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Multi-objective optimization of optimal capacitor allocation in radial distribution systems

  • Sayed Mir Shah Danish ORCID logo EMAIL logo , Mikaeel Ahmadi , Atsushi Yona , Tomonobu Senjyu , Narayanan Krishna ORCID logo and Hiroshi Takahashi
Published/Copyright: July 4, 2020
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International Journal of Emerging Electric Power Systems
From the journal International Journal of Emerging Electric Power Systems Volume 21 Issue 3

Abstract

The optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

Keywords: capacitor placement; IEEE test system; loss minimization; multi-objective optimization; radial distribution network; voltage profile improvement
Corresponding author: Sayed Mir Shah Danish, Faculty of Engineering, University of the Ryukyus, 1 Senbaru Nishihara-cho, Nakagami, Okinawa, 903-0213, Japan, E-mail:

  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

Appendix

See Tables 5 and 6.

Table 5:

IEEE-34 bus test system data.

Line NoFrom busTo busR (Ω)X (Ω)P (kW)Q (kVAr)
1120.1170.048230142.5
2230.10730.04400
3340.16450.0457230142.5
4450.14950.0415230142.5
5560.14950.041500
6670.31440.05400
7780.20960.036230142.5
8890.31440.054230142.5
99100.20960.03600
1010110.1310.0225230142.5
1111120.10480.01813784
123130.15720.0277245
1313140.20960.0367245
1414150.10480.0187245
1515160.05240.00913.57.5
166170.17940.0498230142.5
1717180.16450.0457230142.5
1818190.20790.0473230142.5
1919200.1890.043230142.5
2020210.1890.043230142.5
2121220.2620.045230142.5
2222230.2620.045230142.5
2323240.31440.054230142.5
2424250.20960.036230142.5
2525260.1310.0225230142.5
2626270.10480.01813785
277280.15720.0277548
2828290.15720.0277548
2929300.15720.0277548
3010310.15720.0275734.5
3131320.20960.0365734.5
3232330.15720.0275734.5
3333340.10480.0185734.5
Table 6:

IEEE-118 bus test system data.

