The present invention relates generally to centralized monitoring and
diagnostics of large fleet of Transformers/Reactors. More specifically, the present
invention relates to a system and method for acquiring the data consisting of
design/nameplate data and routine test data from test kits/sensors from multiple
sites/laboratories, analyse the data to characterize health of Transformer/Reactors by
assessing chosen parameters and represent their health using hybrid health indicators on a
graphical user interface.
BACKGROUND OF THE INVENTION
[0002] Transmission sector around the world is undergoing rapid development and
expansion. With each high voltage transmission project coming up at a very fast pace,
several relatively high value, specialized equipment’s like transformers and reactors are
installed as part of the project. These equipment’s form the backbone of any large and
stable transmission system. These equipment’s are expensive, and their maintenance is also
costly. The continued and reliable operation of the equipment’s is vital to the uninterrupted
supply of energy to home, industrial, commercial and other consumers of electrical power.
The transformers/reactors in electric power transmission network are spread over vast
geographical area, which makes monitoring, diagnostics and maintenance planning a
challenging task.
3
[0003] Substations, which are an important part of the electrical power transmission
and distribution system, typically contain or are otherwise dependent upon a number of
transformers/reactors. Optimizing the maintenance, repair, and replacement of these
transformers/reactors is a challenging task, particularly when viewed in the larger context
of system reliability.
[0004] To assess the health of various sub-parts of the equipment, routine tests are
conducted under Annual Maintenance Plan. Since, these transformer/reactors are spread
over vast geographical area it is very difficult to assess their health individually. Further, it
also difficult to organize and analyse the large volumes of information from these disparate
sources in a coordinated way.
[0005] WO2019140553A1 relates to a method and system for determining a health
index of a power distribution system and a computer storage medium. The method
comprises: determining an evaluation object which takes part in health index determination
(S110), wherein evaluation objects comprise: power distribution equipment or a
distribution network consisting of power distribution equipment and lines; collecting
feature values of said evaluation object according to a feature quantity corresponding to
said evaluation object (S120), wherein said feature values comprise: one or more of an
attribute value, an operation status value, a connection relationship value characterizing a
connection relationship, and a connection status value characterizing the connection status
of said connection relationship of said evaluation object; and processing said feature values
4
using an evaluation model adapted to said evaluation object, so as to obtain a first health
index that measures the health state of said evaluation object.
[0006] In the above patent document, calculation methodology for health index is
described using Regression and neural network. However, the document is silent on count
per category, confidence level, worst case approach and trend analysis concepts.
[0007] The research paper titled “An Approach to Determine the Health Index of
Power Transformers” describes a realistic health index formulation method for power
transformers using readily available data. The method considers practical limitations on
obtaining data, and the possible constraints on the parameters. It also utilizes IEC, IEEE,
and CIGRE criteria for condition parameters. This Health Index calculation considers not
only typical test results such as dissolved gas analysis (DGA), oil quality, furan, and power
factor, but also other parameters such as tap changer and bushing condition, physical
observations, load history, maintenance work orders, and age. The calculation includes
condition ratings, weighting factors, and assigned scores for specific condition parameters.
By using a multi-criteria analysis approach, the method combines the various factors into
a condition-based health index.
[0008] The above research paper does not recite of the data acquisition methodology,
count per category concept, worst case approach and confidence level concept.
[0009] Owing to the aforementioned drawbacks, there exists a need to develop a system
and method that analyses data to characterize health of Transformer/Reactors by assessing
5
chosen parameters and represent their health using hybrid health indicators on a graphical
user interface.
OBJECTIVE OF THE INVENTION
[0010] The prime objective of the present invention is to overcome the shortcomings
associated with the conventional systems and methods.
[0011] Another objective of the present invention is to provide a system and method
that determines the current health status of the equipment by means of a hybrid health indexing
scheme and to diagnose abnormalities in transformers/reactors.
[0012] Another objective of the present invention is to provide a system and method,
wherein the hybrid health index helps in ranking transformers/reactors fleet and optimizing
the scheduling of maintenance activities.
