Network Performance during Network Reconfiguration - IEEE Xplore

First International Power and Energy Coference PECon 2006 November 28-29, 2006, Putrajaya, Malaysia

566

Influence of Distributed Generation on Distribution Network Performance during Network Reconfiguration for Service Restoration Zuhaila Mat Yasin, Titik Khawa Abdul Rahman, IEEE Member Abstract - The effect of location and sizing of distributed generation to the power losses and voltage profile during network reconfiguration for service restoration are investigated in this paper. The location of the distributed generation was identified using the pre-determined sensitivity indices, while Evolutionary Programming was used to determine the size of the installed distributed generations. The simulation was conducted by applying three phase fault at an identified location. After the fault is isolated, the network is reconfigured by changing the open/closed states of the tie lines and sectionalising switches for service restoration while minimising the total power losses in the network. Network reconfiguration was implemented using the TOPO application in the power system simulation programme for planning, design and analysis of distribution system (PSS/Adept). The simulation was conducted on the 69-bus distribution system.

Index terms - distributed generation, network reconfiguration, service restoration

I. INTRODUCTION The introduction of generating sources into the distribution system can significantly impact the operating state and dynamics of both the transmission and distribution system. The impacts could be positive or negative depending on the system operating condition, distributed generation characteristic, location and sizing. A proper placement plays a very important role since power flows at the interface substations and throughout the network depend on the geographic distribution of all generation sources with respect to demand irrespective of the voltage at the connection point [1], [2]. Many approaches have been proposed to solve the problem of determining optimal location and sizing of distributed generation (DG) in order to obtain the maximum benefit of DG. References [3] to [5] present the method to identify the optimal location and sizing of DG in order to minimise the total distribution losses and improve voltage profile in the system. Network Reconfiguration of a power distribution system is an operation to alter the topological structure of distribution feeders by changing open/closed status of sectionalising and tie switches. During normal operating condition, networks are reconfigured to reduce the system real power losses and to relieve overloads in the network (load balancing). Another configuration management operation involves the restoration of service to as many customers as possible during a restorative state following a fault [6]. Reference [6] to [9] presents different technique in determining optimal configuration during normal operating condition. Whereas, reference [10] presents a heuristic method to restore service to the isolated portions of a distribution system during fault condition.

1-4244-0273-5/06/$20.00 C2006 IEEE

Reference [11] shows that inclusion of distributed generation in a distribution system would reduce the system losses and hence improves system voltage further when the network is reconfigured. However, the location and sizing of the distributed generation were not optimally selected since it was assumed that the owners of distributed generation units determine the installation location and their capacity to improve their economic benefits. This paper studies the influence of location and capacity sizing of distributed generation (DG) during network reconfiguration in the fault condition. The optimal sectionalizing - tie switch pairs were determined by the TOPO application available in the power system simulation programme for planning, design and analysis of distribution system (PSS/Adept). This application determines optimal sectionalizing - tie switch pairs based on minimum losses configuration and at the same time, all nodes are assured for the supply. The suitable location for distributed generator was determined using the pre-developed sensitivity indices derived from voltage stability index variation with respect to changes in injected active and reactive power at a bus. The optimal capacity sizing of the distributed generation was determined using the Evolutionary Programming (EP) optimisation technique. Various locations and sizes of DGs were also tested in order to realise the effect of location and sizing of DGs in terms of loss minimisation and voltage improvement during network reconfiguration for service restoration. These results were compared with those obtained when the DG was located at the location identified and optimally sized using the technique developed in reference [3]. The study was implemented on the 69-bus distribution system.

