ARTIFICIAL BEE COLONY ALGORITHM BASED APPROACH FOR CAPACITOR ALLOCATION IN UN

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ARTIFICIAL BEE COLONY ALGORITHM BASED APPROACH FOR CAPACITOR ALLOCATION IN UN Powered By Docstoc
					INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING &
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME
                             TECHNOLOGY (IJEET)

ISSN 0976 – 6545(Print)
ISSN 0976 – 6553(Online)
                                                                                IJEET
Volume 4, Issue 4, July-August (2013), pp. 67-73
© IAEME: www.iaeme.com/ijeet.asp                                             ©IAEME
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    ARTIFICIAL BEE COLONY ALGORITHM BASED APPROACH FOR
  CAPACITOR ALLOCATION IN UNBALANCED RADIAL DISTRIBUTION
                          SYSTEMS

        Dr.K.Ravichandrudu1, G.Jyothi 2, Mr.P.Yohan Babu3, Mr.G.V.P.Anjaneyulu4
        1,2,3
                Krishnaveni Engineering College For Women, Narasaraopet, Guntur, AP, India.
                    4
                      Reaserch scholar SVU College of engineering, S.V.U., Tirupathi.



ABSTRACT

        This paper presents an artificial bee colony method for optimal sizing of capacitors at optimal
locations in unbalanced radial distribution systems. The objective function formulated includes the
energy cost, capacitor installation cost and purchase cost. So that the fitness function is to maximize
the net saving. Most conventional optimization techniques are in capable to solve this hard
combinatorial problem with set of operating conditions where as artificial bee colony (ABC)
algorithm is very suitable. This method is executed on a typical 25-bus and 37-bus unbalanced radial
distribution systems (URDS) and yields efficiency in reduction of power losses and improvement of
net saving.

Keywords: Power Loss Indices, Capacitor banks, Loss Minimization, Unbalanced Radial
Distribution Systems, Artificial Bee Colony method, Net saving.

1.     INTRODUCTION

       As the cost of new power plant construction has increased, the electric power industry is
making every effort to reduce the growth of electricity demand. Since a substantial amount of
generated power is being wasted as losses, reduction in losses has been recognized as a viable option
to eliminate to some degree the need for unnecessary additional generating capacity. It is
acknowledged that much of this power loss occurs in the distribution system. In past, a lot of work
has been carried out in the area of reactive power compensation for distribution networks [1-3].
       Voltage improvement and power loss reduction by capacitor placement is analyzed in [4].
Sundhararajan and Pahwa et al. used genetic algorithm for obtaining the optimum values of shunt
capacitors in [5]. They have treated the capacitors as constant reactive power load at that particular
bus. T.S. Abdul salma et al. proposed a heuristic technique, which brings about the identification of
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International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME

the sensitive buses that have a very large impact on reducing the losses in the distribution systems
[6]. C.S. Chen et al. developed a systematic method of optimally locating and sizing of the shunt
capacitors compensation on distribution feeders by taking into account the mutual coupling effect
among phase conductors [7]. The capacitor placement and sizing problem is a nonlinear integer
optimization problem, with locations and ratings of shunt capacitors being discrete values. Particle
swarm optimization based approach for capacitor placement for loss reduction is analyzed in [8].
        In this paper the artificial bee colony method is proposed for finding optimal size of capacitor
in unbalanced radial distribution system for improving the net saving which is formulated as the
difference between the energy saving obtained by loss reduction and the cost of capacitor
installation, purchase and operation.

2.       PROBLEM FORMULATION

       The objective function formulated includes the energy cost, capacitor installation cost and
purchase cost, so that the fitness function is to be maximized for the net savings function (F) by
placing the optimal size of the capacitor. The objective function can be expressed as:

                         
                                n abc        n
                                                   abc'                       nc
                                                                                          
                 F = Max  EC ×  ∑ Ploss j − ∑ Ploss j  × T − a ×  IC × nc + ∑ CC × CB       (1)
                         