[0013] Another objective of the present invention is to provide a system that
incorporates diagnostics feature such as automatic DGA analysis, trend analysis and worstcase analysis.
[0014] Yet another objective of the present invention is to provide a system and method
that address the challenges related to centralized monitoring, diagnostics and maintenance
planning activities for a large fleet of Transformers (Inter-connecting, coupling and
converter transformers) and Reactors (line and bus reactors) by assessing their health.
6
[0015] Yet another objective of the present invention is to provide a system and method
that is simple in design, easy to use/handle and economical.
[0016] These and other objectives of the present invention will be apparent from the
drawings and descriptions herein. Every objective of the invention is attained by at least
one embodiment of the invention. However, no embodiment necessarily meets every
objective set forth herein.
SUMMARY OF THE INVENTION
[0017] The present invention is directed towards a system and method used to acquire
the data consisting of design/nameplate data and routine test data from test kits/sensors
from multiple sites/laboratories, analyse the data to characterize health of
Transformer/Reactors by assessing chosen parameters and represent their health using
hybrid health indicators on a graphical user interface.
[0018] According to an embodiment of the present invention, the system comprises of
infrastructure for testing transformer/reactors (i.e. sensors/testing equipment); network for
collecting and storing the data (transformers/reactors details, test data and analysis results)
on a database server that is operatively accessed by a plurality of clients through a
communication channel and a Human Machine Interface (HMI).
[0019] According to an embodiment of the present invention, the method to
characterize health of Transformer/Reactors using chosen parameters, comprises the steps
of ;
7
• testing of transformers/reactors at site and their oil samples in oil test laboratories;
• entering the results/values of tests performed on the equipment into the ERP
database from various sites and oil test laboratories;
• acquiring the selective test data from ERP database to Health assessment server in
predefined structured tables;
• computing parameter, test and component scores from this refined test
results/values based on a scoring matrix that calculates numeric health index;
• assigning hybrid health indices for each transformer/reactor; and
• presenting the hybrid health indices to the end user on a user-friendly
comprehensive dashboard having several buttons that displays the health of all the
transformers and reactors.
[0020] As should be apparent, the invention can provide a number of advantageous
features and benefits. It is to be understood that, in practising the invention, an embodiment
can be constructed to include one or more features or benefits of embodiments disclosed herein
but not others. Accordingly, it is to be understood that the preferred embodiments discussed
herein are not to be construed as limiting, particularly since embodiments can be formed to
practise the invention that do not include each of the features of the disclosed examples.
BRIEF DESCRIPTION OF THE DRAWINGS
[0021] The present invention and its advantages will be better understood by referring
to the following detailed description and the attached drawing in which
8
Figure 1(a) displays the screenshot of the scoring matrix used for assigning parameter score
and calculating test and component score for inter-connecting transformers;
Figure 1(b) displays the screenshot of the scoring matrix used for assigning parameter score
and calculating test and component score for converter transformers;
Figure 1(c) displays the screenshot of the scoring matrix used for assigning parameter score
and calculating test and component score for coupling transformers;
Figure 1(d) displays the screenshot of the scoring matrix used for assigning parameter score
and calculating test and component score for line and bus reactors;
Figure 2 depicts the formulae used for calculation of test and component score and health index;
Figure 3 is a screenshot of an interface of main dashboard displaying region wise equipment
health index;
Figure 4 displays the colour-coding used to categorize the health indices;
Figure 5 illustrates an example of result page of one of the regions;
Figure 6 displays the screenshot of the health vs make distribution of all the
transformers/reactors;
Figure 7 displays the screenshot of the criticality wise make vs. age distribution of all the
transformers/reactors.;
Figure 8 illustrates an example of a transformer/reactor health analysis page showing parameter
scores of various test performed on the transformer/reactor;
Figure 9 illustrates an example of bushing analysis performed on one of the
transformers/reactors;
Figure 10 illustrates an example of DGA analysis performed on one of the
transformers/reactors;
9
Figure 11 illustrates an example of DGA report generated for one of the transformers/reactors;
Figure 12 illustrates an example of trend analysis performed on one of the
transformers/reactors;
Figure 13 illustrates an example of Health Index Trend of one of the transformers/reactors;
Figure 14 illustrates the detailed flow chart of the data acquisition from site/laboratories;
Figure 15 illustrates the detailed flowchart of data flow from site/laboratories to ERP; and
Figure 16 illustrates the detailed flowchart of data analysis in the Health assessment server and
data from ERP to HMI
DETAILED DESCRIPTION OF THE INVENTION
[0022] The following description includes the preferred best mode of one embodiment
of the present invention. It will be clear from this description of the invention that the invention
is not limited to these illustrated embodiments but that the invention also includes a variety of
modifications and embodiments thereto. Therefore, the present description should be seen as
illustrative and not limiting. While the invention is susceptible to various modifications and
alternative constructions, it should be understood, that there is no intention to limit the
invention to the specific form disclosed, but, on the contrary, the invention is to cover all
modifications, alternative constructions, and equivalents falling within the spirit and scope of
the invention as defined in the claims.
