a combined zone-3 relay blocking and

8/7/2019 A Combined Zone-3 Relay Blocking and

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Abstract— A typical power system voltage collapse scenarios

is often ended with the undesirable operation of the Zone-3

distance relay of the transmission lines. This paper presents a

protection scheme to avoid power system voltage collapse using a

combined method of distance relay’s Zone-3 blocking scheme and

a sensitivity-based load shedding selection. The Zone-3 distance

relay blocking is based on the proper differentiation between

transmission line overloading and line faulted conditions, using a

fast estimation of power flow based on Line Outage DistributionFactor (LODF) and Generation Shift Factor (GSF). The Zone-3

distance relay of the transmission line would be blocked if the

power flow change over the line is determined to be due to an

overload so that more time would be available for the system to

take necessary control actions. One of the important control

actions is the emergency load shedding. A method based on the

calculated sensitivities GSF to identify the most effective load

shedding positions and amounts is proposed. The proposed

method has been implemented in the Advanced Real-Time

Interactive Simulator for Training and Operation (ARISTO)

software with the Nordic 32-bus test system. ARISTO offers the

possibility to test the proposed scheme since it can be seen as the

virtual power system with all live information. The analyses of

power system voltage collapse scenarios with and without the

proposed scheme implemented have shown the effectiveness of the scheme to prevent the voltage collapses.

Index Terms — ARISTO, GSF, LODF, load shedding, voltage

collapse, power system protection.

I. I NTRODUCTION

n the past decades, many power utilities world-wide have

transformed their ways of doing business, from vertically

integrated functioning to open-market systems. The

transformations were undertaken by introducing commercial

incentives in generation, transmission and distribution of

electricity with, in many cases, large efficiency gains. Though

this may seem fairly straightforward at first glance, there areseveral complexities involved in restructuring and several new

issues have surfaced. Recent large-scale power system

blackouts in the USA and Europe [1]-[3] have given us a

“wake-up” call on the vulnerability of our power systems that

they are being operated much closer to the limits than ever

before.

The authors are with the Division of Electric Power Engineering,

Department of Energy and Environment, Chalmers University of Technology,

41296 Gothenburg, Sweden (emails: <jemal; pinares>@student.chalmers.se;<tuan.le; lina.bertling>@chalmers.se).

From the analysis of those blackouts, it has been identified

that blackouts starts with some triggering event, normally a

critical fault in the system, followed by subsequent system

dynamic responses. These triggering events push the system

into unreliable operating condition and reduced the capacity of

the transmission system but the system is still more or less

stabilized. However, additional events, such as load recovery

or improper relay operations, would lead, finally, to a long-

term voltage stability problem [4] and could lead to a voltagecollapse in some parts or the system or in a worst case, whole

system blackout. One of the factors that worsen the power

system condition after the triggering event has occurred is the

un-intentional operation of the distance relays. Due to line

overloading conditions, Zone-3 of the distance protection [5]

may operate and disconnect transmission lines when they are

needed most in the weakened system. That will have

immediate effects on the remaining lines and could eventually

lead to cascading tripping of them and system separations are

the obvious consequences. This phenomenon has been

identified in the blackouts in the USA and South Sweden-

Denmark in 2003.

Large-scale power outages can end up with billions of

dollar losses in economic activities as well as other un-measureable inconveniences. Because of the great impacts of

those events on the modern society, the needs to analyze them

and to propose the mitigation or prevention measures are

becoming more critical.

A review of methods to prevent voltage collapses can be

found in the following section. In this paper, the method

proposed in [6] to prevent undesired operation of Zone-3 of

the distance relay during the overloading condition was

implemented and further extended with the sensitivity-based

load shedding selection scheme. This selection scheme would

allow the system operator to choose the most effective groups

of load to be shed in order to prevent the cascading outages.

This proposed combined method (i.e., blocking of Zone-3relay and selective load shedding) could be implemented

based on a good communication infrastructure and a fast

power flow estimation.

The paper is organized as follows: In Section II, a brief

review of voltage collapses and methods for voltage collapse

preventions are presented. The Zone-3 blocking scheme,

developed in [6] is briefly explained in Section III and it is

further extended to the proposed combined voltage collapse

prevention method. In Section IV, a short description of the

software ARISTO is presented, which is used, likewise, for

A Combined Zone-3 Relay Blocking and

Sensitivity-Based Load Shedding for

Voltage Collapse PreventionKalid Jemal Yunus, Gustavo Pinares, Le Anh Tuan, Member IEEE,

Lina Bertling, Senior Member IEEE

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dynamic simulations of the Nordic 32-bus test system. The

proposed method has been implemented with the dynamic

simulations of the power system blackout scenarios and the

simulation results are presented. Finally, important

conclusions of this work are presented in Section V.

