[ieee 2011 first international conference on informatics and computational intelligence (ici) -...

Cascading Collapse Assessment Considering Hidden Failure

1Nur Ashida Salim

1Faculty of Electrical Engineering

Universiti Teknologi MARA

13500, Penang, Malaysia

nurashida.salim@gmail.com

2Muhammad Murtadha Othman

2Ismail Musirin

2Faculty of Electrical Engineering

Universiti Teknologi MARA

40450, Shah Alam, Malaysia 2mamat505my@yahoo.com

2ismailbm1@gmail.com

3Mohd Salleh Serwan

3Advanced Power Solutions Sdn. Bhd

Worldwide Business Centre,

Jalan Tinju 13/50,

40000, Shah Alam, Selangor 3serwan@aps-my.com

Abstract — Hidden failure relay protection is the major cause

of cascading failure in power system. Therefore, in this study, a

hidden failure model has been developed to study the impact of

certain parameter that could cause cascading collapse. The

parameters that could lead to major blackout include system

loading level, spinning reserve, hidden failure probability and

other factors. As the overall load is the key factor that could

affect the risk of cascading outages, this study will reveal the

impact of it to the system. A test system of IEEE 24 bus RTS is

used as a case study. The hidden failure model adopts here is

the steady state analysis, which is caused by line tripping. The

significant loads at which blackout risk sharply increases are

identifiable for cascading collapse. This study can provide

guidance for the utility on when and how to mitigate the

cascading collapse from spreading to the entire power system.

This study also can determine the critical loading in the risk of

cascading failure.

Keywords – power system reliability; cascading collapse; hidden

failure;

I. INTRODUCTION

In a deregulated power system, the aim of the utility is to supply electricity in a reliable, secure and economical manner[1]. Therefore, each utility company is competing among themselves to provide such quality energy. For that reason, they are trying to avoid any disturbances affecting the system. One of the disturbances that could cause danger for the power system to operate effectively is cascading collapse.

Cascading collapse is continuous outages of components in a power system network. Even though the disturbance rarely happens, but if it does happen, it would disturb the whole system. For worse cases of power system outages, it could lead the whole system to blackout. Cascading failure happens when a component in the power system fails to operate properly and trip. Then the faulted component can affect other components that are connected to it. This situation will go on until the entire system collapse if prevention does not take action fast.

Some major blackouts caused by cascading failure have been reported in [2-4]. According to those reports, most of the cascading failure occurs during ‘shoulder’ periods, which is during spring or fall, and also when the lines or generators is outage due to service or maintenance. This results in higher probability of a cascading outage caused by the

unexpected forced outage of the components near to the faulted one.

In this research a cascading collapse assessment is performed by taking into consideration the total load variation in the system. Here, as the overall load in the system increases, the severity of the system is monitored in terms of its average probability distribution function. The system is in stable condition if the curve shows indication of some exponential decay. However, if the curve shows a power tail, therefore the system is in unstable condition. The critical loading is identified during this condition. The test system used for this case study is the IEEE 24 bus RTS system.

II. CASCADING COLLAPSE MODEL

Throughout the history of the interconnected power

system, disastrous outages of the electric power systems

have been occurring for quite some time. Cascading

collapse is the one of the main reason of the major blackout.

Therefore, actions need to be taken to analyze the cascading

collapse so that it could be mitigated. Some models of

cascading collapse analyses used nowadays are listed below.

A. OPA model

OPA model that has been studied in [5-7] is a blackout model in power system that represents probabilistic cascading line outages and overloads [8]. OPA looked into the overall dynamics in the network blackouts. Its initial outage is generated by random line outages and load variation. When line outage happened the new solution is obtained. Linear programming (LP) and DC load flow is modeled in OPA aiming to reduce the cost function. The overall process basically is to generate a possible cascade of failures and the LP dispatch optimization is obtained.

B. CASCADE model

Other model to model blackout in power system is by

using CASCADE model. CASCADE model that has been

explored in [7, 9, 10] is a probabilistic model that the

cascading is depending on the loading. The initial

disturbance is created by increasing the load to the

components and caused outage. The situation continues as

the load of each components increased. Even though this

model can analyze major blackouts, it assumes all

2011 First International Conference on Informatics and Computational Intelligence

978-0-7695-4618-6/11 $26.00 © 2011 IEEE

DOI 10.1109/ICI.2011.59

318

2011 First International Conference on Informatics and Computational Intelligence

978-0-7695-4618-6/11 $26.00 © 2011 IEEE

DOI 10.1109/ICI.2011.59

318

transmission lines are the same. It also neglects the network

configuration while performing the redistribution during

overload.