[0023] In any embodiment described herein, the open-ended terms "comprising,"
"comprises,” and the like (which are synonymous with "including," "having,” and
"characterized by") may be replaced by the respective partially closed phrases "consisting
10
essentially of," “consists essentially of," and the like or the respective closed phrases
"consisting of," "consists of,” and the like.
[0024] As used herein, the singular forms “a,” “an,” and “the” designate both the
singular and the plural, unless expressly stated to designate the singular only.
[0025] The term “and/or” means any one of the items, any combination of the items,
or all of the items with which this term is associated. The phrase “one or more” is readily
understood by one of skill in the art, particularly when read in context of its usage. For example,
one or more active agents refers to one, one or two, one to three, two or three, or three or more.
[0026] Transformer/Reactor health assessment system is developed for assessing the
health of transformers/reactors fleet using hybrid health indices. The system enables
centralized monitoring of all the transformers and reactors owned by the organization which
are spread throughout the country. This system is used to monitor the health of any
transformer/reactor from anywhere in the country. The asset manager can review the health of
any batch of assets based on their characteristics like criticality, voltage level, type, make and
age. The system gives enough information to the asset manager about the health of
transformer/reactor, to take an appropriate decision to replace, refurbish or repair of the
transformers/reactors at the time of evaluation.
[0027] The present invention is directed towards a system and method for acquiring the
data consisting of design/nameplate data and routine test data from test kits/sensors from
11
multiple sites/laboratories, analyse the data to characterize health of Transformer/Reactors
by assessing chosen parameters and represent their health using hybrid health indicators on
a graphical user interface.
[0028] The system comprises of infrastructure for testing transformer/reactors (i.e.
sensors/testing equipment); network for collecting & storing the data (transformers/reactors
details, test data and analysis results) on a database server (operatively accessed by a
plurality of clients through a communication channel) and Human Machine Interface. .
[0029] The method to characterize health of Transformer/Reactors using chosen
parameters, comprises the steps of testing of transformers/reactors at site and their oil
samples in oil test laboratories; entering the results/values of tests performed on the
equipment into the ERP database from various sites & oil test laboratories; acquiring the
selective test data from ERP database to Health assessment server in predefined structured
tables; computing parameter, test and component scores from this refined test results/values
based on a scoring matrix that calculates numeric health index; assigning hybrid health
indices for each transformer/reactor; and presenting the hybrid health indices to the end
user on a user-friendly comprehensive dashboard having several buttons.