                                j =1        j =1                            j =1      
Where,
         EC is energy Cost in Rs/kWh; T is time Period in hours; n is number of buses
           abc
         Ploss j is the total active power loss before capacitor placement
             '
          abc
        Ploss j is the total active power loss after capacitor placement
       a is the depreciation factor ; IC is the installation cost;
       nc is the number of capacitor locations ; CC is the cost of the three phase capacitor
       CB is the capacitor bank rating in kVAr.
Subjected to inequality constraints are
       i)           0 ≤ CB ≤ CBmax Where CBmax = 20% of Qload
       ii)         The bus voltage magnitudes are to be kept within acceptable operating limits
                   throughout the optimization process. That is ± 5% of the nominal voltage value.
                                                      sys     sys    sys
                                                   Vmax ≥ Vi      ≥ Vmin

3.       ILLUSTRATION OF LOCATION OF CAPACITORS

        The candidate bus identification method for capacitor placement is explained with 37 bus
URDS .The line and the load data of this system is given in [9]. After performing the base case load
flows, total active power loss of system is 85.6746 kW. After compensating the reactive power
injection at each bus in all the phases equal to local reactive load of the system at that particular bus,
perform the load flows as explained in [7] and record the total active power loss and loss reduction of
the system. This procedure is repeated for all remaining buses except source bus.
        The power loss indices (PLI) are calculated as


                             PLI [i ] =
                                          ( Loss reduction [i ] − Min. reduction )                (2)
                                           ( Max. reduction − Min. reduction )


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International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
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                                      Power Loss Indices (PLI)
                 1.2
                  1
                 0.8
                 0.6
                 0.4
                 0.2
                  0
                       0            10              20              30              40

                                              Bus number
            Fig. 1: Power loss indices of 37 bus unbalanced radial distribution system

        The most suitable buses for the capacitor placement are chosen based on the condition that
PLI must be greater than PLI tolerance value, it should be lies in between ‘0’ and ‘1’. The tolerance
value for a chosen system is selected by experimenting with different values in descending order of
the PLI limits. The best value of the tolerance value gives the highest profit and satisfies the system
constraints. Fig.1 shows power loss index vs bus number for 37 bus URDS. From experimentation
the best value of PLI tolerance is set as 0.6. It is concluded that buses 2, 10, 11, 33, 37 are the best
candidate buses for the capacitor placement. Assume capacitor at candidate buses with size varying
the integer steps of the standard size capacitors (50 kVAr per phase).

4.     ARTIFICIAL BEE COLONY METHOD

         Artificial Bee Colony (ABC) is one of the most recently defined method by Dervis Karaboga
in 2005, motivated by the intelligent behavior of honeybees. ABC as an optimization tool provides a
population based search procedure in which individuals called food positions are modified by the
artificial bees with time and the bee’s aim is to discover the places of food sources with high nectar
amount and finally the one with the highest nectar. In this method [10], [11], the colony of artificial
bees consists of three groups of bees: employed bees, onlookers and scouts. First half of the colony
consists of the employed artificial bees and the second half includes the onlookers. For every food
source, there is only one employed bee. In other words, the number of employed bees is equal to the
number of food sources around the hive. The employed bee whose food source has been abandoned
becomes a scout [12]. Thus, ABC system combines local search carried out by employed and
onlooker bees, and global search managed by onlookers and scouts, attempting to balance
exploration and exploitation process [13]. This ABC method is used for finding optimal size of
capacitors at optimal locations.

5.     RESULTS AND ANALYSIS

        To check the validity of the proposed ABC method, 25 bus and 37 bus unbalanced radial
distribution systems have been considered. In addition, the results of these systems were compared
with those obtained via existing PSO method [8]. The proposed ABC method results were obtained
after carrying out 100 independent runs.
        Energy saving cost has been calculated as the difference of energy loss cost without capacitor
and with capacitor. The net saving has been calculated as the difference of energy saving cost and the
capacitor installation and purchase cost. The rate of energy loss cost has been considered as Rs. 3 per

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International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME

kWh, depreciation factor is 0.2, installation cost Rs. 50,000 and the cost of the three phase capacitor
is Rs. 200 for the cost benefit analysis [14]. The Control parameters of existing and proposed
methods of both test systems are given in Table 1.
      Table 1: Control parameters of existing and proposed methods for both test systems

                          Existing method [8]                          Proposed method
        Number of generations=100; Population size=20                   MaxCycle=100
           Wmax=0.9; Wmin=0.2 ; c1 = 2; c2 = 2                          Colony size=40

