cellular communication based remote predictive … · 2015. 8. 31. · cellular communication based...

http://www.iaeme.com/IJEET/index.asp 48 [email protected]

International Journal of Electrical Engineering & Technology (IJEET)

Volume 6, Issue 7, Jul-Aug, 2015, pp.48-60, Article ID: 40220150607005

Available online at

http://www.iaeme.com/IJEETissues.asp?JTypeIJEET&VType=6&IType=7

ISSN Print: 0976-6545 and ISSN Online: 0976-6553

© IAEME Publication

___________________________________________________________________________

CELLULAR COMMUNICATION BASED

REMOTE PREDICTIVE MAINTENANCE

SYSTEM FOR POWER TRANSFORMERS

Pallav Gandhi

M. Tech Student, Instrumentation and Control Department,

Nirma University, Ahmedabad, India

Dipak Adhyaru

Professor, Instrumentation and Control Department,

Nirma University, Ahmedabad, India

ABSTRACT

The Insulating Paper and Pressboards are used to insulate the windings of

transformer. These are mostly made from a Cellulose material. It must have a

high tensile and dielectric strength. Over the era the insulators have slowly

degraded due to ageing, high temperature and chemical reaction such as

oxidation, pyrolysis and hydrolysis. They are degraded to a point, and now

there is no extensively effective insulator. Mainly two parameters are affecting

on life of insulator and that is load current and ambient temperature.

This Paper proposes a system which estimates loss of life of Transformer.

The proposed system is composed of Energy Meter, Embedded ICM that is

heart of the system, and GPRS Gateway. It is installed at the power

transformer site. Here the three phase Energy meter is being used as

MODBUS slave, having electrical parameters such as voltage, current, power

factor, power, etc. All these parameters are sent to the MODBUS master via

MODBUS RS485. The Embedded ICM contains the Microcontroller with

MODBUS Master Function, Advance Insulation Ageing Algorithms, Power

Supply, and RS485 Communication Circuit. The Advanced Insulation Ageing

Algorithms computes the Top-oil Temperature, Hot-spot temperature, Ageing

Rate, and Loss of insulator life. This algorithm is based on IEC 60076-7

standard differential equation and all these things (algorithm) are

implemented in MSP430F5419A. These estimated parameters will be sent to

GPRS Gateway via RS232. GPRS Gateway will connect to remote location

using GPRS technology and Provide data to Remote Server. Remote Server

will have SCADA system so the data can be stored for multiple years and same

data will be utilized for advanced algorithm development.

Cellular Communication Based Remote Predictive Maintenance System For Power

Transformers


Keywords: Transformer, Hot-spot temperature, Insulation, GPRS Gateway,

Energy Meter, MODBUS Master, MODBUS Slave, Ageing Rate, Loss of Life

Cite this Article: Pallav Gandhi and Dipak Adhyaru, Cellular Communication

Based Remote Predictive Maintenance System for Power Transformers.

International Journal of Electrical Engineering & Technology, 6(7), 2015, pp.

48-60.

http://www.iaeme.com/IJEET/issues.asp?JTypeIJEET&VType=6&IType=7

_____________________________________________________________________

1. INTRODUCTION

The insulation paper and pressboard is made from high grade of cellulose. Cellulose is

an organic polymer [1] whose monomer is made of long chain of glucose ring. The

tensile strength of insulator is measured by the degree of polymerization value. The

average number of glucose ring per chain is called the degree of polymerization [1-2]

and it can be used to monitor the ageing of paper. The typical DP (Degree of

Polymerization) value for unused insulator is around 1000 to 1200 [1]. When the

insulator ages, the glucose long chain breaks into smaller chains; gradually the DP

value falls. If the DP value of insulator is found to be 200 or less then that [1-2] then it

is generally considered to be its end of life.