II. A BRIEF R EVIEW OF POWER SYSTEM VOLTAGE COLLAPSES

A. Voltage Stability and Voltage Collapse

Voltage stability refers to the ability of a power system to

maintain an acceptable state of equilibrium voltage at all

busses after being subjected to a disturbance from a given

initial operating condition. The ability of a system to be stable

depends on the capability of keeping the demand and supply

balance [7].

Voltage instability usually occurs in the form of continues

rise or fall of voltages on some busses. The phenomena

“voltage collapse” is the result of sequence of events in the

system that leads to abnormal low voltages in a significant

part of the power system. A possible consequence of this is the

disconnection of generators, lines, loads or other elements in

the power system by the operation of their respective protection systems, and, in a most critical case, to a cascaded

total outage of a power system [4], [7].

In response to a disturbance, power consumed by the loads

tends to be restored by the action of motor slip adjustment,

distribution voltage regulators, tap changing transformers, and

thermostats. For instance, if the load is supplied through a

transformer equipped with under-load tap changer (ULTC),

the tap changer action tries to restore the load voltage, which

means the reduction of the effective impedance of the load as

seen by the transmission system. This will further reduce the

voltage which, in turn, leads to increased reactive power loss.

The worst case causing voltage instability occurs when load

dynamics attempt to restore power consumption beyond thecapability of the transmission network and the connected

generation. If this is case, the capability limits of some of the

generators and lines are reached, protective relays operate due

to high currents and low voltages, disconnecting lines, leading

to reducing the power transfer capacity of the system,

overloading other elements, and cascading tripping of

transmission lines will occur leading to system separation and

voltage collapses.

The operation of protective relays under overload condition

is undesirable since relays are intended to operate under faults

and not under overload conditions. One way avoid this

undesirable operation is to differentiate overload conditions

from faults. This will be discussed further in Section III.

B. Voltage Collapse Prevention

There is a number of protection schemes proposed to

prevent power system voltage collapses (see for example, [8]-

[12]). These schemes include the modification of protection

settings, smart islanding, circuit-breaker blocking,

transformers tap-changers blocking, and load shedding (under

frequency and under voltage).

In this paper, the Zone-3 blocking scheme presented in [6]

is further extended to include multiple outage power flow

estimation and sensitivity-based load shedding which is

utilized as a solution to prevent voltage collapse. For the sake

of completeness, the next section will summarize the key

points in this scheme and discuss the extension of the scheme

into the proposed combined method.

III. THE PROPOSED COMBINED ZONE-3 R ELAY BLOCKING AND

SENSITIVITY BASED LOAD SHEDDING SCHEME

This section is divided in two parts. The first one is devotedto summarize the zone-3 blocking scheme developed in [6]

and its extension to multiple outages. The second part will

present a sensitivity-based load shedding scheme in order to

alleviate the stress condition in the system.

A. Zone 3 Relay Blocking Scheme to Avoid Tripping

Overloads

This procedure is based on blocking Zone-3 relay within

the adaptive distance relay scheme (ADRS) presented in [6].

This scheme relies on a reliable system-wide communication

scheme which will be presented next. Following to this, the

algorithm itself to differentiate overload from short circuit

conditions will be introduced.

1. Communication for the blocking scheme

In this scheme, we have one central control unit (CCU),

which is located in the control center, and regional control

units (RCU), which are located at each substation. Fig. 1

shows the principles of this scheme.

Fig. 1: The adaptive distance relay scheme

CCU takes care of calculating the line outage distribution

factor (LODF) and generation shift factor (GSF) values for

each line following line(s) or generator(s) outage, respectively

[13]. With those factors the power flow redistribution at each

line after a contingency can be estimated. To calculate those

factors, the CCU needs, as inputs, the system parameters (i.e.,

the impedance matrix) and the system element operating states

(i.e, elements in or out of service, power flows over lines)

which can be obtained from the energy management system

(EMS) and regional control units (RCU). After the CCU

calculates those factors, it will send them to the RCUs.