1)       Example: 1
         The 37 bus unbalanced radial distribution system is considered as first example for testing the
efficacy of proposed method. In order to study the effect of capacitor placement at multiple
locations, an attempt was made to place capacitor at more than one location. The locations of
capacitor placement is obtained as discussed in section 3 i.e., candidate buses for the placement of
capacitors. The optimal sizes of capacitors are obtained by proposed and existing optimization
methods. Summary of test results of 37 bus unbalanced radial distribution system is given in Table 2.
The net saving obtained by existing and proposed methods are Rs. 3,09,007 and Rs. 3,15,304 for the
total size of capacitor of 300 kVAr and 250 kVAr respectively.
         From Table 2, it is observed that the minimum voltages in phases A, B and C are improved
from 0.9497, 0.9578 and 0.9445 p.u to 0.9622, 0.9712 and 0.9598 p.u by existing method, 0.9625,
0.9718 and 0.9601 p.u by proposed method respectively. Also observed that the active power loss in
phases of A, B and C is reduced from 31.56, 23.67 and 30.44 kW to 25.47, 20.41 and 24.99 kW by
existing method and 25.23, 20.36 and 24.81 kW by proposed method respectively.The reactive
power loss in phases A, B and C is reduced from 24.01, 22.32 and 29.19 kVAr to 20.41, 18.83 and
24.65 kVAr by existing method and 20.21, 18.78 and 24.49 kVAr by proposed method respectively.
From table 2 it is also observed that the total active and reactive power demand of test system is
reduced by placing capacitors at optimal locations by proposed method than existing method.
2)       Example: 2
         The 25 bus unbalanced radial distribution system is considered as second example for testing
the efficacy of proposed method. The line and load data of this test is taken from [14]. The selection
of locations for capacitors is same as second example. For this test system 0.4 is taken as PLI
tolerance which is selected by experimentation. The PLI values for 25 bus unbalanced radial
distribution system is shown in Fig. 2. From this Fig. 2, the buses 9, 12, 14 and 15 are selected as
optimal locations.

                1.2                     Power loss indices (PLI)
                 1
                0.8
                0.6
                0.4
                0.2
                 0
                      0          5         10       15         20         25         30
                                                Bus number
            Fig. 2: Power loss indices of 25 bus unbalanced radial distribution system

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International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
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        Summary of test results of 25 bus unbalanced radial distribution system is given in Table 3.
The net saving obtained by existing and proposed methods are Rs. 10,87,405 and Rs. 11,00,689 for
the total size of capacitor of 450 kVAr and 500 kVAr respectively. From Table 3, it is observed that
the minimum voltages in phases A, B and C are improved from 0.9284, 0.9284 and 0.9366 p.u to
0.9545, 0.9522 and 0.9611 p.u by existing method, 0.9567, 0.9542 and 0.9631 p.u by proposed
method respectively. Also observed that the active power loss in phases of A, B and C is reduced
from 52.82, 55.44 and 41.86 kW to 37.58, 39.22 and 29.51 kW by existing method and 37.34, 38.92
and 29.32 kW by proposed method respectively. The reactive power loss in phases A, B and C is
reduced from 58.32, 53.29 and 55.69 kVAr to 41.56, 38.05 and 39.77 kVAr by existing method and
41.36, 37.58 and 39.23 kVAr by proposed method respectively.

         Table 2: Summary of test results of 37 bus unbalanced radial distribution system
                               Before capacitor placement             Existing method [8]                 Proposed method
        Description
                               Phase    Phase
                                                  Phase C   Phase A        Phase B    Phase C    Phase A      Phase B   Phase C
                                A         B
                          2                                      0            0             0      50           50           50
    Size of the           10                                     0            0             0      50           50           50
   Capacitor(Qc
                          11                                 100             100        100        50           50           50
     in kVAr)                   ---       ---       ---
    with node             33                                 100             100        100       100          100          100
      number
                          37                                     50           50            50     50           50           50

     Minimum voltage           0.9497   0.9578    0.9445    0.9622          0.9712     0.9598    0.9625       0.9718    0.9601