C. Hidden Failure model

Of all the failures occurred in a power system, the ones

that remain hidden are the most crucial. According to [11],

more than 70% of power system major disturbances

involved hidden failure protection system. Ref. [9, 11, 12]

adopts hidden failure model to study the distribution of rare

events. It uses DC load flow during the simulation and

performs tripping until the system collapse.

III. CRITICAL LOADING

It is sure that as load in the power system increases, the

possibility of a blackout to happen is more likely to happen.

In a complex network, criticality is associated with power

tails in the probability distributions [13].

The critical loading is important in power system

operation because it identifies a reference point for rising

risk of large disturbances[14]. If the curve of probability

distribution shows some indication of power tail, it indicates

bad situation could happen to the network. Other than that,

there is also a gain in the economics point of view. One of

the aims of exploring the risk analysis of cascading failures

is to identify and quantify the tradeoffs so that early defense

actions can be made. The concept of load increment on the distribution of

blackout size is shown in Table. I. If the network is operating at a very low loading level, each component has a minimum impact of failure. This could result a large operating margins of that components. Nonetheless, if the system is operating at a very high loading, each component is operating near their operating limit. As a result, if an initial outage happens, it would cause cascading outages, leading to a total or near total blackout.

IV. HIDDEN FAILURE MODEL

During normal operating condition, hidden failure

cannot be detected [15]. However it will exposed as a

straight effect of further system disturbances. Hidden failure

could cause a relay system to incorrectly separate circuit

elements[16]. In this study, line protection hidden failure is

adopt to model the operation of protection relays.

Each line has a different probability of tripping depends

on the load. In this study, it is modeled as an increasing

function of the line flow as seen by the line relay. The

probability is at a pre-determined value below the line limit

and will increase linearly up to 1.4 times of the line limit.

The probability of incorrect line tripping is modeled as in

Fig. 1[12].

TABLE I. LOG-LOG PLOT FOR DIFFERENT TYPES OF LOADING LEVEL

Log-log plot Loading Level Characteristic

Very Low Load Exponential tails

Critical Load Power Tail

Very High Load Total blackout

likely

Figure 1. Probability of an exposed line tripping incorrectly In hidden failure model, DC load flow approximation is

adopted in the simulation. This is due to the linearized, lossless power system which is equivalent to a current source in a resistive circuit. Here, the transmission lines are considered like resistors along with the generation and load is current sources and sinks.

Here, the model uses DC load flow is a method to estimate power flows through an AC system, assuming that the entire system has a voltage magnitude of 1.0 per unit. It also neglects the transmission line resistance. DC load flow solution is non-iterative. It has the solution of convergence at every simulation.

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V. CASCADING COLLAPSE ALGORITHM

The simulation procedure starts from a base case load

flow and follow the following steps. The procedure is

repeated for N time to obtain the statistical distribution of

the blackout.

1) Increase load at each load bus. Select an initial line as the

triggering line and trip that line. Perform the DC load

after each tripping.

2) Check for line flow violations and trip the line upon

violation.

3) If there is no more violation, determine the currently

exposed lines, which are all lines that are connected to

the last violated lines.

4) Determine the probability of incorrect tripping for each

exposed line according to Fig. 1.

5) For each exposed line/generator, generate a random

number to determine whether the line/generator tripped.

(The exposed line/generator will trip if its probability of

incorrect tripping is greater than the random number

generated)

6) For the exposed lines, determine the conditional

probability of tripping, Pcj for each stored exposed

line/generators as in equation (1).

( )∏∏ −=didnt trip that lines all

j

that triplines all

jcjp1 p P

(1)

7) Record the lines that tripped.

8) Compute and plot the probability distribution function

(PDF) for the cascading outage.

9) Repeat until no lines are loss or all lines connected to any

bus are tripped (blackout).

The overall flow chart for the algorithm of cascading

collapse is depicted in Fig. 2.