[0030] Health index of Transformers and Reactors is expressed either in numeric or in
non-numeric form. Both Numeric and Non-numeric ways of health index representations
have their own benefits and drawbacks. For e.g. Numeric score allows quantification and
thereby it is possible to ranks all transformers/reactors, while non-numeric score (Colourcoding) does not allow quantification. Numeric score can distinguish between two health
12
indices even if they fall in same category. For e.g. two transformers/equipment having
health index of 4.2 and 5.5, fall in Light Green colour category if the range of good category
is 4.1 to 6, hence non-numeric score cannot distinguish them. On the other hand numeric
health index can hide single parameter in advanced stage of failure if all other parameters
are in excellent/good condition while non-numeric representation like worst-case failure
can highlight such issues. For e.g. Numeric health index of Transformer/Reactor can be 8,
falling under very good category even though it is having presence of C2H2 in oil and
should be investigated, hence, numeric score can mask important information at times. The
drawback of worst-case approach is that it cannot differentiate between multiple failure
modes. The drawbacks of worst-case approach can be overcome by use of count per
category but again it is not a single number but a set of numbers and it makes representation
of the result on a dashboard more difficult.
[0031] The system utilizes hybrid health indexing scheme (both numeric and nonnumeric) for health assessment of equipment. The hybrid health index assignment for
individual transformer/reactor consist of a Numeric weighted average health index
(calculated as per formula shown in Figure 2), Colour-coded index of all
transformers/reactors (as shown in Figure 4), Worst-case to quickly highlight
transformer/reactor with some critical parameters (Figure 5) and Count per category index
for each individual transformer/reactor ( Figure 5). Supplementary features such as
customized trend analysis and various useful distributions (Make-Age, Make-health and
Health index wise Make-age) are also available in the system to assist planning of
maintenance activities.
13
[0032] The scoring matrix as illustrated in Figure 1, is the key element for the purpose
of calculation of numeric health index. In this scoring matrix, each key component of the
equipment such as bushing, dielectric insulation and On Load Tap Changer (OLTC) is
subdivided into several tests, based on the tests performed to determine the healthiness of
that particular component. For example, the tests performed to determine health of bushing
are Capacitance and Tan Delta, similarly Dissolved Gas Analysis, Core Insulation
Resistance, Furan etc. are performed for healthiness of dielectric insulation. Further, each
test is subdivided into several parameters which constitute the test. For example, various
gases like H2, CH4, C2H2, C2H4, C2H6, CO, CO2 become the parameters for DGA test.
In this manner, 21 parameters for inter-connecting transformers, 20 parameters for
converter transformers, 19 parameters for coupling transformers and 20 parameters for line
and bus reactors have been chosen for evaluation with their assigned unique weightages
which provide concrete information on health of Transformer/Reactors. The acceptable
limits of the values of these parameters are then divided into six categories viz. Critical
(S1), Very Poor (S2), Poor (S3), Good (S4), Very Good (S5) and Excellent (S6). Also, each
of the parameter, test and component have been assigned certain weightages based on the
importance of each element in determining the health of the overall equipment. These
weightages assigned are unique and have been determined based on the vast in-house
experience in the field of condition monitoring of power equipment. In order to calculate
the parameter score, the respective test value is fetched from the corresponding SQL Server
table. For example, DGA data is fetched from oil analysis table; capacitance and tan delta
values are fetched from Capacitance Tan Delta table. The category (S1 to S6) of each of
14
these values are then computed by comparison with the values/ranges decided in the six
categories of the scoring matrix. The numerical part of this category reflects the parameter
score. For example, if the value of some parameter falls in S3 category, then the respective
parameter score will be 3, similarly the parameter score will be 6 for S6 category. The test
score is calculated using these parameter scores by using formula shown in Figure 2. Once
the test scores are calculated, the corresponding component scores are calculated using
formula shown in Figure 2. Finally, the health index is calculated using these component
scores using formula shown in Figure 2. The health index calculated at this stage is then
scaled to 10. This numeric health index assigned to each equipment is stored in the health
analysis results table of the Health assessment server database.
