K (2012) Direct search algorithm for capacitive compensation in radial distribution systems. Int J Electr Power Energy Syst 42(1):24–30

    Article  Google Scholar 

  9. Sultana S, Roy PK (2014) Optimal capacitor placement in radial distribution systems using teaching learning based optimization. Int J Electr Power Energy Syst 54:387–398

    Article  Google Scholar 

  10. Sarma AK (2011) Optimal selection of capacitors for radial distribution systems using plant growth simulation algorithm. Int J Adv Sci Technol 30:43–54

    Google Scholar 

  11. da Silva IC, Carneiro S Jr, de Oliveira EJ, de Souza Costa J, Pereira JLR, Garcia PAN (2008) A heuristic constructive algorithm for capacitor placement on distribution systems. IEEE Trans Power Syst 23(4):1619–1626

    Article  Google Scholar 

  12. Reddy DP, Gunaprasad K (2014) Sensitivity based capacitor placement using cuckoo search algorithm for maximum annual savings. IOSR J Eng 4(4):6–9

    Article  Google Scholar 

  13. Arcanjo DN, Pereira JLR, Oliveira EJ, Peres W, de Oliveira LW, da Silva Jr IC (2012) Cuckoo search optimization technique applied to capacitor placement on distribution system problem. In: 10th IEEE/IAS Int Conf on industry applications (INDUSCON), 2012, 5–7, Fortaleza, pp 1–6

  14. Reddy VU, Anohar TG (2013) Optimal capacitor placement for loss reduction in distribution systems by using cuckoo search algorithm. ITSI Trans Electr Electron Eng 1(2):68–70

    Google Scholar 

  15. Rao RS (2010) Capacitor placement in radial distribution system for loss reduction using artificial bee colony algorithmz. Int J Electr Comput Energ Electron Commun Eng 4(8):1108–1112

    Google Scholar 

  16. Taher SA, Bagherpour R (2013) A new approach for optimal capacitor placement and sizing in unbalanced distorted distribution systems using hybrid honey bee colony algorithm. Int J Electr Power Energy Syst 49:430–448

    Article  Google Scholar 

  17. Muthukumar K, Jayalalitha S, Cherukuri SHC (2014) Artificial bee colony algorithm based approach for optimal sizing and location of shunt capacitors in radial distribution systems with composite and exponential loads. ARPN J Eng Appl Sci 9(7):1099–1106

    Google Scholar 

  18. Su CT, Chung CF, Chiou JP (2005) Distribution network reconfiguration for loss reduction by ant colony search algorithm. Electr Power Syst Res 75(2–3):190–199

    Article  Google Scholar 

  19. Kasaei MJ, Gandomkar M (2009) Loss reduction in distribution system with simultaneous using of capacitor placement and reconfiguration by ant colony algorithm. In: 24th int power system conference, 23–25 Nov. 2009, Iran, Tehran

  20. Devabalaji KR, Ravi K, Kothari DP (2015) Optimal location and sizing of capacitor placement in radial distribution system using bacterial foraging optimization algorithm. Int J Electr Power Energy Syst 71:383–390

    Article  Google Scholar 

  21. Soleymani M, Soleymani S, Zayandehroodi H, Eslami M, Khajehzadeh A (2014) Capacitor location and size determination to reduce power losses of a distribution feeder by firefly algorithm. Int J Sci Eng Res 5(9):419–424

    Google Scholar 

  22. Sirjani R, Mohamed A, Shareef H (2010) Optimal capacitor placement in a radial distribution system using harmony search algorithm. J Appl Sci 10(23):2998–3006

    Article  Google Scholar 

  23. Muthukumar K, Jayalalitha S, Ramasamy M, Haricharan C (2014) Optimal shunt capacitor allocation and sizing using harmony search algorithm for power loss minimization in radial distribution networks. Int J Dev Res 4(3):537–545

    Google Scholar 

  24. Wang RT, Yang YL, Wang B, Wang XW, Huang JW, Zeng SZ (2012) Application of optimization algorithm on simulating the fisher fishing in multi-objective optimal reactive power. Energy Procedia 17:1482–1489

    Article  Google Scholar 

  25. Abd-Elaziz AY, Ali ES, Abd-Elazim SM (2016) Flower pollination algorithm for optimal capacitor placement and sizing in distribution systems. Electr Power Compon Syst 44(5):544–555