The RCUs, which are located in every substation, calculate

the estimated power flow on each monitored line and takes

necessary action on the relays in charge of each monitored

lines. This calculation is based on the values of LODF and the

GSF factors given by the CCU. The RCUs also get the



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information of which components are the cause of

contingency and their power flow before the contingency

occurs. The RCUs which supervise the component that caused

the contingency are responsible in providing this data to the

CCU and the other RCUs. In order to broadcast the

information of pre-contingency load flow, RCUs must store

the power flow data at certain time intervals.

2. Fast Estimation of Power Flow and the Zone-3 Relay

Blocking Algorithm

In this scheme, a fast estimation of power flow following

an outage and its comparison with measured power flow is

proposed as a way to differentiate between faulted conditions

and overload conditions over transmission lines.

The power flow estimation is based on the computation of

the well-known sensitivity factors, LODF and GSF [13]. The

LODF represents the change of power flow in a line “l ” due to

an outage in line “k ”. The GSF represents the change of power

flow in a line “l ” due to a change of power in generator “ g ” (it

can also be a change in the load, as will be discussed in

Section III.B).

After a line outage and a generation/load change, theestimated power flow over a line “l ” is calculated as:

( ) ( )

( ) g

k Initial Estimated

P g l GSF

P k l LODF Pl g k l P

×

+×+=

,

,,,

(1)

( )( )

( )

k in jn im jm

l

k nn mm nm

x X X X X

x LODF l ,k

x X X 2 X

− − +

=

− + −

(2)

( ) ( ) jg ig

l

1GSF l,g X X

x= −

(3)

where:

xk : reactance of the disconnected line k

xl : reactance of the monitored line l

X a,b : a, b element of the impedance matrix

i,j : Buses IDs where line l is connected

n,m : Buses IDs where line k is connected

g : Bus ID where the generator or load is connected

P l : Measured power in the monitored line l

P g : Measured power of the generator or load before disconnected

P k : Measured power of the line k before disconnected

Once the estimated power flow is calculated, if a relay

detects the line impedance in its Zone-3, it will send a signal

to the RCUs. The RCUs calculate the error as a percentage of

the difference between the measured power flow from the

same line at the given instant and the estimated power. If the

error is within the given tolerance range it will send the block

signal. This would indicate that the power flow change is due

to a line outage. The algorithm is shown in Fig. 2.

In the meantime, a fast relieving action in the form of load

shedding should be taken. If a load shedding action is

triggered by the system condition, the line flows will change

as a consequence. The proposed method will monitor the new

system condition and determine if any Zone 3 blocking is still

necessary, by continuously comparing the measured and

estimated power flow once the impedance of a particular line

is found to be in zone of protection of a given relay.

Fig. 2: The schematic diagram for the Zone-3 relay blocking scheme

The algorithm was tested for single outage in [6], however

multi-outage cases were not considered. An extension of the

single outage case is presented in this paper. For multiplecontingencies, it depends on how long it takes between

contingencies. If another contingency occurs after the system

has stabilized we can consider it as single contingency with

reduced components. Then the actual load flow data stored

before the second contingency occurs is used in calculating the

estimated power flow on the remaining lines. But, if the

contingencies occur at the same time, which could be the case

of a bus-bar fault, we have to figure out the way to use the

data before any contingency occurs. The multi-outage power

flow estimation is also based on [6] but considering every

outage (i.e., generators, lines) occurred one after the other and

estimating a new power flow and LODFs or GSFs at every

stage. Fig. 3 presents a schematic diagram of the procedure toestimate the power flow on all lines after a multiple outages.

Basically, the procedure to calculate the estimated power after

multiple outages can be summarized as follow:

1. All the system element states and power flows are

obtained after the given outage.

2. The first calculation is done for generation outage or

output power change since it doesn’t imply the

modification of the impedance matrix.

3. The new power flow is calculated using GSFs and it is

stored. The change of power due to slack generator

must be also taken into account.

4. When finished with all generator outages, continuewith line outage.

5. The second calculation is for lines outage. It implies

the modification of the impedance matrix. The

“original power flow” in this case comes from the

calculation stored when calculating the change of

power flow due to generator/load changes.

6. The new power flow is estimated using LODFs and is

stored.

7. A new impedance matrix Z bus is evaluated considering

the line outage and the procedure is repeated until all



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specified lines are taken out.

