Service Restoration in Distribution Network with ... - IEEE Xplore

4th Student Conference on Research and Development (SCOReD 2006), Shah Alam, Selangor, MALAYSIA, 27-28 June, 2006

Service Restoration in Distribution Network with Distributed Generation Zuhaila Mat Yasin, Titik Khawa Abdul Rahman Fakulti Kejuruteraan Elektrik Universiti Teknologi Mara, 40450 Shah Alam Selangor Abstract--This paper studies the influence of location and capacity sizing of distributed generation during service restoration. It is assumed that after the occurrence of fault at particular section of a distribution network, the loads get disconnected and are left unsupplied. Service should be restored to the affected loads through a network reconfiguration procedure. In this study, network reconfiguration was implemented using the TOPO application in the power system simulation programme for planning, design and analysis of distribution system (PSS/Adept). This application determines the optimal sectionalizing-tie switch pairs based on minimum losses configuration and at the same time, all nodes are assured for the supply. 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 proposed study was conducted on the IEEE 69 bus distribution system. The results show that installing distributed generation at the suitable location with appropriate sizing has able to provide lower loss level and higher voltage profile in fault condition as compared to that obtained when the network was installed with compensating capacitor.

Keywords: distributed generation, service restoration, network reconfiguration, compensating capacitor

I. INTRODUCTION An electric power system consists of three principle divisions namely generating stations, transmission lines and distribution systems. The distribution system is part of the system between transmission lines and the consumer service point. Distributed generation (DG) is defined as energy resources of limited sizes (15 MW or less) connected to the substation, distribution feeder or customer load levels. It is expected that DG could contribute in the following areas of distribution system operation [1]:a) Quality improvement such as dynamic voltage compensation, voltage profile improvement, etc. b) Reliability improvement such as service restoration and uninterruptible power supply. c) Economic benefits such as energy efficiency, loss minimisation and load leveling. There are many technical issues to be considered when connecting distributed generation (DG) to the distribution system such as thermal rating of equipment,

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system fault levels, stability, reverse power flow capabilities of tap-changers, line drop compensation, steady-state voltage rise, power losses, power quality (such as flickers and harmonics) and protection [2]. However, depending on the system’s operating condition and the DG’s characteristics and location, DGs installation may impose either be positive or negative impact. Several techniques have been developed in determining the optimal location and sizing of DG as described in references 3 to 5 in order to minimise the total distribution losses and improve voltage profile in the system. The unsuitable location and sizing of the DG unit will result in an increasing of power losses and in a reducing of reliability levels [6]. Forces and scheduled outages are commonplace in distribution system. The occurrence of fault will results in the isolation of some portion (branches) of the feeder downstream from the affected area. Therefore the service should be restored to these branches via network reconfiguration [7]. System reconfiguration problem concerns with identifying the suitable tie-line switches to be closed in replacement of opening sectionalizing switches. Distribution system reconfiguration can be considered as a combinatorial optimisation problem, involving distribution system planning, loss minimisation and supply restoration [8]. Many techniques have been proposed to find the suitable pair of switches (sectionalizing – tie) in order to achieve these objectives [7-10]. This paper studies the influence of location and capacity sizing of distributed generation (DG) during service restoration in the event of fault. 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 predeveloped sensitivity indices derived from voltage stability improvement with respect to changes in injected active and reactive power at a bus [3]. The optimal capacity sizing of the distributed generation was determined using the Evolutionary Programming (EP)

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optimisation technique [3]. Various locations and sizes of DGs were also tested in order to realize the effect of location and sizing of DGs in terms of loss minimisation and voltage improvement during service restoration in the fault condition. The results were compared with those obtained when the network was installed with compensating capacitor. The study was implemented on the 69-bus distribution system [3].

Expressing equations 2 and 3 into matrix form gives

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 [11] 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:The voltage stability index at a load bus i is given by [11]

Li " 4[Voi V Li cos

2 i ! V Li

cos

2 i ] / Voi ................(1)

oi

!