    Article  Google Scholar 

  26. Abd-Elaziz AY, Ali ES, Abd-Elazim SM (2016) Optimal sizing and locations of capacitors in radial distribution systems via flower pollination optimization algorithm and power loss index. Eng Sci Technol Int J (JESTCH) 19(1):610–618

    Article  Google Scholar 

  27. Abd-Elaziz AY, Ali ES, Abd-Elazim SM (2016) Flower pollination algorithm and loss sensitivity factors for optimal sizing and placement of capacitors in radial distribution systems. Int J Electr Power Energy Syst 78 C:207–214

    Article  Google Scholar 

  28. Ali ES, Abd-Elazim SM, Abd-Elaziz AY (2016) Improved harmony algorithm for optimal locations and sizing of capacitors in radial distribution systems. Int J Electr Power Energy Syst 79 C:275–284

    Article  Google Scholar 

  29. Ali ES, Abd-Elazim SM, Abd-Elaziz AY (2016) Improved harmony algorithm and power loss index for optimal locations and sizing of capacitors in radial distribution systems. Int J Electr Power Energy Syst 80 C:252–263

    Article  Google Scholar 

  30. Jalilzadeh S, Sabouri M, Sharifi E (2012) Optimal capacitor placement in a radial distribution system using shuffled frog leaping and particle swarm optimization algorithms. Int J Netw Secur 3(2):16–20

    Google Scholar 

  31. Sadollah A, Bahreininejad A, Eskandar H, Hamdi M (2013) Mine blast algorithm: a new population based algorithm for solving constrained engineering optimization problems. Appl Soft Comput 13:2592–2612

    Article  Google Scholar 

  32. Sadollah A, Bahreininejad A, Eskandar H, Hamdi M (2012) Mine blast algorithm for optimization of truss structures with discrete variables. Comput Struct 102–103:49–63

    Article  Google Scholar 

  33. Majumdar S, Mandal K, Chakraborty N (2014) Performance study of mine blast algorithm for automatic voltage regulator tuning. In: 2014 Annual IEEE India Conf. (INDICON), 11–13, Dec. 2014, pp 1–6

  34. Lenin K, Reddy BR, SuryaKalavathi M (2014) Abatement of real power loss by using mine blast algorithm. Int J Res Electron Commun Technol 1(2):7–13

    Google Scholar 

  35. Sadollah A, Eskandar H, Kim JH (2014) Geometry optimization of a cylindrical fin heat sink using mine blast algorithm. Int J Adv Manuf Technol 73(5–8):795–804

    Article  Google Scholar 

  36. Sadollah A, Eskandar H, Bahreininejad A, Kim JH (2015) Water cycle, mine blast and improved mine blast algorithms for discrete sizing optimization of truss structures. Comput Struct 149:1–16

    Article  Google Scholar 

  37. Salleh MNM, Hussain K (2016) Accelerated mine blast algorithm for ANFIS training for solving classification problems. Int J Softw Eng Appl 10(6):161–168

    Google Scholar 

  38. Sadollah A, Lee HM, Yoo DG, Kim JH (2016) Mine blast harmony search and its applications, Vol 382 of the series advances in intelligent systems and computing, pp 155–168

  39. Teng JH (2003) A direct approach for distribution system load flow solutions. IEEE Trans Power Deliv 18(3):882–887

    Article  Google Scholar 

  40. Das D, Nagi HS, Kothari DP (1994) Novel method for solving radial distribution networks. IEE Proc Gener Transm Distrib 141(4):291–298

    Article  Google Scholar 

  41. Su CT, Tsai CC (1996) A new fuzzy reasoning approach to optimum capacitor allocation for primary distribution systems. In: Proceeding of the IEEE on industrial technology conference (ICIT ’96), 2–6 December 1996, Shanghai, pp 237–241

  42. Das D, Kothari DP, Kalam A (1995) Simple and efficient method for load flow solution of radial distribution networks. Int J Electr Power Energy Syst 17(5):335–346

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electric Power and Machine Department, Faculty of Engineering, Zagazig University, Zagazig, Egypt

    S. M. Abd Elazim & E. S. Ali

Authors
  1. S. M. Abd Elazim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. E. S. Ali
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to E. S. Ali.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abd Elazim, S.M., Ali, E.S. Optimal locations and sizing of capacitors in radial distribution systems using mine blast algorithm. Electr Eng 100, 1–9 (2018). https://doi.org/10.1007/s00202-016-0475-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00202-016-0475-1

Keywords

Search

Navigation