Fig. 3: Schematic diagram of fast estimation of line flows after multiple

outages

B. Combined Zone-3 Blocking and Sensitivity Based Load Shedding Scheme

Even though unwanted disconnections using Zone-3 relay

blocking algorithm, described above, can be prevented, the

system can be still prone to a voltage collapse. Due to this, an

emergency control, the load shedding scheme based on the

calculated sensitivity factors, is proposed. In this scheme, the

location of the best "shedding" candidates will be identified.

The best candidates here refer to the loads which could relieve

the most with the stress in the critical power system elements.

The selection of the shedding candidates can be done based on

the calculation of the sensitivity factors GSF, which were

described earlier. As stated in the previous Section, this factor

indicates the change in power flow over a line “l ” due to the

change in either generation or load at a bus “ g ”. The

disconnections of loads located at buses with the highest GSFs

for the corresponding overloaded line (which needs to be

relieved) will greatly reduce the loading of that line. Once the

potential candidate locations for load shedding are identified,

the amount of power to be shed to relieve a particular line is

given by:

( )( ) ( )

( )

Limit Measured Shed

P l P l P g

GSF l ,g

−

=

(4)where:

P Shed ( g ) : is the estimation of power to be shed at bus g

P Limit (l ) : is the power flow limit on line l

P Measured (l ) : is the measured power on line l

( )GSF l ,g : is the highest GSF factor referring to the change

in the load at location g with respect to the flow

on the line l. It should be noted that before load shedding starts, first the

prediction of the possibility of a voltage collapse is important.

There are a number of methods dealing with this issue (see for

example, [14]-[16]). However, this is out of the scope of this

paper, and we have assumed that the fast detection of a

voltage collapse, in this case, is known and the proposed

scheme is focused on the points after that.

IV. SIMULATION STUDY

This section describes the software used to simulate the

power system dynamic operation. It is called Advanced Real-

Time Interactive Simulator for Training and Operation(ARISTO) and presents the dynamic simulation of the voltage

collapse scenarios with and without the proposed protection

scheme implemented using the Nordic 32-bus test system [17].

A. Description of ARISTO

ARISTO is an Advanced Real-time Interactive Simulator

for Training and Operation. One of the important

characteristic of this simulator is that it handles detailed

dynamic phenomena in real time, being capable of running

large scale systems [18]. The interactive graphic user interface

is very suitable to get a deep understanding of the system

behavior. The architecture of the software is as shown in Fig.

4.

Fig. 4: The architecture of ARISTO [18]

The ARISTO simulator has been developed by the Swedish

Transmission System Operator (Svenska Kraftnät), and is used

for power system analysis and training of the system

operators. One of the unique features of this software is the

“Event Panel” where the “operator” can send instructions to

the simulator. It is particularly useful for creating different

scenarios, i.e. a sequence of events with certain time-stamped

occurrence for each event in the scenario. The scenarios are

sent to the simulator to see the dynamic responses of the

system. Other facility is the “Curve Diagram Panel,” which is

used to monitor the system, where the generator frequency, the

bus voltage, the line transfer power, and the generator output

power are represented in different graphs. Every variation of

those parameters can be checked and analyzed there. The

“Event Browser Panel” is also an important facility of

ARISTO because each control action done by the “operator”

or automatic actions by the system and the precise time at

which the actions happened are recorded there. By observing



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the Event Brower, the user can easily notice different

actions/responses of the system to certain events occurred,

especially automatic actions by the protection system.

The ARISTO simulator is also used for educational

purpose, e.g., in the courses on “Power System Operation” and

“Project Engineering Design Project”, as well as on research

work at Chalmers University of Technology [11]-[12].

B. Simulation scenario

The Nordic 32-bus system [17] is used to simulate the power system voltage collapse scenarios. The single-line diagram of

this system is shown in Fig. 5. This system is divided into 4

main areas: the North, Central, Southwest and Northeast. The

North is characterized by high generation and mostly consists

of hydro power plants and some load centers. The Central

region consists of a large amount of load and large thermal

power plants. The Southwest region consists of some thermal

power plants and some load and finally the northeast is

connected to the north and has a mix of generations and loads

and it also connects the system with the external network. The

North generation region is connected to central load centers by

long transmission lines. The power flow in the normal

operating condition is mainly for the North to the Center and

the Southwest.