2. INSULATION LIFE

The insulator is continuously suffering from the electrical, mechanical, thermal, and

chemical stresses [3] during its operation. In this paper, the insulator life prediction is

mainly focused on thermal degradation of paper insulation. According to the IEEE

C57.91 the normal life of the insulator is 20 to 21 years [4]. The life of insulator will

be defined for the given temperature of the insulator. The total life between the initial

state for which the insulation is considered new and final state for which electrical

failure, dielectric stress and mechanical [1] movement occurring in normal life have

been considered. So it is essential to select good cellulose paper having good

mechanical strength. The electrical and mechanical strength of insulator is mainly

dependent on the ambient temperature, operating load, hot-spot temperature and

different physical and chemical process of the transformer [4].

3. AGEING FACTOR

The dielectric strength of insulator mainly depends on the moisture content of the

insulator, temperature, and the content of the oxygen and acid. The temperature of the

insulator is main factor for ageing agents [5-6]. The maximum temperature of the

insulator is used for calculation of ageing of insulator. The insulation ageing is very

complex process. Due to rapid increase in load leading to increase in hot-spot

temperature causing the thermal decomposition of insulator [7]. There are mainly

three mechanisms which contribute to cellulose degradation i.e. hydrolysis (water),

oxidation (oxygen), and pyrolysis [1, 8-10] (thermal degradation).

3.1. Hydrolysis

The ingress of water from the atmosphere or ageing of insulation paper causes the

breaking of the glucose chain [9], i.e. The oxygen bridge between glucose rings is

affected by water molecules, causing a break in the cellulose chain and creates two –

Pallav Gandhi and Dipak Adhyaru


OH groups, each attached to its ring. The Result is degradation in DP value and

weakening of the insulator [9].

This also leads to decrease in the mechanical life of the insulator by half for every

two molecule of water [1]. Therefore, the thermal deterioration of insulator is

proportional to the water particles. For example, reducing the water particles of the

insulator from 1% to 0.5% doubles the life of the insulator. According to Lundgaard

study from SINTEF energy research shows that if the insulator’s normal life is

defined as ageing under well dry and oxygen free conditions, for 1% water contents in

insulator the life of the insulator decreases t to 60% of the normal life. If the water

content increases to 3% - 4% then the life assessment will fall to 25 % of normal life

[10].

3.2. Oxidation

The main source of oxygen molecules comes from either atmosphere or from the

thermal degradation of insulator. Oxygen molecule attacks [9] the carbon atom in the

glucose monomer and form aldehydes, carboxylic acids, and ketones. The bonds

between rings are weakened which causes degradation of DP [10].

3.3. Pyrolysis (Effect of Heat)

The main source of heat generation in the transformer is due to winding temperature

and this is termed as hot-spot temperature. This heat will cause the breakdown of

individual monomer of the long chain [9]. The insulator decomposes rapidly if its

temperature is above 140 . Sometimes due to the high temperature there is reduction

in DP value of insulator and the insulator becomes brittle; the result is solid residue

and gases are formed. The formations mainly consist of carbon dioxide, hydrogen,

water vapour and carbon monoxide. Further glucose rings decomposes to other

compounds called furans [10].

4. INSULATOR AGEING RATE

The ageing of Insulator is a time function depending on the temperature, oxygen

content, moisture content, and acid content. The temperature distribution in the

insulator is not uniform, [6, 9-10] making it a complex process. The part which is

operating at the highest temperature undergoes [8] the highest deterioration.

Therefore ageing rate is the rate at which the deterioration of insulator for a hot-

spot temperature is accelerated compared with the degradation rate at the reference

hot-spot temperature. The relative ageing rate V is defined by equation (1) for non-

thermally upgraded paper and equation (2) for thermally upgraded paper [11].

(1)

(2)

Where,

is a hot-spot temperature in

110 is rated reference hot-spot temperature for thermally upgraded paper

98 is rated reference hot-spot temperature for non-thermally upgraded paper


Transformers


5. INSULATION LOSS OF LIFE

The loss of life over a period is equivalent to life consumed by the insulation in hours

or days during that period [9]. Mathematically it is calculated by integrating the

relative ageing rate over certain period of time.