   Max. Volt. regulation       0.0503   0.0422    0.0555    0.0378          0.0288     0.0402    0.0375       0.0282    0.0399
   Improvement of max.
                                ---       ---       ---     24.8509        31.7535    27.5676    25.4473      33.1754   28.1081
   Voltage regulation (%)

                      Best                                                 309007                             315304
      Net
                                          ---
  saving(Rs.)       Worst                                                  222161                             248654
                   Average                                                 307764                             309321
   Total active power loss
                               31.56    23.67      30.44     25.47          20.41       24.99     25.23        20.36        24.81
            (kW)
   Total active power loss
                                ---       ---       ---      19.32          13.77       17.89     20.05        13.99        18.49
       reduction (%)
  Total reactive power loss
                               24.01    22.31      29.20     20.41          18.83       24.65     20.21        18.78        24.49
           (kVAr)

  Total reactive power loss
                                ---       ---       ---      15.02          15.62       15.56     15.86        15.84        16.10
        reduction (%)
     Total active Power
                               885.56   789.67    1163.44   879.47          786.41    1157.99    879.23       786.36    1157.81
       demand(kW)
    Total reactive Power
                               442.01   397.31    580.19    438.40          393.83     575.65    438.21       393.78    575.49
      demand(kVAr)
   Total Feeder Demand
                               989.75   883.99    1300.09   982.68          879.51    1293.19    982.38       879.44    1292.95
          (kVA)
  Released feeder capacity
                                ---       ---       ---      7.07            4.48       6.90      7.36         4.55         7.13
          (kVA)




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International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
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           Table 3: Summary of test results of 25 bus unbalanced radial distribution system
                                 Before capacitor placement           Existing method [8]              Proposed method
           Description          Phase
                                          Phase B Phase C      Phase A     Phase B    Phase C   Phase A   Phase B   Phase C
                                  A
                         9                                         150       150        150      150        150          150
      Size of the
     Capacitor (Qc       12                                        100       100        100      100        100          100
       in kVAr)          14       ---       ---       ---           0         0          0       150        150          150
      with node
        number           15                                        200       200        200      100        100          100

       Minimum voltage          0.9284    0.9284    0.9366     0.9545       0.9522     0.9611   0.9567     0.9542    0.9631
  Max. Volt. Regulation (%)      7.16      7.16      6.34       4.55         4.78       3.89     4.33       4.58      3.69
Improvement of max. Voltage
                                  ---       ---       ---      36.4525     33.2402    38.6435   39.5251   36.0335   41.7981
        regulation (%)
                       Best                                              1087405.2260                  1100689.5266
      Net
                      Worst                 ---                          1059162.1232                  1093939.6864
  saving(Rs.)
                     Average                                             1086473.9888                  1099873.1927
 Total active power loss (kW)    52.82     55.44     41.86         37.58    39.22     29.51      37.34    38.92     29.32
   Total active power loss
                                  ---       ---       ---          28.85    29.26      29.50     29.31      29.80    29.96
         reduction (%)
  Total reactive power loss
                                 58.32     53.29     55.69         41.86    38.05      39.77     41.36      37.58    39.23
            (kVAr)
  Total reactive power loss
                                  ---       ---       ---          28.22    28.60      28.59     29.08      29.48    29.56
         reduction (%)
      Total active Power
                                1126.12   1138.74   1125.16    1110.88     1122.52    1112.81   1110.64   1122.22   1112.62
         demand(kW)
     Total reactive Power
                                850.32    854.29    855.69     833.86       839.05     839.77   833.36     838.58    839.23
        demand(kVAr)
    Total Feeder Demand
                                1411.09   1423.57   1413.57    1389.02     1401.45    1394.12   1388.53   1400.93   1393.64
             (kVA)
   Released feeder capacity
                                  ---       ---       ---          22.07    22.12      19.45     22.56      22.64    19.93
             (kVA)


6.         CONCLUSION

        The proposed ABC method successfully achieved the optimal solutions. The results of the
proposed method were compared with existing method for capacitor placement at multiple locations.
The proposed method shows that the sizes of capacitors at optimal locations improve the net saving
significantly than the sizes of capacitor obtained by existing method. The real and reactive power
demand effect is reduced on total system due to capacitors placement. The minimum voltage is also
improved by proposed method than existing method.

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International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
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