Li

)

Li

" load angle at bus i

oi

" no load angle at bus i

The first sensitivity index was formulated from the change in Li with respect to the change in injected Pi at bus i is given by

' % %...............(5) % % %&

The elements of the row matrices in equations 4 and 5 are derived from equation 1 as follows,

+

,

Vo ! 2V L #Li " 4 i 2 i ...............(6) #V Li Voi

-

#Li 4 " 2 ! Voi V Li sin # Li Vo i

i

#V Li

Li

#Qi

,

#

Li

#Qi

,

#V Li #Qi

and

#

#Qi

$ 2V L2i cos

i

sin

i

.......(7)

are obtained from the

inverse of loadflow jacobian matrix.

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. Xi = Pg ………………………(11)

Cos / = 0.85, where / is power factor angle

Hence, the second sensitivity index was derived from the change in L with respect to the change in injected Q at bus i is given by

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* #V Li ( ' #L ( #Qi % # Li %& ( # Li ( () #Qi

Qg = Pg x tan -1 / ………………(12)

#Li #Li #V Li #Li # Li " $ ...............( 2) x x #Pi #V Li #Pi # Li #Pi

#Li #Li #V Li #L i # Li " $ x x .......... .....( 3) #Q i #V Li #Q i # Li #Q i

#Li * #Li "( #Qi () #V Li

III OPTIMAL SIZING OF DISTRIBUTED GENERATION

Voi " no load voltage at bus i "(

' % %...............(4) % % %&

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.

2

V Li " load voltage at bus i

i

#Li * #Li "( #Pi () #V Li

* #V Li ( #L ' ( #Pi %( # Li %& # Li ( () #Pi

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

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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

Minimise

1P

loss

.....................................(13)

j "1

n " number of lines in the system Voltage constraints, Vimin 0 Vi 0 Vimax ..............(14)

Fig.1: A 69-bus test system

IV NETWORK RECONFIGURATION FOR SERVICE RESTORATION The location and sizing of the distributed generation (DG) were identified using the techniques described in section 2 and 3. 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. The resulting network is the radial network with minimum real power loss.

V SIMULATION RESULTS AND DISCUSSIONS 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 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

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switch connection

TABLE 1 TIE LINE SWITCHES CONNECTION S1 S2 S3 S4

8-43

16-46

12-21

50-59

S5 27-65

TABLE 2 THE FIRST 5 BUSES WITH HIGHEST SENSITIVITY INDEX VALUE

Bus No. 61 64 21 65 59

#Li #Pi 26.3958 7.7781 3.8323 2.5544 2.396

Bus No 61 64 50 49 21

#Li #Qi 10.2167 2.8583 1.2550 1.0333 1.0086

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 DG. The optimal output of the distributed generator 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. In order to study the effect of 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 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)

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4th Student Conference on Research and Development (SCOReD 2006), Shah Alam, Selangor, MALAYSIA, 27-28 June, 2006 TABLE 3 OPTIMAL DG OUTPUT FOR LOSS MINIMISATION IN THE SYSTEM FOR OVERALL LOAD INCREASE IN THE SYSTEM.

450

optimal output of DG at each bus location (MW) 61 64 59 65 21

0.6

1.1009

0.9632

1.1464

0.8369

0.4527

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

w ithout DG DG at bus 21 DG at bus 59 DG at bus 61 DG at bus 64 DG at bus 65 C at bus 61

500

Real Power Loss (kW)

Loading (p.u)

550

400 350 300 250 200 150 100 50 0 0.60

The fault was applied to the network individually with different location of DG. The minimum losses and minimum voltage were identified after the network is reconfigured by closing the corresponding tie-line switches for load restoration. The graph in figure 2, 3, 4, 5 and 6 illustrates the variation of losses in the system as a result of installing distributed generation (DG) at the respective buses with different fault location.

350

1.40

550 w ithout DG DG at bus 21 DG at bus 59 DG at bus 61 DG at bus 64 DG at bus 65 C at bus 61

500 450



400

1.20

Fig. 4: Total system losses with fault at bus 20 for overall load increase in the system.


450

1.00

Loading

550 500

0.80

300

400 350 300 250 200 150

250

100

200

50

150

0 0.60

100

0.80

50

1.00

1.20

1.40

Loading

0 0.60

0.80

1.00

1.20

1.40

Loading

Fig.5: Total system losses with fault at bus 40 for overall load increase in the system. 550

Fig.2: Total power losses with fault at bus 6 for overall load increase in the system


500 450

550 500


450 400 350



300 250

400 350 300 250 200 150

200

100

150

50

100

0

50

0.60

0

0.80

1.00

1.20

1.40

Loading 0.60

0.80

1.00

1.20

1.40


Loading


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From the graph shown in figure 2, 3, 4, 5 and 6, it could be observed that load increase at all buses has caused an increase in the total losses of the system significantly. However, with the installation of DG at bus 61 produced minimum losses in the system for various location of fault as compared to the other DG location. Figure 7, 8, 9, 10 and 11 shows the minimum voltage profile in the system as a result of installing DG at the respective buses with different fault location.