The loss of life (L) over period of time is equal to [11]

(3)

And in discrete-time form over a number of time intervals,

(4)

Where,

is relative ageing rate during interval n

is nth time interval

n is number of each time interval

N is total number of interval during the period

6. MODBUS RTU PROTOCOL

MODBUS is used for serial communication protocol. It is derived from the

master/slave architecture. The master may communicate to one or more slave devices

on different slave address. Always only a master device can initiate the

communication to slave devices on MODBUS network. Slave device can only

respond to the request data from the master. MODBUS RTU (Remote Terminal Unit)

is the MODBUS protocol used on a serial line communication with RS-232 and RS-

485 port as the interface.

To initiate communicate with slave device, a master device sends a frame that

contain following data as also shown in Fig.1:

Figure 1 Modbus RTU Frame Structure

Slave device address

The device address can be in a range of 0 to 247 addresses. Addresses 1 to 247 are

applicable for specific slave devices and Address number 0 is used for broadcasting

frame received by all the slave devices.

Function code

The function codes defines the command that tells the slave device what kind of

action takes place, such as read and write data.

Data

The data defines addresses in the device’s memory map for reading functions.It

contains data values to be written into the device’s memory.



Error Check

The error check is a 16-bit numeric value representing the cycling redundancy

check (CRC). The CRC is generated by the master device and being checked by the

receiving device. If the CRC code does not match with code of the receiving devices

then the receiving device asks for a retransmission.

7. NOVEL IDEA TOWARDS TRANSFORMER CONDITIONING

MONITORING SYSTEM

This paper presents a new system that employs the present technologies, coupled with

wireless GPRS Gateway, to provide data acquisition to the end user and then analyses

the received data from the GPRS module. The main aim for developing this system is

to provide real time data to the end user.

The main objective of this system is to monitor the insulator ageing rate and hot-

spot temperature. The ageing of insulator is mainly affected by changes in

temperature and electrical operation characteristics of transformer. The failure of

insulator when in use is mainly due to the temperature rise, ageing, over load, and

improper installation and maintenance. Out of these factors temperature rise and

ageing rate of insulator needs continues monitoring to save the insulator life.

8. EXPERIMENTAL

The Main Objective of this system is used to monitor the condition of the transformer

insulation system. The wireless GPRS based device being used works for transformer

insulation conditioning monitoring system. The transformer insulation conditioning

monitoring system will monitor following parameters:

Top-Oil Temperature

Hot-spot temperature

Ageing rate of insulation

Insulation loss of life

The above parameter are calculated as per the IEC 60076-7 standards. Fig.2

contains the complete block diagram of the transformer insulation monitoring system,

consisting of Energy Meter, embedded ICM (Insulation Conditioning Monitoring),

GPRS Gateway, and SCADA for ICM (Insulation Conditioning Monitoring) System.

Figure 2 System Block Diagram


Transformers


8.1. Energy Meter

The 3-phase Energy meter is used to measure electrical parameters in power

transformer. For this system Schneider Conserve EM 1200 series power meter is used

[12]. It has an integrated serial RS-485 Modbus RTU interface. This facility allows

direct reading of all applicable parameter such as voltage, current, power, power

factor, etc... Due to this advantage the meter can measure the main electrical

parameter and make them available via COM port. This COM port allows connecting

meter remotely. The meter has unique address from 1 to 247 (up to threedigits). This

will allow communication from one port to master device. The meter never initiates

communication it can only respond.

Table 1Parameter of Master and Slave Station

When master device wants the electrical parameter from the meter, the master

device sends messages that contain the meter address and the parameter it wants and

checks the sum for error detection.

In order to implement the MODBUS Protocol communication between Energy

meter and Master device, first of all we should configure both MASTER Device and

Energy meter for the same communication mode and same BAUDRTE that is 9600

BPS (bits per second) [13]. Configuration is shown in table 1.

