network reconfiguration for service restoration are investigated in this paper. ... simulation was conducted on the 69-bus distribution system. Index terms ...
First International Power and Energy Coference PECon 2006 November 28-29, 2006, Putrajaya, Malaysia
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 , . 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  to  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 . Reference  to  presents different technique in determining optimal configuration during normal operating condition. Whereas, reference  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  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 . 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  identifies the suitable location for the distributed generator by studying the pre-developed voltage stability index  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  is as follows:-
567 The voltage stability index at a load bus i is given by  Li
] / Voi .................(1)
load voltage at bus i no load voltage at bus i
load angle at bus i = no load angle at bus i
Hence, the second sensitivity index
from the change in L with respect to the change in injected Q at bus i is given by aL,
Expressing equations 2 and 3 into matrix form gives a aLl
The elements of the row matrices in equations (4) derived from equation (1) as follows,
U2 voi aOL,
Vi VL, sin Oi + 2V/ cos aVL,
aQi e Qi aQi
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
n = number of lines in the system Voltage constraints, Vimin < Vi < V .ma
aQi and (5)
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 . 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.
sin Oi ].....(7)
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
32 33 34
2 63 64 65
51 58 59 6 0 61
Figure 1: A 69-bus test system TABLE 1 TIE LINE SWITCHES CONNECTION
TABLE 2 THE FIRST 5 BUSES WITH HIGHEST SENSITIVITY INDEX VALUE
61 64 21 65 59
api 26.3958 7.7781 3.8323 2.5544 2.396
optimal output of DG at each bus location (MW) 64 21 61 59 65 0.4527 1.1009 0.9632 1.1464 0.8369
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
TABLE 3: OPTIMAL DG OUTPUT FOR LOSS MINIMISATION IN THE SYSTEM FOR OVERALL LOAD INCREASE IN THE SYSTEM.
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
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.
w ithout DG
DG at bus 21 DG at bus 59 )K DG at bus 61 DG at bus 64 DG at bus 65
100_ 50 0.60
Figure 2: Total power losses when fault increase in the system
at bus 6 for overall load
existing netw ork ithout DG DG at bus 21 DG at bus 59
-*--DG at bus
existing netw ork
w ithout DG
DG at bus 21
DG at bus 59
DG at bus 64
DG at bus 64
DG at bus 65 0 250 -J/
DG at bus 65 300-
power losses when fault
10 for overall load
Total power losses when fault the system
for overall load
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.
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
100 0.960 0
Figure 4: Total power losses when fault increase in the system
m 0.940 -.
at bus 20 for overall load
DG at bus DG at bus -K-DG at bus DG at bus DG at bus
DG at bus
+ Eidsting network
DG at bus 59
DG at bus
DG at bus 64 DG at bus 65
Figure 7: Minimum voltage when fault increase in the system
at bus 6 for overall load
Figure 5: Total power losses when fault increase in the system
at bus 40 for overall load
+ 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
Figure 8: Minimum voltage when fault increase in
at bus 10 for overall load
570 restoration. The optimal location of the distributed
3 0.940 m
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
+without DG DG at bus21
DG at bus 59= DG at bus 61 DG at bus 64
location of fault. The results of the existing configuration
network were compared with the results obtained after the network is reconfigured. From the numerical simulation, the
Figure 9: Minimuim voltage when fault increase in the sys-tern
at bus 20 for overall load
of distributed generation at the proposed location
and sizing voltage
able to produce the best results in terms of
profile improvement and
after the network is reconfigured at various fault location.
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3 0.940 m
DG at bus DG at bus -K DG at bus DG at bus + DG at bus
Figure 10: Minimlum voltage when increase the sys-,tem
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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
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