In the pre-fault scenario, generator G1 and G2 from the

substation FT63, G1 from RT131, and G2 from FT44 were out

of service. These buses are marked with red circles as shown

in Fig. 5. These generator outages correspond to a total

disconnection of 1.41 GW which leaves the total generation in

this scenario to 9.2 GW. In addition to this, two important

transmission lines, CL14 and CL17, which links the central

and the north part of the network, were on a scheduled outage

for maintenance. The system was working with normal

frequency and bus voltages. The line CL15 is with high load

but within the limit.

Fig. 5: Nordic 32-bus system in the pre-fault condition in ARISTO

The triggering event for the voltage collapse scenario was a

double bus-bar fault at substation FT44 (shown with the red

circle in Fig. 6). This fault resulted in the disconnection of line

FL16, FL1, CL12 and generators G1 and G3, which are all

connected to FT44. The network condition just after the fault

at FT44 can be seen in Fig. 6.

Fig. 6: The Nordic 32-bus system just after the fault at FT44

C. Simulation of the voltage collapse scenario without the

proposed prevention method implemented

The voltage collapse scenario observed was rather slow.

The loading of remaining lines CL15 and CL16 (see Fig. 6)

increased just after the fault at FT44 was cleared. On the other

hand, due to lack of generation in south area, voltage at

substations FT42 and FT150 in the central and FT62 in the

south west decreased substantially. As a consequence, tap

changers in these areas started to operate to bring the voltage

on the load side (low voltage) back to normal. This worsened

the situation and the voltage drop in these areas kept on

decreasing as the result of transformers’ tap changer actions.

Fig. 7 illustrates the curve diagram of system conditions

showing generation, line loadings, system frequency and

voltages after the fault.

Fig. 7: System condition after the fault

The results of this sequence of events was that the power

transfers in critical lines (CL15, CL16) increased and

oscillates; the lines were, thereby, disconnected by Zone-3

distance relays due to high currents and low voltages. Thus,

the central area was separated from the north. Since central

area was mainly a consumption area, the generation in this

Generation duringthe fault Line loading

during fault

Frequency during

the fault

Voltage during

the fault



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area was not enough to supply its load, as a result under

frequency protections of the generators disconnects the units

and total collapse in the central and south western part took

place as shown in Fig. 8.

Fig. 8: Nordic 32-bus system in total system collapse

In the North area, where there were lots of generators and

small loads, the voltage and frequency increased due to loss of

load in the south area, the supply–demand balance was heavily

disturbed causing the system frequency to reach its upper limit

and the generators are disconnected by the operation of over

frequency protection. This loss of generation in the north area

leads to total blackout of the entire system as shown in Fig. 9

below.

Fig. 9: Nordic 32-bus system in a total system voltage collapse

D. Simulation of voltage collapse scenario with the proposed prevention method implemented

The proposed protection scheme were tested in order to

prevent the system from a total voltage collapse. As presented

earlier, ARISTO is a continuous real-time simulator. It can be

seen as a virtual power system. The power flows and voltages

taken from ARISTO can be seen as the “measured” values in

the actual power system. To implement the proposed

protection scheme as explained in Section III, after a

contingency occurred (lines and/or generators outages), the

“measured” power flows on all the lines need to be compared

with their estimated values based on fast calculation of power

flows using the sensitivity factors calculated and stored earlier

in order to differentiate between overloading conditions and

the faulted conditions on the remaining lines.

To begin with, Table 1 shows the pre-fault “measured” power flow taken from ARISTO on the critical transmission

lines.TABLE 1: POWER FLOW ON THE CRITICAL LINES (FROM ARISTO)

Line Number From

Bus I

To

Bus J

MW at

Bus I

MW at

Bus J

CL15 CT21 FT41 896.7 850.6

CL16 CT32 FT42 658.8 633.6

CL12 CT21 FT44 502.5 479.4

FL16 FT44 FT42 455.0 451.1

FL1 FT44 FT43 450.6 446.8

When the double bus-bar fault occurred at the substation

FT44, as mentioned earlier, this fault resulted in the

disconnection of line FL16, FL1, CL12 and generators G1 and

G3, which were all connected to FT44. These will be

considered as the multiple outages in our calculation. The total

generation disconnected at the bus FT44 was 730 MW.

The data in Table 1 and the changes in generation at FT44

were used as inputs in a Matlab routine developed according

to the schematic diagram shown in Fig. 3, in order to fast

estimate line flows after multiple outages. The estimated

power flows on the critical lines after the fault at FT44 are

presented in Table 2.TABLE 2: ESTIMATED POWER FLOWS ON CRITICAL LINES

Line Number From

Substation

I

From

Substation

J

MW at

Substation

I

MW at

Substation

J

CL15 CT21 FT41 1265.211 1215.915

CL16 CT32 FT42 985.540 944.946

The “measured” power flow in ARISTO on the critical

lines right after the fault is cleared is given in Table 3.