II. OPTIMAL LOCATION OF DISTRIBUTED GENERATION In order to obtain maximum benefit from the distributed generator, suitable location and sizing has to be determined before its installation. The technique developed in reference [3] identifies the suitable location for the distributed generator by studying the pre-developed voltage stability index [12] variations with respect to changes in reactive and active power injections at a bus. Two sensitivity indices were derived based on voltage stability index formulation. These sensitivity indices relate the changes in the voltage stability index with respect to changes in injected active and reactive power at a load bus. The sensitivity indices were computed for every load bus and those buses with highest sensitivity values were chosen for the distributed generation placement. The derivation of the sensitivity indices from the voltage stability index formulated in reference [3] is as follows:-

567 The voltage stability index at a load bus i is given by [12] Li

=

4[Voi

2

-vi

COSVLo si

VL

=

VO

=

2

2

] / Voi .................(1)

load voltage at bus i no load voltage at bus i

(Ooi

0i

COS 01

Li

)

Xi=Pg

load angle at bus i = no load angle at bus i

00i

aLi

aP,

a VL,

_x

i

aV

iLx aOLi

+

aP,

.(2)

'

aPi

Hence, the second sensitivity index

derived

was

from the change in L with respect to the change in injected Q at bus i is given by aL,

au1L

aQi

a VLi

a

VLii

O0L

DL, x

i

(Qi

+

i

(3)

e0Li aQi

Expressing equations 2 and 3 into matrix form gives a aLl

OP.

aVL,

L

aiL

0OL

1

aPi a

aL:L

:Qi

aQi

L] OOL'0

VL evai

(4)

VL,

.Q

(5)

L,

The elements of the row matrices in equations (4) derived from equation (1) as follows,

are

aLl eaVLi

Li aVL

i

U2 voi aOL,

Li

[

4

7

V02

....

(6)

Vi VL, sin Oi + 2V/ cos aVL,

aQi e Qi aQi

and

Li

aQi

Cos s

=

0.85, where (/ is power factor angle

The operation of the distributed generator is considered to be at steady state and therefore, the distributed generator is modelled as injected active and reactive power, Pg and Qg respectively. The objective of the optimisation is to minimise the network losses denoted by equation (13). Hence, the fitness for the EP was taken to be the total losses in the distribution system and evaluated by executing the load flow programme with the injected active and reactive power at the suitable location determined from the sensitivity analysis. The optimisation also took into consideration the voltage constraint of the system as shown in equation (14), so as to ensure that the maximum and minimum voltages would not be exceeded. n

MinimiseZ Pioss

..........

(13)

n = number of lines in the system Voltage constraints, Vimin < Vi < V .ma

(14)

-

aQi and (5)

(11)

j=1

VL,

00 L -

...........

Qg = Pg x tan -l 5 ........... (12)

The first sensitivity index was formulated from the change in L, with respect to the change in injected P, at bus i is given by aL,

III. OPTIMAL SIZING OF DISTRIBUTED GENERATION The optimal size of the distributed generator is determined by having the kW output (Pg) of the distributed generator as the variable to be optimised in the EP optimisation technique [3]. The kVar output of the distributed generator was determined using equation (12) and the power factor of the system is set to be 0.85.

are obtained

sin Oi ].....(7)

from the

inverse of loadflow jacobian matrix.

The sensitivity criterion was determined from the values of the sensitivity indices evaluated at each load bus in a system. Buses with highest sensitivity values are selected for the location of the distributed generators.

IV. METHODOLOGY The location and sizing of the distributed generation (DG) were identified using the techniques described in section II and III. The DG was represented as negative load and network reconfiguration was implemented for service restoration and loss minimisation. Several fault locations were pre-identified and the faults were isolated. The corresponding tie-line switch was closed in order to maintain the radial configuration before the network is reconfigured. The simulation was executed using a commercial load flow program called PSS/Adept. PSS/Adept or Power System Simulator and Advanced Distribution Engineering Productivity Tool, is a network simulation program for planning, designing and analyzing distribution system. PSS/Adept utilizes the Gauss-Seidel method for the solving load flow equations. In PSS/Adept, Tie Open Point Optimisation (TOPO) is used to determine the network configuration with lowest real power loss. TOPO algorithm uses a heuristic method based on optimum power flow. Starting with the initial radial system, TOPO closes one of the controllable switches to form a loop. An optimum power flow procedures is then done on the loop to determine the best switch to open to change the network back to radial. The process continues until the switch that is opened is always the one that was closed at which time TOPO has finished.

