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Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

Postal Subscription Code 80-972

2018 Impact Factor: 1.701

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Front. Energy    2014, Vol. 8 Issue (4) : 434-442    https://doi.org/10.1007/s11708-014-0313-y
RESEARCH ARTICLE
Power system reconfiguration and loss minimization for a distribution systems using “Catfish PSO” algorithm
K Sathish KUMAR(),S NAVEEN
School of Electrical Engineering, VIT University, Vellore 632014, India
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Abstract

One of the very important ways to save electrical energy in the distribution system is network reconfiguration for loss reduction. Distribution networks are built as interconnected mesh networks; however, they are arranged to be radial in operation. The distribution feeder reconfiguration is to find a radial operating structure that optimizes network performance while satisfying operating constraints. The change in network configuration is performed by opening sectionalizing (normally closed) and closing tie (normally opened) switches of the network. These switches are changed in such a way that the radial structure of networks is maintained, all of the loads are energized, power loss is reduced, power quality is enhanced, and system security is increased. Distribution feeder reconfiguration is a complex nonlinear combinatorial problem since the status of the switches is non-differentiable. This paper proposes a new evolutionary algorithm (EA) for solving the distribution feeder reconfiguration (DFR) problem for a 33-bus and a 16-bus sample network, which effectively ensures the loss minimization.
Keywords distribution system reconfiguration (DFR)      power loss reduction      catfish particle swarm optimization (catfish PSO)      radial structure     
Corresponding Author(s): K Sathish KUMAR   
Just Accepted Date: 11 August 2014   Online First Date: 25 September 2014    Issue Date: 09 January 2015
 Cite this article:   
K Sathish KUMAR,S NAVEEN. Power system reconfiguration and loss minimization for a distribution systems using “Catfish PSO” algorithm[J]. Front. Energy, 2014, 8(4): 434-442.
 URL:  
https://academic.hep.com.cn/fie/EN/10.1007/s11708-014-0313-y
https://academic.hep.com.cn/fie/EN/Y2014/V8/I4/434
Fig.1  Catfish PSO process

(a) gbest trapped in local optima; (b) worst 10% particles-W being removed; (c) introduction of catfish particles ‘C’ in swarm; (d) catfish-particle finding a better solution; (e) catfish particle guiding the whole swarm to a promising new region; (f) particles

