Micro Grid Architecture for Line Fault Detection and Isolation

Maneesha Vinodini Ramesh, Neethu Mohan and Aryadevi Remanidevi Devidas

Amrita Center for wireless Networks and Applications, Amritapuri, Clappana P. O.,

Kollam, Kerala, India

Keywords: Micro Grid, Line Fault, Intelligent Module, Wireless Communication.

Abstract: One of the major problems power grids system face today is the inability to continuously deliver power at

the consumer side. The main reason for this is the occurrence of faults and its long term persistence within

the system. This persistence of faults causes the cascading failure of the system, thereby adversely affecting

the connected loads. Traditional methods of fault isolation cause the shutdown of power to a large area to

maintain the system stability. Today, localization of faults and its isolation is doing manually. Therefore, a

localized fault recovery mechanism is very essential to maintain the system’s stability after the occurrence

of a fault. In this paper, we have developed fast fault detection and isolation mechanism for single phase to

neutral line fault in a three phase islanded micro grid scenario. The fault detection and isolation during the

islanded operation mode of a micro grid is very critical, since bidirectional power flow is present. The fault

detection mechanism we developed can detect and isolate the fault within a few milliseconds and localize

the fault within a two second delay for both in single and bi-directional power flow scenarios. The proposed

system is capable of locating the exact faulted segment with the aid of the communication network

integrated into the power grid. The implemented system was tested with different ranges of fault current and

the analysis showed that the proposed system could localize the fault with less than a two second delay.

1 INTRODUCTION

The frequency of fault occurrence of the secondary

distribution grid as compared to the primary side is

considerably high. Most of the faults in a power

system results in a huge variation of electrical

parameters which will badly affect the operation of

the loads. In today’s distribution grid, whenever a

fault occurs in any part of the distribution grid, that

fault should be isolated from the distribution

transformer. This condition causes a long term

power cut in majority of the grid.

A micro grid is a small scale distribution

network, which is designed to provide power for a

local community. Whenever an abnormal condition

occurs in the main grid, the micro grid can work in

island mode. During the islanded mode of operation,

power sharing is present within the micro grid. The

power flow within the network is bidirectional,

which is based on the power demand. In order to

develop a fault detection mechanism in an island

micro grid scenario, the direction of power flow

should also be known.

In this paper, we proposed a three phase micro

grid system. This micro grid system includes smart

homes, which can act like a power supplier as well

as a consumer, and intelligent modules which are

present at each distribution pole. Most of the fault

detection and isolation mechanisms, which had

proposed previously in other works for a micro grid

system, were mainly in DC system. In most of the

previous work, fault detection and isolation

mechanism for micro grid system has done in the

DC system. Furthermore, most of the works used

ring type architecture for this DC micro grid system.

In this paper, we considered the AC micro grid

system with radial architecture. By considering this

system, we developed and implemented an

automatic fault detection, isolation and fast fault

localization mechanism.

The rest of the paper is structured as follows:

Section 2 presents the related works, section 3

explains the proposed system architecture, section 4

gives the fault detection and isolation method,

section 5 gives the fault localization method, section

6 gives the hardware design, section 7 gives the

hardware implementation, section 8 gives the

experimentation and analysis and section 9 gives the

conclusion.

250

Vinodini Ramesh M., Mohan N. and Devidas A..

Micro Grid Architecture for Line Fault Detection and Isolation.

DOI: 10.5220/0005454002500255

In Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS-2015), pages 250-255

ISBN: 978-989-758-105-2

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

Figure 1: Three phase islanded micro grid architecture for fault detection and isolation.

2 RELATED WORK

A fault protection and isolation scheme for a DC

micro grid system was proposed in (Jae-Do and

Jared, 2013). In this scheme, the authors used the

current sensor to detect and isolate the fault with the

help of a master and slave controller, which is

associated with every segment of this loop type

micro grid system. But in the island mode of

operation, the protection schemes for the micro grid

system may be entirely different from the traditional

protection scheme since bidirectional power flow is

present. Different types of fault which occur at three

phase distribution system were compared in

(Cheraghi and Goodarz, 2011). The simulation

depicted that the magnitude of the fault current

varies widely for different types of fault in a three

phase system. In order to develop a protection

scheme for this system, knowledge about this huge

fault current was vital. An overview of the existing

protection schemes for the micro gird was given in

(Buigues, 2013). The protection scheme for a micro

grid should be tolerable to the dynamic topological

change due to changes in the connection and

disconnection of generators, load centres, storage

system and other switches.