568 The resulting network is the radial network with minimum real power loss. V. RESULTS A 69-bus radial distribution system is used in all simulation tests. The one-line diagram of the 69-bus test system is shown in figure 1. The tie line switches in the network are located as tabulated in Table 1. Various location of fault are simulated and studied for assessing the benefit of distributed generation (DG) to the voltage profile improvement and real power loss reduction in the event of fault. For each location, the fault is assumed to be isolated. 28 29 30 31

30r

3 38

37

47

32 33 34

40 41

35

50

49

51

6

52

"

58

2 63 64 65

51 58 59 6 0 61

Figure 1: A 69-bus test system TABLE 1 TIE LINE SWITCHES CONNECTION

switch connection

s1 8-43

2 16-46

s3 12-21

4 50-59

s5 27-65

TABLE 2 THE FIRST 5 BUSES WITH HIGHEST SENSITIVITY INDEX VALUE

Bus No.

aLi

61 64 21 65 59

api 26.3958 7.7781 3.8323 2.5544 2.396

0.6

optimal output of DG at each bus location (MW) 64 21 61 59 65 0.4527 1.1009 0.9632 1.1464 0.8369

0.8

1.4699

1.2896

1.5340

1.1228

0.6125

1.0

1.8401

1.6181

1.9273

1.4148

0.7783

1.2

2.2091

1.9487

2.3245

1.7090

0.9475

1.4

2.5799

2.2823

2.7238

2.0074

1.1266

Loading

(p.u)

In order to study the effect of distributed generation (DG) to the system losses and voltage profile in the event of fault, various fault location were selected. The fault location selected including the fault near to the main source, fault near to the load and fault near to the DG. The selected fault buses are as follows: (a) bus 6 (near to the main source) (b) bus 10 (near to the load) (c) bus 20 (near to the DG) (d) bus 40 (near to the load) (e) bus 62 (near to the DG)

42 43 44 45 46

.

48

TABLE 3: OPTIMAL DG OUTPUT FOR LOSS MINIMISATION IN THE SYSTEM FOR OVERALL LOAD INCREASE IN THE SYSTEM.

Bus No

aLi

aQi 61 64 50 49 21

The fault was applied to the network individually with different location of distributed generation. The minimum losses and minimum voltage were identified after the network is reconfigured by closing/opening the corresponding tie-line and sectionalizing switches for service restoration. The graph in figure 2, 3, 4, 5 and figure 6 illustrates the variation of losses in the system as a result of installing distributed generation (DG) at the respective buses with fault occur at bus 6, 10, 20, 40 and 62 respectively. Each graph shows the comparison of the existing network (considering only tie line switches), the reconfigured network without DG and the reconfigured network with DG at bus 21, 59, 61, 64 and 65 (considering both tie line and sectionalizing switches).

10.2167 2.8583 1.2550 1.0333 1.0086

450

350 U,

From table 2, it could be observed that bus 61 has the highest sensitivity index value and therefore it is chosen as the suitable location for distributed generator. However, for comparison, buses 64, 21, 65 and 59 were also selected for distributed generator allocation so that the improvement on the network performance in terms of loss minimisation and voltage profile improvement under fault condition could be analyzed. The results for each case are to be compared with the existing network and the reconfigured network without distributed generation. The optimal output of the distributed generation (DG) in order to minimise the system losses identified by the proposed EP optimisation technique is tabulated in Table 3. This table provides the optimal output of DG for various loading condition.