8.2. Embedded ICM

Embedded ICM (Insulation Condition Monitoring) consist of MSP430F5419A

microcontroller [14] with MODBUS master and Advanced Insulation Ageing

Algorithms, Power supply and RS485 Communication Circuit. As discussed earlier

the electrical and mechanical strength of transformer insulation is mainly dependent

on the ambient temperature and operating load of the transformer.

Here, MODBUS master is not device but it is a Function that is implemented in

the Microcontroller. The MODBUS Master function will gather data from MODBUS

RTU (RS 485) based Energy Meter. MODBUS Master will poll the collected data for

Voltage, Current, and Power Factor, Power etc. for the calculation of Hot-spot

Temperature, Ageing Rate, and Insulation loss of life, the Load (Current) is the most

important parameter. So MODBUS Master Function will provide these data to the

Microcontroller on UART (Universal Asynchronous Trans receiver).

For ambient Temperature measurement the microcontroller having in built

temperature monitoring sensor will be used for ambient temperature monitoring. Due

to this advantage system doesn’t require extra sensors to measure ambient

temperature and it will make the system cost effective.

Parameter Type Settings

Communication Mode RS485 Modbus

Baud Rate 9600

Parity None

Delay (ms) 100

Slave Address 1~247

Select Literacy Read

Stop bit 1

Read Number (Byte) 255



In addition to this for the calculation of Hot-spot temperature some other

parameters also required that is based on the power transformer specification sheet.

These parameters will be provided by user input from the specification sheet in Table

2.

Advanced Insulation Ageing Algorithms consist of the IEC 60076-7 standards

based differential equation [11] that is implemented in MSP430F5419A

microcontroller.

There are two methodologies to deal with hot-spot temperature. Either to measure

it or to calculate it. But measuring of hot-spot temperature can prove to be costly to

the system. For this reason, several models [4, 11] are used for prediction of hot-spot

temperature. For prediction of Hot-spot temperature IEC 60076-7 [11] Standards is

used in this paper.

Based on Ambient Temperature, operating Load of Power transformer and power

transformer specifications the Top-oil temperature and Hot-spot temperature will be

calculated. This is as per the IEC 60076-7 Standards. Once Hot-spot Temperature is

derived; based on that one can easily calculate Relative ageing Rate as Per the IEC

60076-7 Standards [11]. If integrated value with defined sample time interval of

Ageing Rate one can calculate insulation loss of life as per IEC 60076-7 standards

[11].

Once all these parameters such as operating load of power transformer, Ambient

Temperature, Top-oil Temperature, Hot-spot Temperature, Relative Ageing Rate, and

Insulator Loss of life are derived; then that will be transmitted to remote server via

GPRS Gateway. The remote server is located at particular central zone. Remote server

is having a facility for further analysis and load shedding as well as predictive

Maintenance, all these will be taken care for the transformer.

Table 2 Power Transformer Specification Sheet [11, 15]

Parameter Type Description

Rated Power 20/27 MVA

Voltage (High voltage/ low voltage) 66/22 kV

Cooling ONAN-ONAF

System Frequency 50 Hz

Oil time constant (τ0) 150 min.

Winding Time Constant (τw) 7 min.

Winding Exponent (y) 1.3

Oil Exponent (x) 0.8

Loss Ratio (R) 8

Thermal Time Constant (K11) 0.5

Thermal Time Constant (K21) 2

Thermal Time Constant (K22) 2

Top-oil temperature rise above ambient (∆θor) 45

Hot-spot temperature rise above top-oil temperature (∆θhr) 35

Power supply unit will provide power supply to the microcontroller, GPRS

Gateway, and RS485 Communication Circuit. The RS485 Communication circuit will

connect UART port of the microcontroller and RS485 port of the energy meter. I.e. it

will provide interface between UART port and RS485 port.


Transformers


8.3. GSM/GPRS Gateway

GSM/GPRS Gateway will connect remote location using GPRS technology and

provide data to the Remote Server. For this system here HK GPRS Gateway device is

used. This GPRS Gateway will provide interface between wireless output and

MSP430F5419A Microcontroller. The main role of the GPRS Gateway in this system

is to transmit all the parameters to the remote server.