TABLE 3: MEASURED POWER FLOWS ON CRITICAL LINES,

AFTER THE FAULT IS CLEARED

Line Number From

Substation

I

From

Substation

J

MW at

Substation

I

MW at

Substation

J

CL15 CT21 FT41 1215.400 1107.500

CL16 CT32 FT42 1035.400 949.700

The errors between the two values, the “measured” and

estimated values, are determined and shown in Table 4

TABLE 4: POWER FLOW ERROR (% DIFFERENCE) ON THE CRITICAL LINES

Line Number From

Substation

I

To

Substation

J

% error at

Substation

I

% error at

Substation

J

CL15 CT21 FT41 4.1 9.8

CL16 CT32 FT42 -4.8 -0.5

Generation during

the voltage collapse

Output power from

Generators

Power flow over

some lines

Frequency in

the system

Frequency duringthe voltage collapse

Line loading during

the voltage collapse

Voltage during the

voltage collapse

Slow decreaseof voltages

Voltages



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According to [6], an error of 10% might be composed of

1% of current transformer (CT) error, 1% of potential

transformer (PT) error, 3% of device errors, and 5% of

calculation errors. Our error should be 5%, since we are using

“correct” measured data. However, since in the multi-outage

algorithm we introduce error after error, we must consider

increasing the acceptable error, to 10%. If any Zone 3 relay of

those monitored lines start, the RCU will make a comparison

and will determine the error. In the current simulation, thedifference in the power flow was within the 10% error as can

be since in Table 4. This indicates that the start of Zone-3

relay action was due to an overload condition rather than due

to a short circuit condition.

About 3 minutes after the fault, Zone-3 relay of line CL15

detected the fault (and the Zone-3 timer starts) since the

impedance seen by the relay had been reducing and entered in

its protection zone. However, this was not the result of an

actual fault, but from overloading condition as will be

discussed. According to the communication scheme, the relay

sends a signal to the corresponding RCU. The RCU compares

the measured power flow with the calculated value. In our

case, the error in measured and calculated power flow on thecritical lines at this time was found to be similar to those

shown in Table IV, which was lower than 10%, indicating that

the relay had to be blocked. However, blocking the relay was

not enough to save the system from collapse. Even though the

Zone-3 was blocked, the voltages in the system would

gradually go down and finally the system would collapse due

to a voltage instability scenario. The blocking of Zone-3 on

critical lines would give more time to the system operator to

take actions such as load shedding.

At this point, the Zone-3 relay on the line CL15 relay had

to be blocked and load shedding should be carried out as fast

as possible, otherwise, the system would disintegrate due to

voltage collapse. This situation was also dangerous for the line

since the power flow can be above its maximum loading

(thermal) limit. It should be noted that the decision to block

the relay must be done quickly before the Zone-3 relay trips.

The time setting for Zone-3 relay is usually in an order of 1

second [5].

A more reliable automatic load shedding will be possible if

some method to identify the proximity to voltage collapse is

implemented. As mentioned in Section III.A.2, voltage

collapse identification is out of the scope of this work.

However, one of the methods discussed in [14]-[16] could be

implemented. To start the load shedding algorithm, voltage

collapse identification was assumed. To do this, we used the

GSF calculation for each load buses in the South as shown inTable 5 to determine which load buses would be the most

effective in reducing the power flow on the stressed lines.

As can be seen in Table 5, load buses FT41 (4041) and

FT61 (4061) have the highest relieving effects on the line

CL15. The amount of the load that must be shed should bring

the power flow on the line below its maximum limit. This can

be calculated using Equation (4). The calculation result set the

total amount of load that should be shed as 714 MW. Taking

this result into account, some of the loads connected to the

transformers T1, T2, T3 at substation FT41 were

disconnected. These loads amount a total of 689 MW. The

total load shedding could also be shared with the substation

FT61, since both have the same GSF value.