Line noFrom busTo busR (Ω)X (Ω)P (kW)Q (kVAr)
1120.0360.01,296133.84101.14
2230.0330.01,18816.21411.292
3240.0450.016234.31521.845
4450.0150.05473.01663.602
5560.0150.054144.268.604
6670.0150.0125104.4761.725
7780.0180.01428.54711.503
8890.0210.06387.5651.073
92100.1660.1344198.2106.77
1010110.1120.0789146.875.995
1111120.1870.31326.0418.687
1212130.1420.151252.123.22
1313140.180.118141.9117.5
1414150.150.04521.8728.79
1515160.160.1833.3726.45
1616170.1570.17132.4325.23
1711180.2180.28520.23411.906
1818190.1180.185156.9478.523
1919200.160.196546.29351.4
2020210.120.189180.31164.2
2121220.120.078993.16754.594
2222231.410.72385.1839.65
2323240.2930.1348168.195.178
2424250.1330.104125.11150.22
2525260.1780.13416.0324.62
2626270.1780.13426.0324.62
274280.0150.0296594.56522.62
2828290.0120.0276120.6259.117
2929300.120.2766102.3899.554
3030310.210.243513.4318.5
3131320.120.054475.25456.14
3232330.1780.234151.43136.79
3333340.1780.234205.3883.302
3434350.1540.162131.693.082
3535360.1870.261448.4369.79
3636370.1330.099440.52321.64
3737380.330.194112.5455.134
3838390.310.19453.96338.998
3939400.130.194393.05342.6
4040410.280.15326.74278.56
4141421.180.85536.26240.24
4242430.420.243676.24766.562
4329440.270.097253.5239.76
4444450.3390.122140.32831.964
4545460.270.177939.65320.758
4646470.210.138366.19542.361
4747480.120.078973.90451.653
4848490.150.0987114.7757.965
4949500.150.0987918.371205.1
5050510.240.1581210.3146.66
5151520.120.078966.6856.608
5229530.4050.145842.20740.184
5353540.4050.1458433.74283.41
5454550.3910.14162.126.86
5555560.4060.146192.4688.38
5656570.4060.146185.18855.436
5757580.7060.5461345.3332.4
5858590.3380.121822.516.83
5959600.3380.121880.55149.156
6030610.2070.074795.8690.758
6161620.2470.892262.9247.7
621630.0280.0418478.8463.74
6363640.1170.2016120.9452.006
6464650.2550.0918139.11100.34
6565660.210.0759391.78193.5
6666670.3830.13827.74126.713
6767680.5040.330352.81425.257
6868690.4060.146166.8938.713
6969700.9620.761467.5395.14
7070710.1650.06594.85239.74
7171720.3030.1092132.584.363
7272730.3030.109252.69922.482
7373740.2060.144869.79614.775
7474750.2330.08431.34929.817
7575760.5910.1773192.39122.43
7676770.1260.045365.7545.37
7764780.5590.3687238.15223.22
7878790.1860.1227294.55162.47
7979800.1860.1227485.57437.92
8080810.260.139243.53183.03
8181820.1540.148243.53183.03
8282830.230.128134.25119.29
8383840.2520.10622.7127.96
8484850.180.14849.51326.515
8579860.160.182383.78257.16
8686870.20.2349.6420.6
8787880.160.39322.47311.806
8865890.6690.241262.9342.96
8989900.2660.122730.6734.93
9090910.2660.122762.5366.79
9191920.2660.1227114.5781.748
9292930.2660.122781.29266.526
9393940.2330.11531.73315.96
9494950.4960.13833.3260.48
9591960.1960.18531.28224.85
9696970.1960.18507.03367.42
9797980.18660.12226.3911.7
9898990.07460.31845.9930.392
9911000.06250.0265100.6647.572
1001001010.15010.234456.48350.3
1011011020.13470.0888522.56449.29
1021021030.23070.1203408.43168.46
1031031040.4470.1608141.48134.25
1041041050.16320.0588104.4366.024
1051051060.330.09996.79383.647
1061061070.1560.0561493.92419.34
1071071080.38190.1374225.38135.88
1081081090.16260.0585509.21387.21
1091091100.38190.1374188.5173.46
1101101110.24450.0879918.03898.55
1111111120.20880.0753305.08215.37
1121001130.23010.082854.3840.97
1131131140.61020.2196211.14192.9
1141141150.18660.12767.00953.336
1151151160.37320.246162.0790.321
1161161170.4050.36748.78529.156
1171101180.4890.43833.918.98

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Received: 2019-09-09
Accepted: 2020-05-25
Published Online: 2020-07-04

© 2020 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/ijeeps-2019-0206
Keywords for this article
capacitor placement; IEEE test system; loss minimization; multi-objective optimization; radial distribution network; voltage profile improvement

Articles in the same Issue

  1. Review
  2. Power quality problem and key improvement technology for regional power grids
  3. Research Articles
  4. Machine learning roles in advancing the power network stability due to deployments of renewable energies and electric vehicles
  5. Analysis between graph-based and Power Transfer Distribution Factors (PTDF)-based model reduction methods in Electric Power Systems
  6. Experimental control of photovoltaic system using neuro – Kalman filter maximum power point tracking (MPPT) technique
  7. Data compression techniques for Phasor Measurement Unit (PMU) applications in smart transmission grid
  8. Influence of inter-turn short circuit on the performance of 10 kV, 1000 kW induction motor
  9. Detection of coherent groups using measured signals, in an inter-area mode, for creating controlled islands to protect the power system from blackout
  10. Multi-objective optimization of optimal capacitor allocation in radial distribution systems
  11. A novel approach of closeness centrality measure for voltage stability analysis in an electric power grid
  12. Dynamic Simulation of Eastern Regional Grid of India using Power System Simulator for Engineering PSS®E
  13. Optimal total harmonic distortion minimization in multilevel inverter using improved whale optimization algorithm
  14. A cost effective accumulator management system for electric vehicles
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