8.4. Remote Server

Remote Server will store operating load of transformer, Ambient Temperature, Top-

oil Temperature, Ageing Rate, and Insulator loss of life data. For this system HK

SCADA System is used. These data will be used for analysis purpose. Remote server

has SCADA system so that data can be stored for many years and the same data will

also be applicable for the development of advanced algorithm and for further analysis.

HK SCADA system performs the critical function of data collection, storage, and

processing, display and report generation. It gathers the plant floor data collected by

distributed GPRS, ZIGBEE, Wi-Fi, RF or an in-plant Ethernet / RS - 485 networks,

and stores it in a central database.

9. EXPERIMENTAL IMPLEMENTATION

As earlier discussed the time-varying load factor (K) and Ambient temperature (θA)

are used for finding the Hot-spot Temperature [4]. Fig.3, inputs are load factor K, and

Ambient Temperature θA on the left side. The desired output is Hot-spot Temperature

θh on the right side. The Laplace variable s is essentially the derivative operator d/dt.

Figure 3 Block Diagram that represents the differential equations



The second block of the uppermost part represents the Hot-spot Temperature

dynamics. The first term of second block is k21 that represent the fundamental Hot-

spot Temperature rise. And second term of that block is k21-1 that represents changing

the rate of oil flow. The combined effect of these two terms will sudden rise in high

peak in Hot-spot Temperature [11]. The values for k11, k21,k22, are described in the

above table 2. If you have measured Top-oil Temperature then that will be directly

fed through the switch and that will be shifted to the right side; the Top-oil calculation

is not required.

The differential equation for finding Top-oil Temperature θo is mention below

[11]. For this equation inputs parameters are K, and θA and output Parameter is θo.

(5)

The differential equation for finding Hot-spot Temperature rise ∆θh is sum of two

differential equations [11], for this equation input parameter is K and output

parameter is ∆θh.

Where,

(6)

The two equations are

(7)

And

(8)

The final equation for the finding the Hot-Spot Temperature θh [11] is sum of the Top-

oil Temperature and Hot-spot Temperature rise.

(9)

For finding Relative Ageing Rate and the Insulation Loss of life both these equations

are broadly described in the above section.

These above equations are used for finding Top-oil Temperature, Hot-spot

Temperature, Ageing Rate, and Insulation Loss of Life. All these are implemented in

algorithm form in the MSP430F5419A Microcontroller and the output results of that

particular parameter is shown Fig.4 in the SCADA system.

10. RESULTS

The Transformer Real time load current data is provided by the Energy Meter via

MODBUS RTU. The estimated top oil temperature is used to determine the hot-spot

temperature parameter

Hot-spot parameter is used to determine Ageing Rate and Loss of Life of

transformer. At the end of the all these, the parameters will be transmitted to the

SCADA remote server via GPRS Gateway.

Fig.4 shows the different real time indicators in the main page of the SCADA.

There is a difference in a Rated loss of life and actual loss of life of the transformer.

The rated working hour loss of the power transformer is 1 hour but in the Actual, loss

of life of transformer is 2 hour during this working hour


Transformers


Figure 4 SCADA Main Page that Show Transformer Real time Indicators

Figure.5 SCADA Trend Page for Ambient Temperature and Hot-spot Temperature

The effect of the increase in the load profile of the Power transformer and ambient

temperature of the environment can be seen in the Fig.5 and Fig.6 As previously

discussed in the section 9, the load current and ambient temperature must have effect

on the hot-spot temperature of the power transformer. Fig.7 shows the increase in load

current and ambient temperature increases the hot-spot temperature of the

transformer.



Figure.6 SCADA Trend Page for Rated Ageing and Actual Ageing

Figure.7 SCADA Trend Page for Rated Current and Actual Current

From the Fig.5 it is concluded that when there is an increase in the hot-spot

temperature (shown in Fig.5) the ageing of the transformer also increases. Because of

the ageing and hot-spot temperature are linearly proportional to each other.