[0033] It is possible that even though one of the critical parameters is in very poor
category and the equipment seeks urgent attention, but due to assigned weightages the
overall numerical health index may fall in very good/good category. For such scenarios,
Worst-case failure approach has been framed for quick identification & isolation of
transformers/reactors on the HMI, wherein certain parameters are diagnosed to be critical
stage. The methodology for identification of equipment with worst-case failure mode is
unique, wherein no score is calculated/evaluated. The worst test approach enables the user
to quickly assess the health of the equipment based on some critical parameters such as
C2H2 violation based on absolute value and rate of change. The worst-case approach
module is configurable so that more such parameters can be incorporated for evaluation.
15
[0034] The Count per Category feature allows representation of multiple failure modes
in each category simultaneously. The feature of Count per Category aids the user to have
an idea of how many test parameters are lying in each category at one glance. The count of
number of parameters falling in each of the 6 categories (S1, S2, S3, S4, S5, S6) is stored
in the health analysis results table. The category “No-data” indicates the number of
parameters for which the test data is not entered/available in database. This count is shown
as Count per Category (S1-S2-S3-S4-S5-S6-No Data) on the HMI (Figure 5).
[0035] The oil test results from site/oil test laboratories are used by Dissolve Gas
Analysis module to detect incipient fault present in transformers/reactors and states its
severity, as per various methods mentioned in IEEE C57.104-2019 and IEC 60599. In
addition to this, trend analysis feature in HMI allows user to analyse the trends of all oil
test results over a user-defined period.
[0036] Further, one more important parameter, known as Confidence level for each test
result is calculated based on the actual and prescribed testing frequency. Confidence level
indicates whether the tests was performed within the prescribed test frequency or not.
Confidence level informs the user that whether the test data analyzed is relevant or
outdated. If the test is performed as per prescribed testing frequency or within 6 months
after the prescribed testing frequency, the confidence level assigned is 10. For the tests
performed 6-12 months after the date of normal frequency, the confidence level assigned
is 7. Similarly, for the test performed 12-36 months after the date of normal frequency the
assigned value is 4 and for more than 36 months after the date of normal frequency, the
16
values assigned is 0. This confidence level is also stored in the health analysis results table
of the Health assessment server database. The overall data quality indicator for whole
transformer/reactor unit is calculated from individual data quality indicator for each
parameters based on weighted average. In case, confidence level of that equipment is below
the acceptable limit, the user will retest the equipment before taking any decision.
[0037] All the calculations are performed automatically once per day after the data
from ERP is pushed into the Health assessment server database. This information is
presented to the end user in the form of a HMI (Human Machine Interface) application.
The HMI application consists of various interfaces, each having its own architecture.
[0038] The dashboard as illustrated in Figure 4 gives overall picture about the health
of all the transformers and reactors spread over the country. Further, it also shows region
wise distribution of transformers/reactors with associated health index. The health index
values are divided into six categories based on criticality as per the colour coding shown in
Figure 5 and then all the equipment are arranged into their respective categories.
[0039] The topmost pie chart on the main dashboard along with 8 colour-coded buttons
adjacent to it represent the overall health of all the equipment (transformers and reactors)
linked with this system excluding the spare equipment. The same dashboard is replicated
for transformers and reactors individually which can be viewed by clicking on the
“Transformers” or ‘Reactors’ buttons provided on the right hand side. On clicking any of
these buttons, the system directs the user to the result page (Figure 5).
17
[0040] The smaller ten pie charts in the main dashboard represent the health of all the
transformers/reactors in the individual regions. On clicking any of the region in the pie
chart, a screen similar to Figure 5 appears and pertains to the region whose button has been
clicked.
[0041] There are six buttons on the right side of the main dashboard. Functionality of
each button is mentioned below:
a. Spares: This takes you to a page similar to result page (Figure 5), where the results of all
the spares (transformers and reactors) are displayed.
b. Transformers: The main dashboard (Figure 4) is replicated here exclusively for
transformers with the same functionalities as of main dashboard.
c. Converter Transformers: The main dashboard (Figure 4) is replicated here exclusively
for converter transformers with the same functionalities as of main dashboard.
d. Reactors: The main dashboard (Figure 4) is replicated here exclusively for reactors with
the same functionalities as of main dashboard.