TABLE 5: GSF CALCULATION RESULTS AT DIFFERENT BUSES

(SUBSTATIONS) WITH RESPECT TO LINE CL15

Buses GSF values

4041 (FT41) 0.445

1044 0.146

4043 0.120

4046 0.120

1043 0.146

4061 (FT61) 0.445

1041 0.146

1045 0.146

4062 0.146

4063 0.146

4051 0.146

4047 0.120

During load shedding, we had to also make sure that the

system frequency does not overshoot. This was handled by

step by step load shedding of some magnitude depending on

the primary frequency regulation capability of the system. The

system condition after the application of the mitigation action(load shedding) is shown in Fig. 10. It can be seen that the

system has been stabilized after the proposed load shedding,

and thus the total voltage collapse has been avoided.

Fig. 10: Stabilized system after mitigation action

The system frequency increased, in this case approximately

to 50.2 Hz, immediately after the load shedding and is

stabilized with the automatic frequency regulation. In reality,

this is composed of primary frequency control by decreasing

the generators output to stop frequency increases first, then

followed by the secondary frequency control actions

(automatic or manual) to bring back frequency to the

acceptable level. It can be also noticed also that the loading of

the transmission line CL16 was reduced. It is observed also

that the power flows on some other lines such as FL6 and FL2

increase but below dangerous values. Finally, the system

voltage is recovered to more acceptable values. This has

shown that our proposed method works effectively.

Generation during

the load shedding

Output power from

GeneratorsPower flow over

some lines

Frequency in

the system

Frequency duringthe load shedding

Line loading duringthe load shedding

Voltage during theload shedding

Increase of

system voltage

Voltages



8

V. CONCLUSIONS

In this paper, a method of Zone-3 relay blocking has been

implemented and extended by the combination of the selective

load shedding scheme to prevent potential power system

voltage collapse. The method makes use of the continuous

real/time power system simulator ARISTO as a “test-bed” or a

virtual power system for implementing voltage collapse

scenarios and the preventive measures. This method aims at

avoiding the unwanted operation of Zone-3 distance relays inthe line overload conditions, and complements with selective

load sheddings as the emergency control action based on line

loading relief sensitivity factors. The simulation study has

shown that the scheme works effectively and a voltage

collapse scenario could be avoided after applying the proposed

mitigation scheme.

VI. ACKNOWLEDGEMENTS

The authors would like to thank the contribution to this work

made by Shemsedim Nursebo, Chrispin Singoyi, and

Mohammed Abdul Wasi during the course on Power

Engineering Design Project in the academic year 2009/2010 at

Chalmers University of Technology.

VII. R EFERENCES

[1] S. Larsson, and E. Ek; “The black-out in southern Sweden and eastern

Denmark,” IEEE PES General meeting , Denver Colorado, USA, June 8th 2004.

[2] G. Andersson, P. Donalek, R. Farmer, N. Hatziargyriou, I. Kamwa, P.

Kundur, N. Martins, J. Paserba, P. Pourbeik, J. Sanchez-Gasca, R.Schulz, A. Stankovic, C. Taylor, and V. Vittal, “Causes of the 2003

Major Grid Blackouts in North America and Europe, and Recommended

Means to Improve System Dynamic Performance,” IEEE PES General Meeting , Denver, Colorado, June 8th, 2004.

[3] J. W. Bialek; “Blackouts in the US/Canada and continental Europe in

2003: Is liberalization to blame?”, in proc. of IEEE PES Power Tech2005, Russia, 27-30 June, 2005.

[4] C. Taylor, “Power System Voltage Stability”, McGraw Hill Inc., 2004.

[5] S.H. Horowitz, A.G. Phadke, "Power System Relaying", 3rd Edition,Jonh Wiley & Sons Inc., 2008.

[6] Lim Seong-Il, “Zone 3 Relay Blocking Scheme to Prevent Cascaded

Events”. Transactions of Tianjin University, Volume 14, Number 2,February 2008.

[7] P. Kundur, “Power System Stability and Control”, McGraw-Hill , New

York, 1994.[8] Yuri V. Makarov, Viktor I. Reshetov, Vladimir A. Stroev, and Nikolai I.

Voropai, “Blackout Prevention in the United States, Europe, and

Russia”, Proceeding of the IEEE , Volumen 93, Issue 11, November,

2005.

[9] S. Tamronglak , S. E. Horowitz, A. G. Phadke, J. S. Thorp; “Anatomy

Of Power System Blackouts: Preventive Relaying Strategies,” IEEETransactions on Power Delivery, Vol. 11, Issue 2, April, 1996.