1.000

Min Voltage (p.u)

0.960

0.920 w ithout DG DG at bus 21 DG at bus 59 DG at bus 61 DG at bus 64 DG at bus 65 C at bus 61

0.880

1.000

0.840 0.60

0.80

1.00

1.20

1.40

Loading

Figure 9: Minimum voltage with fault at bus 20

0.920

1.000


0.880

0.960

Min Voltage (p.u)

Min Voltage (p.u)

0.960

0.840 0.60

0.80

1.00

1.20

1.40

Loading

Fig.7: Minimum voltage with fault at bus 6

0.920 w ithout DG DG at bus 21 DG at bus 59 DG at bus 61 DG at bus 64 DG at bus 65 C at bus 61

0.880

1.000

0.840 0.60

0.80

1.00

1.20

1.40

Loading


0.920

1.000


0.880

0.960

Min Voltage (p.u)

Min Voltage (p.u)

0.960

0.840 0.60

0.80

1.00

1.20

1.40

Loading

Fig. 8: Minimum voltage with fault at bus 10


0.880

The graph in figure 7, 8, 9, 10 and 11, shows that the increase in the load has also reduced the minimum voltage. For all locations of fault, the installation of DG at bus 61 provides better improvement in terms of voltage profile. At all fault location selected above, the results shows that the location of DG at bus 61 produce minimum total losses while maintaining the voltage profile at the acceptable range.

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0.920

0.840 0.60

0.80

1.00

1.20

1.40

Loading


VI CONCLUSION In this paper, the benefit of implementing Distributed Generation (DG) in terms of minimising the power loss and improving voltage profile under fault condition were analyzed. The optimal location of DG is determined by

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sensitivity indices based on voltage stability improvement with respect to changes in reactive and active power injections at a load bus. The optimal size 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. The best five locations from the sensitivity analysis with optimal sizing from EP were selected for the analysis. Network reconfiguration was implemented after the occurrence of fault for service restoration. The simulation was carried out using software PSS/Adept with various location of fault. The results were compared with the network with compensating capacitor at the optimal location. From the numerical simulation, the presence of DG at the proposed location and sizing are able to produce the best results in terms of voltage profile improvement and power loss minimisation at various fault location.

[3] [4]

[5]

[6] [7] [8]

[9] M.E. Baran and F.F. Wu, “Network Reconfiguration in Distribution Systems for Loss Reduction and Load Balancing”, IEEE Trans. on Power Delivery., vol.4, No.2, pp. 1401 – 1407, April 1989. 10]

VII REFERENCES [1]

P.P. Barker, R.W.D. Mello, “Determining the Impact of Distributed Generation on Power Systems. I. Radial Distribution Systems”, in IEEE/Power Eng Soc. Summer Meeting, vol 3, 2000, pp 1645-1656.

[2]

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.

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T.K.A. Rahman, S.R.A. 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 Distributed Generation,” in IEEE Bologna PowerTech Conference, 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. N.H. Said, J.F. Canard, F.Dumas, “Dispersed Generation Impact on Distribution Networks”, in IEEE Computer Applications in Power, Vol. 12, no. 2, April 1999, pp. 22-28. D. Shirmohammadi, “Service Restoration in Distribution Networks via Network Reconfiguration”, in IEEE Trans on Power Delivery, Vol. 7, No. 2, April 1992 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.

M.E. de Oliveira, L.F.Ochoa, A.Padhila-Feltrin, J.R.S. Mantovani, “Network Reconfiguration and Loss Allocation for Distribution Systems with Distributed Generation”, in IEEE/PES Trans & Distribution Conference & Exposition: Latin America, 2004. [11] T.K.A. Rahman and G.B. Jasmon, “A New Voltage Stability Index and Load flow Technique for Power System Analysis ”, International Journal of Power and Energy Systems., vol.17, no.1, pp. 28 – 37, 1997.

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