e. Make-Health Distribution: This screen (Figure 6) shows the distribution of all the
transformer/reactor manufacturers’ vs their health. This assists in quickly evaluating the
performance of all the transformer/reactor supplied by any particular manufacturer.
f. Make-Age Distribution: This screen (Figure 7) shows the distribution of
all/transformer/reactor according to their manufacturers and age based on the criticality
index chosen by the user. The criticality index can be chosen from the six colour coded
18
buttons present on the top half of the page. The colour-coding is as per Figure 5. This page
(Figure 7) depicts a very unique feature of the system. On this page, criticality wise
manufacturer vs. age analysis is performed for quick management information. For each of
the health category, manufacturer’s performance is tabulated. Using this, ranking of each
manufacturer is calculated based on the health index of all the equipment supplied by the
respective manufacturer.
[0042] Result Page - This page as illustrated in Figure 5 shows the list of all the
corresponding equipment along with their nameplate details (region/substation/equipmenttype/equipment-serial -no./description/ commissioning-data/make) and their respective
health index, confidence level and count per category. Various filters (based on
region/substation/voltage/make/equipment type/worst case/age group/health status)
provided on top of the table can be used to further refine the results as per user’s
requirement. Further, there are options present right below the filters to export the table as
csv or PDF or to take a printout of the table.
[0043] Each row in the table of the Result Page represents an equipment and the serial
number of each equipment is a hyperlink. On clicking the serial number,
transformer/reactor analysis page opens up as shown in Figure 8. This page has all the
information about the equipment ranging from its nameplate details (1st table) to its current
health. The second table lists all the parameter/test/component values/dates/confidence
level/score of the equipment. The parameters and their respective scores are colour coded
as per Figure 4.
19
[0044] There is a “Comments” section on the Results page wherein special remarks
pertaining to this equipment can be seen. Only selected users (with special rights) can edit,
delete or create comments.
[0045] There is an option for the user to view the health of all the bushings of the
equipment by clicking on the “Get Details” button placed in the bushing test cell. Bushing
analysis screen (Figure 9) opens up on clicking the “Get Details” button. This page contains
the nameplate details of the equipment and complete health analysis of all the bushings of
the equipment. The colour coding of the parameter score on this page is also as per Figure
4.
[0046] The user can also get an insight on how the oil DGA is performing by clicking
on the “Get Details” button placed in the DGA test cell. DGA Analysis Page (Figure 10)
opens up. It shows detailed analysis of the latest DGA results of the equipment as per
various methods mentioned in IEEE C57.104-2019 and IEC 60599.
[0047] There is an additional option of “Get History” in all the test cells using which
the user can view the historical data values of all the parameters of that particular test. On
clicking the “Get History” button, a .csv file will be downloaded containing the test data
history.
20
[0048] On the top right hand side of the window, there is a “Plot” button which will
allow the user to plot various tests of the equipment (the one whose equipment analysis
page is open) against the test dates. The user can select the test data to be plotted from the
various filters available on the Plot Page (figure 12).
[0049] The user can also see the trend of equipment health index with date/time by
clicking on the “Health Index Trend” button located right below the “Plot” button.
[0050] DGA Analysis Page - This page as illustrated in Figure 10 shows the detailed
dissolved gas analysis as per various methods mentioned in IEEE C57.104-2019 and IEC
60599. Further, the developer’s own experience in the field of condition monitoring has
been incorporated in this analysis. The nameplate details and the latest gas values are also
shown on this page. Few add-ons are provided on this page- Duval Triangle (to show Duval
triangle analysis on the data as per IEC 60599), Duval Pentagon (to show Duval Pentagon
analysis on the data as per IEEE C57.104:2019), Generate DGA report (to generate a brief
report on the DGA analysis in a unique pre-defined format shown in figure 11) and Trend
Analysis (to see the historical gas trend).
[0051] Health Index Trend - This trend as illustrated in Figure 13 depicts another
unique feature of the system. It shows the date wise trend of health index to keep track of
equipment health. Whenever the health index of the equipment changes, the value of the
index gets logged into the system against the respective date. The trend is then generated
21
using that log to visualize the variation of the healthiness of the equipment, analogous to
heart beat of a person.