existing network

400

0

300 250

w ithout DG

DG at bus 21 DG at bus 59 )K DG at bus 61 DG at bus 64 DG at bus 65

2000

n

m

150

100_ 50 0.60

0.80

1.00

1.20

1.40

loading

Figure 2: Total power losses when fault increase in the system

occur

at bus 6 for overall load

569 600R-

existing netw ork ithout DG DG at bus 21 DG at bus 59

500

-*--DG at bus

400 40-

existing netw ork

400

w

350 X350

61

w ithout DG

DG at bus 21

-

DG at bus 59

DG at bus 64

DG at bus 64

0

DG at bus 65 0 250 -J/

DG at bus 65 300-

200

0

150

200

100

0

100

50-

0

0

0.60

0.80

1.00

1.20

0.60

1.40

0.80

1.00

3:

increase in

Total

power losses when fault

occur

at bus

10 for overall load

the system

X400 o

-* 3

Figure

6:

Total power losses when fault the system

occur

at bus

62

for overall load

increase in

At all fault location selected above, the results shows that the reconfigured network were reduced the total losses as compared to the existing network. However, the reconfigured network with DG at bus 61 produced the minimum total losses. Figure 7, 8, 9, 10 and figure 11 illustrate the results for minimum voltage when fault occur at bus 6, 10, 20, 40 and 62 respectively.

600

500

1.40

loading

loading

Figure

1.20

existing netw ork w ithout DG DG at bus 21 DG at bus 59 DG at bus 61 DG at bus 64 00at bus 65 DG

300

1.000

200

0.980

100 0.960 0

0

0.60

0.80

1.00

1.20

1.40

m

loading

Figure 4: Total power losses when fault increase in the system

occur

m 0.940 -.

at bus 20 for overall load

>

0.920 0.900

0.880 0.860

300 existing

+ 250

w

netw

ork

without DG

DG at bus DG at bus -K-DG at bus DG at bus DG at bus

21 59

61

64 65

0.840

ithout DG

DG at bus

+ Eidsting network

21

0.60

0.80

DG at bus 59

nU,

200

)K

0

t

DG at bus

1.00

1.20

1.40

Loading

61

DG at bus 64 DG at bus 65

Figure 7: Minimum voltage when fault increase in the system

150

occur

at bus 6 for overall load

0

-

1.000

100

50

Y...-

/

0.980 50

0.960 3

0.60

0.80

1.00

1.20

1.40

loading

Figure 5: Total power losses when fault increase in the system

occur

at bus 40 for overall load

0.940

0)

c

0.920

-

0.900

0.880 0.860

+ Eidsting network wwithout DG DG at bus 21 DG at bus 59

-K-DG at bus 61

DG at bus 64

+ DG at bus 65 0.840

0.60

0.80

1.00

1.20

1.40

Loading

Figure 8: Minimum voltage when fault increase in

the system

occur

at bus 10 for overall load

570 restoration. The optimal location of the distributed

1 .000

\V

\1/

generation

0.980 0.960

3 0.940 m

(DG)

is determined

by sensitivity

indices based

voltage stability improvement with respect to changes in reactive and active power injections at a load bus. The optimal sizing of the DG is determined by having the kW output (Pg) of the DG as the variable to be optimised in the Evolutionary Programme (EP) optimisation. The objective of the optimisation is to minimise the network losses. Network reconfiguration was implemented after the occurrence of fault for service restoration. The simulation was carried out using software PSS/Adept with various on

0.920

0

>

Edsting

0.900

network

+without DG DG at bus21

0.880

DG at bus 59= DG at bus 61 DG at bus 64

0.860

lDG~ at

location of fault. The results of the existing configuration

bus 65

network were compared with the results obtained after the network is reconfigured. From the numerical simulation, the

0.840

0.60

0.80

1.00

1.20

1.40

Loading

Figure 9: Minimuim voltage when fault increase in the sys-tern

occur

presence

at bus 20 for overall load

of distributed generation at the proposed location

and sizing voltage

are

able to produce the best results in terms of

profile improvement and

power

loss minimisation

after the network is reconfigured at various fault location.