A fault current detection method by analyzing

the current conditions at different relay locations did

in (Sanaye-Pasand and Khorashadi-Zadeh, 2003).

Whenever a fault occurs at the transmission line, the

current at each the relay location was subject to

change. The principle of variation of the current

sensor before and after the fault incidence was used

for fault detection and its classification in this work.

An over current protection for a micro grid

system with the help IED has been proposed in

(Voima, Kauhaniemi and Laaksonen, 2011).

According to them, a new over current protection

scheme is needed for a micro grid system when it is

operating islanded mode since the change in the

operating condition from grid connected mode to

islanded mode causes a drastic change in the

distribution network parameters. Detection of a fault

is done in this paper with the help of the

telecommunication communication system in

association with IEDs.

An approach of using wireless sensor networks

to power grid monitoring was given in (Fateh,

Govindarasu and Ajjarapu, 2013). According to this

paper, even though the bandwidth and latency was

the main bottlenecks for using wireless sensor

networks in a smart grid scenario, proper design of

the network could make wireless sensor networks

the best solution for power grid monitoring. The

authors used a hierarchical wireless sensor network

in this paper. Different communication technologies

and its requirements which are applicable in a smart

grid scenario were addressed in (Fateh, Govindarasu

and Ajjarapu, 2013).

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Analysis of different communication

technologies gave in this paper with different

communication requirements like latency, reliability,

frequency and security. Study of wireless sensor

network for smart grid monitoring application gave

in (Gungor and Hancke, 2010). The authors did an

experimental study of WSN at different power grid

scenario and found that it can meet most of the

communication requirements needed for smart grid

communication.

3 MICROGRID ARCHITECTURE

FOR FAULT DETECTION AND

ISOLATION

In this work we considered a three phase micro grid,

which operates in islanded mode. Each smart home

in this system had the capability to generate power

from a renewable energy resource and stored it. In

order to maintained the system self sustaining, the

extra power generated within the system could share

among the load centres according to the power

demand. This sharing of power between the loads

was vital since the micro grid was not connected to

the regular power grid source. The system

architecture of the proposed system is given in

Figure1.

In the figure 1, the micro grid has nine

distribution poles named as Pole 1, Pole 2 …Pole 9

and each distribution pole is connected to each smart

home. In this work we considered only single phase

loads which were equally distributed along three

phases. We assumed that every load had a renewable

energy source and it will act both as a load and

generator. The extra power produced can also be

stored. The smart meter which was present at each

smart home can continuously monitor the

bidirectional power flows into the home as well as

away from the home. Since a three phase

distribution grid was considered in this work, the

distribution pole will have three power lines. In

order to monitor the three phase lines, we needed to

use three intelligent modules at each distribution

pole. If we have only had one intelligent module to

monitor the three phase lines, failure of this

intelligent module could cause the three phase lines

unobservable. Thus, intelligent modules for each

phase line would improve the robustness of the

system. At each distribution pole, the breakers

associated with an intelligent module. A control

station associated with the micro grid to control and

take decision according to data of the system.

4 FAULT DETACTION AND

ISOLATION METHOD

Power sharing is one of the key features of the

proposed micro grid system. Faults which may occur

in this three phase micro grid could cause the system

to unbalance and prevent the power sharing.

Therefore, a fault detection and isolation mechanism

is very essential for the continuous operation of the

system. In this work, only the single line to neutral

fault was considered since 95 % of the fault occurs

within a three phase system was this type of fault.