HK SCADA has a facility to show real time parameter in web client site. So, Fig.8

shows all estimated parameters on SCADA web client site. Similarly Fig.9, 10 and 11

shows group wise parameters on SCADA web client site


Transformers


Figure.8 SCADA Web client Page which shows all Estimated Parameters

Figure.9 SCADA Web client Page which show Particular Group wise Parameters (Group-1)





ACKNOWLEDGEMENT

I am very grateful and would like to thank all the member of NOVATRICE

Technologies (P) Ltd. And HARIKRUPA AUTOMATION (P) Ltd. for their advice

and valuable support without them it would not have been possible for me to complete

this paper.

I would like also thank to all my friends, colleague and classmates for all the

thoughtful and mind stimulating discussions we had, which prompted us to think

beyond the obvious

REFERENCES

[1] T. A. Prevost and T. V. Oommen, Cellulose Insulation in Oil-Filled Power

Transformers: Part I - History and Development, in Electrical Insulation

Magazine, IEEE. 22 2006, pp. 28-35.

[2] T V. Oommen, Thomas A. Prevost, Cellulose Insulation in Oil-Filled Power

Transformers: P art II – Maintaining Insulation Integrity and Life, IEEE

Electrical Insulation Magazine, 22(2), 2006, pp. 5-14.

[3] Yuan Li, Ming-jie Tang, Jun-bo Deng, Guan-jun Zhang, Shu-hong Wang, An

Approach to Aging Assessment of Power Transformer Based on Multi-

parameters, 2012 IEEE International Conference on Condition Monitoring and

Diagnosis, 23-27 September 2012, Bali, Indonesia.

[4] IEEE Standard, (C57.91-1995) Guide for Loading Mineral-Oil-Immersed

Transformers.

[5] Nick Lelekakis, Wenyu Guo, Daniel Martin, Jaury Wijaya,Dejan Susa, A Field

Study of Aging in Paper-Oil Insulation Systems, IEEE Electrical Insulation

Magazine, 28(1) January/February 2012.

[6] Cigre, Ageing of cellulose in mineral-oil insulated transformers, Cigré Brochure

323, 2007, p.46.

[7] X. Zhang, E. Gockenbach, Asset-Management of Transformers Based on

Condition Monitoring and Standard Diagnosis, IEEE Electrical Insulation

Magazine, 24(4), 2008, pp. 26-40.

[8] K. Najdenkoski, G. Rafajlovski, V. Dimcev, Thermal Aging of Distribution

Transformers According to IEEE and IEC Standards, Power Engineering Society

General Meeting, IEEE, 2007, pp. 1-5

[9] W. J. McNutt, Insulation Thermal Life Considerations for Transformer Loading

Guides, Transactions on Power Delivery, 7(1), January 1992.

[10] Mohad Taufiq Ishak, Simulation Study on Influencing Parameters of Thermal

Ageing for Transformer Lifetime Prediction, University of Manchester, 2009.

[11] IEC 60076-7, (2005) Loading Guide for Oil-immersed Power

Transformers.Transl. J. Magn. Jpn, 2, 2005, pp. 740-741.

[12] Schneide Conzerv EM1200 Series Power Meters User Manual, EAV95462-01,

06/2014.

[13] Kelong Wang, Daogang Peng, Lei Song, Hao Zhang, Implementation of Modbus

Communication Protocol based on ARM Coretx-M0, IEEE International

Conference on system science and Engineering (ICSSE), July 2014, pp 11-13

[14] MSP430F5419A, MSP430F541xA Mixed Signal Microcontroller data sheet.

[15] Technical Specification for 220/132 kV, 150 & 100 MVA; 132/66 kV, 50 & 100

MVA Auto Power Transformer, GETCO/E/TS-XMER 01/ R6 April 13.

cellular communication based remote predictive … · 2015. 8. 31. · cellular communication based...

Documents