[10] Dr Damir Novosel, “System Blackouts: Description and Prevention,”

IEEE PSRC System Protection SC, WG C6 Wide Area Protection and

Control , Chicago, November 12

th

, 2003.[11] M. Jonsson, J. Daalder, K. Walve “An emergency strategy scheme based

on conventional distance protection to avoid complete system collapse”

IEEE PES Transmission and Distribution Conference and Exposition, Vol. 1, pp. 315-319, 7-12 Sept. 2003.

[12] D. Istardi, S. Abba-Aliyu, A. Bergqvist, N Rouch, A. Abdalrahman,L.A. Tuan, and L. Bertling, “Understanding Power System Voltage

Collapses Using ARISTO: Effects of Protection,” IEEE PowerTech 2009, Bucharest, June 28 – July 2, 2009.

[13] Wood A J, Wollenberg B F. “Power Generation Operation and Control”,

2nd Edition, Wiley Interscience, 1996.

[14] M. Moghvvemi, F. M. Omar, “A Line Outage Study for Prediction of Static Voltage Collapse,” IEEE Power Engineering Review, Vol. 18,

Issue 8, August 2002.

[15] M. Nizam, A. Mohamed, A. Hussain, “Dynamic Voltage Collapse

Prediction In Power Systems Using Power Transfer Stability Index,”

Power and Energy Conference, IEEE PECon 2006 , Putra Jaya, Malasia,

28-29 November, 2006

[16] T. A. Evers, C. L. Pierre, G. L. Lebby, Y. D. Song; “Prediction of Voltage Collapse in Power Systems,” Proceedings of the ThirtiethSoutheastern Symposium on System Theory 1998, Morgantown, United

States, 8-10 March, 1998[17] CIGRE TF 38-02-08, "Long Term Dynamics Phase II", 1995.

[18] Svenska Kraftnät, “ARISTO user guide”, 1993-2006.

VIII. BIOGRAPHIES

Kalid Jemal Yunus was born in Mechara, westernharage, Oromia Regional state, Ethiopia on July 6,

1983. He graduated from Arba-Minch University in

Electrical Engineering in 2006 and has served as an

assistant lecturer from 2006-2008 in Haramaya

University. Currently, he is studying master degree inElectric power engineering at Chalmers university of

Technology. His field of interest is renewable energy

technologies, power electronic, power systems.

Gustavo Pinares Ccorimanya was born in Lima,

Peru, on June 11th, 1981. He graduated from

Universidad Nacional de Ingeniería on 2003 and

worked for Red de Energía del Perú from 2004 to2008 as a protection engineer. Currently, he is pursuing a master degree in Electric Power

Engineering at Chalmers University of Technology.

His fields of interest are power system protection and power electronic application in power systems.

Le Anh Tuan (S’01, M’09) received his Ph.D. in2004 in Power Systems from Chalmers University of

Technology, Sweden, and his M.Sc. degree in 1997

in Energy Economics from Asian Institute of Technology, Thailand. Currently he is a senior

lecturer at the Division of Electric Power

Engineering, Department of Energy and

Environment, Chalmers University of Technology,

Sweden. His research interests include power system

operation and planning, power market and

deregulation issues, grid integration of renewable energy and plug-in electricvehicles.

Lina Bertling (S’98-M’02-SM’08) was born in

Huddinge, Sweden, in 1973. She has a Professor

Chair in Sustainable Electric Power Systems and isHead of the Division of Electric Power Engineering,

at the Department of Energy and Environment, at

Chalmers University of Technology, in Gothenburg,Sweden. She has been with Svenska Kraftnät, the

Swedish Transmission System Operator during

2007-2009, and from June 2008 as head of the

R&D. She has been with KTH School of Electrical

Engineering, in Stockholm, during 1997-2009 where

she finalized her Docent degree, Associate Professor, in 2008, and the Ph.D.in 2002, both in Electric Power Systems. Her research interests are in

transmission and distribution systems including high voltage equipment and

HVDC, and wind power systems with applications for reliability assessmentand modeling, and maintenance planning.

Dr. Bertling is a senior member of IEEE and a member of Cigré, Cired,

World Energy Council, and the Royal Swedish Academy of EngineeringSciences. She was the general chair of the 9th International conference on

probabilistic methods applied to power systems (PMAPS) in Stockholm, in

2006 and is the chair of the first IEEE PES Conference on Innovative SmartGrid Technologies Europe 2010 in Gothenburg in 2010.

a combined zone-3 relay blocking and

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