Each distribution pole was associated with three

intelligent modules for each phase line. Each

intelligent device was connected to a current sensor,

voltage sensor, circuit breaker, communication

module and a micro controller unit. These sensors

along with circuit breakers and communication

modules were connected to the micro controller. The

block diagram of an intelligent device is shown in

Figure 2. Current sensors and voltage sensors

continuously monitored the current and voltage

condition at each phase line. The processor unit at

each intelligent device continuously checked

whether the current values exceeded the allowable

lower and upper threshold limit. If the current sensor

value had exceeded the threshold limits, the circuit

breaker present at that phase line opened the circuit.

5 FAULT LOCALIZATION

METHOD

After the fault detection and isolation the intelligent

device continuously sent the sensed current value to

its neighbouring distribution pole’s intelligent

device. Whenever an intelligent device received a

message from its neighbour, it compared the

received value with its own sensed value. Each

intelligent device took one of the two decisions after

this comparison.

a. If the difference in current values of the

adjacent intelligent module was not a high

value, then no fault occurred between the two

poles and the status of the breaker was closed

condition.

b. If the difference in current values of the

adjacent intelligent module was a high value

then a fault occurred between the two poles and

it opened the breaker associated with that phase

line.

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Figure 2: Block diagram of intelligent device.

Thus the breaker associated with the exact fault

location opened and the other breaker remained in

the closed. This helped to exactly locate the fault

within this islanded micro grid. The main advantage

of this localized fault isolation was that it avoids the

entire system shut down during faulted condition.

Besides, the other part of the distribution grid

remained in stable condition.

After localization of fault, the intelligent module

sent the information about fault location and the new

status of breaker condition to the control station. The

fault detection and isolation resulted in the formation

of two nano girds. These two nano grids could be a

power demanded region or power balanced region.

To change the power demanded region to a power

balanced region, the power re-routing mechanisms

could be introduced in future.

6 HARDWARE DESIGN

Fault detection and isolation had an important role

for maintain the stability of the proposed micro grid

system. A segment of the proposed micro grid

system with automatic fault detection and isolation

mechanism in a single phase system was

implemented in our laboratory. In this work, two

intelligent modules which were to be present at each

distribution pole have developed. Hardware

architecture of an intelligent module gave in Figure

Whenever a fault occurred, the current and voltage

value changed. Therefore, in our system we used

these parameters to determine the fault condition.

Even though the fault was detected from the current

value, we also monitored the change in voltage in

our system. According to (Rebekah Hren Brian,

2011) the voltage drop for feeders should not exceed

2% and the voltage drop for branch circuit should

not exceed 3%, for efficient operation. In our

system, the voltage was continuously monitored to

ensure its variation has limited in this range.

Figure 3: Hardware architecture of an intelligent module.

Since the short circuit current due to single phase to

neutral line fault was very high, we have generated a

scaled down version of this high fault current in this

system to ensure the safety. The current sensor used

to monitor the over current should have had the

capability to tolerate our scaled down version of

over current. The current sensor with good

resolution would have increased the accuracy of

measurement. A transformer, which can provide

good isolation was calibrated in the voltage range of

44V to 240V and used as a voltage sensor in this

system since the RMS voltage used was 240V.

Consider figure 3. A signal conditioning circuit was

used in association with these sensors to manipulate

the sensor output in such a way that it met the

requirements for the next stage for future processing.

Since the output voltage range of the current sensor

was very small, we needed to amplify this voltage to

a range which could be easily detectable by the

micro controller. For that we used a signal condition

circuit with the selected current sensor. This would

also improve the resolution of the sensor. Since the

output voltage of the current sensor was in an AC

voltage range of 0-6V, we needed to manipulate the

signal in such a way that it could be given to the

micro controller unit. We needed a micro controller

unit of ADC resolution of atleast10 bit with good

operating speed. We selected PIC as our micro

controller unit since its ADC can provide required

resolution and have a wide operating voltage range

of 2V to 5.5V. Besides, it had a program memory of

8Kbytes and data memory of 368bytes and had a

good operating range of 20 MHz.

In the hardware implementation, we used relay

module for fault isolation. The relay module needed

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for our system should have good ampere range so

that it could be controlled easily. In this system we

selected a relay with 30A current range with an

operation voltage of 12V DC. A communication

module was needed to implement the localization of

fault. The intelligent module was present at every

distribution pole and the distance between these

distributions poles were 40-60 meter. Therefore, our

communication module should have had a

communication range greater than this distance and

should have operated in unlicensed frequency band.