1 .000

VII. REFERENCES

0.980 0.960

P.P. Barker, R.W.D. Mello,

[2]

Generation on Power Systems. I. Radial Distribution Systems", in IEEE/Power Eng Soc. Summer Meeting, vol 3, 2000, pp 1645-1656. Y.Mao, K.N.Miu, "Switch Placement to Improve System Reliability for Radial Distribution Systems with Distribution Generation", in IEEE Trans. on Power Systems, vol 18, no 4, Nov 2003.

3 0.940 m

0.920

0

>

--+-

Esting network

0.900

E)dsting netvvork

[3]

DG at bus DG at bus -K DG at bus DG at bus + DG at bus

0.860

21

59

[4]

61 64

65

0.60

0.80

1.00

1.20

[5]

1.40

Loading

Figure 10: Minimlum voltage when increase the sys-,tem

fault occur at bus 40 for

overall

load

Rahim,

I.

Musirin,

"Optimal Allocation and

Sizing of Distributed Generation in Distribution System", in Malaysian Power and Energy Conference, Dec 2004. J.A. Greatbanks, D.H. Popovic, M.Begovic, A. Pregelj, T.C. Green, "On Optimization for Security and Reliability of Power Systems with

[6]

Jun 2003. G. Celi, E.Ghiani, S.Mocci, F.Pilo, "A Multiobjective Evolutionary Algorithm for the Sizing and Siting of Distributed Generation," in IEEE Trans. on Power Systems, vol 20, no 2, May 2005. Chiang, R.Jean-Jumeau, "Optimal Network Reconfigurations

H.

Part 2:

in

Solution Algorithms and Numerical

Results," in IEEE Transactions on Power Delivery, Vol. 5, no. 3, July 1990. [7] M.A. Kashem, V. Ganapathy and G.B. Jasmon, "Network Reconfiguration for Enhancement of Voltage Stability in Distribution Networks," in IEEE Gen. Trans. Distribution, vol. 147, No. 3, May 2000. [8] S. Civanlar, J.J. Grainger, H. Yin, S.S.H. Lee, "Distribution Feeder Reconfiguration for Loss Reduction," in IEEE Trans. Power Delivery, Vol 3, no 3, July 1998. [9] M.E. Baran and F.F. Wu, "Network Reconfiguration in Distribution

1 .000

0.980 0.960

3 0.940 0.920

0

Edsting

0.900

Systems for

network

+-without DG X

via

DG at bus 64 + DG at bus 65

-

Balancing",

1407, April in

IEEE

Trans.

on

1989.

Distribution Networks

Network Reconfiguration", in IEEE Trans

Choi,

[11] J.H.

1.00

1.20

1.40

Loading Minimium voltage increase in the sys- uem

1401

on

Power Delivery,

Vol. 7, No. 2, April 1992.

0.840 0.80

vol.4, No.2, pp.

[10] D. Shirmohammadi, "Service Restoration

-K-DG at bus 61

0.60

Loss Reduction and Load

Power Delivery.,

DG at bus 21 DG at bus 59

0.880

11:

S.R.A.

Distribution Systems:

in

Figure

Rahman,

Impact of Distributed

Distributed Generation," in IEEE Bologna PowerTech Conference,

0.840

0.860

T.K.A.

the

without DG

0.880

M

"Determining

[1]

when fault occur at bus 62 for overall load

From figure 7, 8, 9, 10 and figure 11, it can be seen that the minimum voltage increase in the system after network is reconfigured at all fault location. VI. CONCLUSION This paper presents the influence of location and sizing of distributed generation to the power losses and voltage profile during network reconfiguration for service

J.C.Kim,

S.H.Moon, "Integration of Dispersed Generations

to Automated Distribution Networks for Network Reconfiguration", in

IEEE Bologna PowerTech Conference, Jun 2003.

[12] T.K.A. Rahman and G.B. Jasmon, "A New Voltage Stability Index Load adLa

and

flow Technique for Power System nlss" Analysis" lwTcnqefrPwrSse

International Journal of Power and Energy Systems., vol.17, no.1,

pp.

28 - 37, 1997.