SL No. Frombus (i) To bus(i+1) R(i, j+1)/? X(i, j+1)/? P/kW Q/kvar
1 0 1 0.0922 0.0477 100 60
2 1 2 0.493 0.2511 90 40
3 2 3 0.366 0.1864 120 80
4 3 4 0.3811 0.1941 60 30
5 4 5 0.819 0.707 60 20
6 5 6 0.1872 0.6188 200 100
7 6 7 1.7114 1.2351 200 100
8 7 8 1.03 0.74 60 20
9 8 9 1.04 0.74 60 20
10 9 10 0.1966 0.065 45 20
11 10 11 0.3744 0.1238 60 35
12 11 12 1.468 1.155 60 35
13 12 13 0.5416 0.7219 120 80
14 13 14 0.591 0.526 60 10
15 14 15 0.7463 0.545 60 20
16 15 16 1.289 1.721 60 20
17 16 17 0.732 0.574 90 40
18 1 18 0.164 0.1565 90 40
19 18 19 1.5042 1.3554 90 40
20 19 20 0.4095 0.4784 90 40
21 20 21 0.7089 0.9373 90 40
22 2 22 0.4512 0.3083 90 50
23 22 23 0.898 0.7091 420 200
24 23 24 0.896 0.7011 420 200
25 5 25 0.203 0.1034 60 25
26 25 26 0.2842 0.1447 60 25
27 26 27 1.059 0.9337 60 20
28 27 28 0.8042 0.7006 120 70
29 28 29 0.5075 0.2585 200 600
30 29 30 0.9744 0.963 150 70
31 30 31 0.3105 0.3619 210 100
32 31 32 0.341 0.5302 60 40
33 20 7 2.000 2.000 – –
34 8 13 2.000 2.000 – –
35 11 21 2.000 2.000 – –
36 17 32 0.500 0.500 – –
37 24 28 0.500 0.500 – –
Tab.1  Line data for 33-bus test system
Fig.2  33-bus radial distribution system
From To Resistance/? Reactance/? P/MW Q/Mvar
1 4 0.075 0.1 2.0 1.6
4 5 0.08 0.11 3.0 1.5
4 6 0.09 0.18 2.0 0.8
6 7 0.04 0.04 1.5 1.2
2 8 0.11 0.11 4.0 2.7
8 9 0.08 0.11 5.0 3.0
8 10 0.11 0.11 1.0 0.9
9 11 0.11 0.11 0.6 0.1
9 12 0.08 0.11 4.5 2.0
3 13 0.11 0.11 1.0 0.9
13 14 0.09 0.12 1.0 0.7
13 15 0.08 0.11 1.0 0.9
15 16 0.04 0.04 2.1 1.0
5 11 0.04 0.04 – –
10 14 0.04 0.04 – –
7 16 0.09 0.12 –
Tab.2  Line data for 16-bus test system
Fig.3  16-bus radial distribution system
Switch status Power loss/kW
Closed Open
1,2,3,4,5,6,8,10,11,12,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,33,34,35,36 7, 9,14,32,37 144.9971
1,2,3,4,5,6,8,9,10,12,15,16,17,18,19,20,21,22,23,24,25,26,27,29,30,31,33,34,35,36,37 7, 11, 14,28,32 131.2282
1,2,3,4,5,6,8,9,11,12,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,33,34,35,36 7, 10,14,32,37 147.8499
1,2,3,4,5,7,6,8,9,10,12,15,16,17,18,19,20,21,22,23,24,25,26,27,29,30,32,33,35,36,37 11,14,28,31,34 158.7181
1,2,3,4,5,7,8,9,10,12,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,32,33,34,35,36 6, 11,14,31,37 152.4523
Tab.3  Power loss results using catfish PSO with various switch statuses on 33-bus test system
Switch status Power loss/kW
Closed Open
1,2,3,4,6,8,10,11,14,12,13,15 5, 7,16 475.66
1,2,3,6,7,8,10, 12,13,14,15,16 5, 4, 11 445.14
1,2,3,6,8,10,11,12,13,14,15,16 5, 7,4, 468.11
Tab.4  Power loss results using catfish PSO with various switch statuses on 16-bus test system
Methods Switches open Power loss/kW
Proposed method 7,11,14,28,32 131.2282
BFOA [6] 7, 9,13,14,32 135.78
Shirmohammadi et al. [3] 7, 10,14,32,37 141.54
Refined genetic algorithm (Zhu [4] ) 7, 9,14,32,37 139.55
ACS & GA [18] 7, 9,14,28,32 137.00
Martín and Gil [19] 7, 9,14,32,37 139.55
AG-Algorithm [20] 7, 9,14,32,37 139.55
Gomes et al. [2] 7, 9,14,32,37 136.57
Goswami and Basu [21] 7, 9,14,32,37 136.57
Bouhouras. [7] 7, 9,14,32,37 136.57
Gomes et al. [8] 7, 10,14,32,37 136.66
Tab.5  Comparison with other methods using 33-bus network (Loss in base configuration is 202.71 kW)
Methods Switches open Power loss/kW
Proposed method 5,4,11 445.14
(Refined genetic algorithm) (Zhu [4] ) 6,9,11 466.11
ACSA [22] 6,9,11 466.11
Tab.6  Comparison with other methods using 16-bus network (Loss in base configuration is 511.41 kW)
Fig.4  Convergence characteristics of power loss in 33-bus test system with 30 iterations
Fig.5  Convergence characteristics of power loss in 33-bus test system with 25 iterations
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