Figure 2. Overall flow chart for cascading collapse

VI. RESULTS & DISCUSSION

The simulation uses the IEEE 24 bus RTS as shown in

Fig. 3. This system has two areas with three generators in

area one and eight generators in area two[17]. For each

generator in the same area, it is assumed to own by the same

owner. As for the loads also, for each load in the same area,

it belongs to the same owner. The simulation starts from a

base case load flow. A line is selected as the triggering

event and the following procedures is repeated N times.

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Figure 3. Single line diagram for IEEE 24bus RTS

In this study, the outages correspond to the internal

cascading processes is the transmission line outages. With a

line tripping as the initial triggering event, the algorithm is

simulated for several times to get the accumulated statistics

of the probability distribution function (pdf) of blackout

size. Here, the overall loading is varies from very low up to

very high loading.

At a very low loading, the impact of cascading collapse

to occur is very minimal. During this condition, the

components have large operating margin that could make

them secure for any failure. However if the power system is

operated recklessly at a very high loading, each components

in the system will operate near to its emergency operating

limit. Therefore, the tendency for the system to collapse

with an initial outage is high.

It is obvious that the pdf of the blackout size changes

from the exponential tail form to the certain total blackout

form as the overall loading increases.

Figure 4. Variation of pdf with loading

Fig. 4 shows the average pdf as a function of loading

level for the IEEE 24 bus RTS network. From 100% of the

loading level until up to 200%, the average pdf for the

system to collapse is significantly small until it approaches

to zero. As the loading level increases above 200%, the

average pdf increases. From the curve, it can be seen clearly

that the change in slope occurs near loading of 210%. At

this point of loading level, the pdf start to increase as the

loading level increases.

Figure 5. PDF of blackout at 200% loading

Fig. 5 shows the average pdf of blackout as function of

loading. Here, the loading level is 200% of the overall total

loading. The curve shows an exponential decline in the

average pdf. This implies that the system is still in stable

condition.

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Figure 6. PDF of blackout at 210% loading

Fig. 6 shows the average pdf of collapse at loading level

of 210% of the accumulated load in the system. During this

loading level, the curve still shows an exponential decay in

the average pdf. This also implies that the system is still in

stable condition.

Figure 7. PDF of blackout at 220% loading

Fig. 7 shows the average pdf of collapse at loading level

of 220% of the total load in the system. At this loading

condition, the curve still shows an exponential decay in the

average pdf. At this condition, the system is still in stable

condition.

Figure 8. PDF of blackout at 240% loading

Fig. 8 shows the average pdf of blackout at loading level

of 240% of the accumulated load in the system. During this

loading level, the curve shows some indication of power

tail. From the curve, the critical loading at which the system

starts to become unstable can be identified.

The results obtained for IEEE 24 bus RTS is quite

similar to those using the OPA model for IEEE 118 bus

system as in [18, 19] and hidden failure model for WSCC

179 bus system performed in [9]. However, by using the

CASCADE model as in [9, 20] the results obtained

qualitatively similar but the results are sharper.

From the results obtained, hidden failure and OPA

model presents similarity in the loading assessment for

probabilistic cascading outages that could cause cascading

failure due to the criticality in loading level. The

significance of this research is that it can exactly monitor

the critical loading as it is one of the parameters that have to

be concerned in the power system operation. The threat of a

major disturbance could be reduced by reducing the overall

loading of the system in order to obtain an exponential tail.

By performing this analysis, the system operator could find

the loading margin to the critical loading as a preparation to

face large blackouts.

VII. CONCLUSIONS

With the development of power market, power system

are forced to operate near the critical loading as proposed in

[5, 19]. This is because, the industry need to supply as much

electricity as possible in order to compete among other

utility. However, by implementing this analysis in their

system operation, the chances of a large blackout to happen

can be reduced. A hidden failure mechanism has been

developed using a DC load flow model to study the

behavior of cascading collapse of a transmission network

during the variation of overall loading level in the system.

This shows that the power system will follow power law

near the critical loading. Also, the average pdf will increase

sharply as the load increases. Although the DC model of

hidden failure presents a simplified system than the real

system operation, it is a benchmark for further research to

fully understand the idea of cascading failures. This research

could be further pursued in the dynamic analysis where the

frequency violation is monitored with an initial generator

tripping.

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