In order to power up the entire module from the

main supply, a step down transformer was needed.

Since the circuits in this intelligent module needed a

voltage of 0- 5V, we used a step down transformer

of 230 V to 6V and then the required voltage was

taken through regulators.

Each intelligent module had a current sensor and

a voltage sensor. These sensors continuously

monitored the current and the voltage condition of

the power line. The sensors were connected to the

micro controller unit through a signal conditioning

circuit. There was a circuit breaker connected with

the power line which helped to isolate the line when

anomalous conditions occurred. Operation of the

relay was controlled by the processor unit with the

help of a driver circuit. The XBee module present at

each intelligent module helped to communicate with

the neighbouring unit so that the intelligent module

could exactly locate the faulted part of the grid.

There was a display associated with the micro

controller unit. It indicated the current and voltage

condition of the line continuously. The power supply

module associated with this system took power

directly from the line and made it suitable and

available for all the circuits present within each

individual intelligent module.

7 HARDWARE

IMPLEMENTATION

We developed two intelligent modules in this

hardware. These modules were connected to a power

supply line and were tested with different load

conditions.

We used an ACS 714 current sensor with a

maximum current rating of 5A and a sensor

transformer with a voltage rating of 30-300V with a

current rating of 500mA. The micro controller unit

used in this module was PIC16F877A since it met

all the requirements for this design. An XBee

module with 2.4GHz frequency with 0dBm power

output was used in this project for wireless

communication (Rhidolabz, 2014).

The two intelligent modules were developed and

connected with the power line. Whenever we

simulated a faulted current within this system, the

two modules sensed the faulted current and

immediately tripped and communicated together and

exactly isolated the faulted part. After detecting the

faulted section, it isolated this part and maintained

the system’s stability.

Figure 4: Hardware implementation of intelligent module.

8 EXPERIMENTATION AND

ANALYSIS

We have tested the system with resistive and

inductive loads.

Figure 5: Integrated system.

In this test we have generated different scaled down

fault current and observe tripping time variation.

Test has done with both resistive and inductive

loads. Table 1 and table 2 show the fault current test

of intelligent module I with resistive loads and

inductive loads respectively.

Table 3 and 4 gave the fault current test of

intelligent module II with resistive and inductive

loads respectively. From the fault current test we

found that our system could locate the fault at

different over current conditions with almost the

same delay.

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Table 1: Fault current test of intelligent module I with

resistive loads.

Fault Current (in %) Fault localization time (sec)

115 1.15

163 1.06

190 1.16

211 1.05

238.3 1.15

Table 2: Fault current test of intelligent module I with

inductive loads.

Fault Current (in %) Fault localization time (sec)

133 1.19

195 1.15

Table 3: Fault current test of intelligent module II with

resistive loads.

Fault Current (in %) Fault localization time (sec)

116 1.01

133 1.02

163.33 1.02

200 1.1

Table 4: Fault current test of intelligent module II with

inductive loads.

Fault Current (in %) Fault localization time (sec)

133 1.12

195 1.28

9 CONCLUSIONS

Three phase micro grid architecture capable of

automatic fault detection and isolation mechanism

was proposed in this paper. The bidirectional power

flow inside the islanded micro grid made the fault

detection mechanism more challenging. A fault

detection mechanism developed in this work could

detect and isolate the fault and make the remaining

part of the grid in a balanced condition. The

proposed system was tested with different fault

current conditions and the results showed that the

proposed system could localize the fault within a 2

second delay. Even though a single phase to neutral

fault was very common in a three phase distribution

power system, other types of faults and its

occurrence was also important. Automatic fault

detection and localization of fault could not make

the system balanced. New approaches to power re-

establishment after fault detection and isolation

could also be done as future work.

ACKNOWLEDGEMENTS

We would like to express our sincere gratitude to our

beloved chancellor Sri. Mata Amritanandamayi Devi

(AMMA) for the immeasurable motivation and

guidance for doing this work.

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