[0052] The flowchart of Figures 14 and 15 show the data acquisition from
site/laboratories to ERP. Various routine tests are conducted on a transformer/reactor
(bushing test, dielectric insulation tests, OLTC related test), at site during its lifetime.
Further, transformer/reactor oil samples are collected at pre-defined intervals and tested for
Dissolved Gas (DGA) Analysis & Oil quality of the insulation oil at Regional (RTL),
Specialised (STL) and Central (CIOTL) oil test laboratories. The results of the routine test
performed on a transformer/reactor (bushing test, dielectric insulation tests, OLTC related
test) at site during its life time are reviewed and updated onto the Enterprise Resource
Planning (ERP) Graphical User Interface (GUI). The data captured is then stored in the
central ERP database at other end of network. Apart from these, the nameplate details
(Location, Make, Commissioning Date, Voltage rating etc.), tripping data and related
components/accessories are stored in ERP database and are linked with the main
equipment. All of these raw test data: site test data, Lab DGA results and design/name plate
details are monitored for any change, by change log function. Whenever any changes are
detected, the altered portion of data is identified and pushed from ERP database to health
assessment server on daily basis using ERP data interface engine after several refinements
and filtrations (refer figure 15). ERP data interface engine has been used to set up cross
system communication, integration and for establishing the connection between ERP and
non-ERP compliant systems (Health assessment server in this case).
22
[0053] The flowchart of Figure 16 shows the data flow from ERP to the final user via
Health assessment server. The Health assessment server contains a SQL Server database,
which has dedicated tables for each test result: Capacitance Tan Delta of Bushing,
Capacitance Tan Delta of Winding, Oil analysis, Core Insulation Resistance, Insulation
Resistance. Other than these tables, there are few more tables for maintaining master/nameplate details for all equipment, maintaining the health analysis results, storing the scoring
matrix etc. Once the data is fed into Health assessment server database, a complex computer
code is executed using a high-level Python Web framework (Django in this case). This code
fetches the data automatically on a daily basis and computes health index of all the
transformer and reactors using sophisticated algorithms. Apart from these, count per
category and worst-case analysis results are also computed and stored in SQL database.
Further, confidence level is calculated based on test data availability and stored in SQL
database. The user can check the DGA analysis using IEEE/IEC standards on the user
interface. The user can also analyze the trend of various test data or health index of any
equipment on the user interface.
[0054] Although the foregoing description contains many specifics, these should not
be construed as limiting the scope of the present invention, but merely as providing illustrations
of some of the presently preferred embodiments. Similarly, other embodiments of the invention
may be devised which do not depart from the spirit or scope of the present invention. Features
from different embodiments may be employed in combination.
23
[0055] The scope of the invention is, therefore, indicated and limited only by the
appended claims and their legal equivalents, rather than by the foregoing description. All
additions, deletions and modifications to the invention as disclosed herein which fall within the
meaning and scope of the claims are to be embraced thereby.

We Claim:
1. A transformer/reactor health assessment system, comprising;
infrastructure for testing transformer/reactors (i.e. sensors/testing equipment);
a network for collecting and storing the data (transformers/reactors details, test data and
analysis results) on a database server;
said server operatively accessed by a plurality of clients through a communication
channel); and
a Human Machine Interface.
2. The system as claimed in Claim 1, wherein said system has an inbuilt engine to perform
Dissolved Gas Analysis automatically, (based on latest IEEE C57.104-2019 and IEC
60599 standard) and detect any incipient fault inside the transformer/reactor.
3. The system as claimed in Claim 1, wherein said system enables centralized monitoring
of all the transformer/reactors based on Criticality level, Voltage level, Type, Make and
Age.
4. A method to characterize health of Transformer/Reactors using the system as claimed
in Claim 1, comprising the steps of ;
• testing of said transformers/reactors at site and their oil samples in oil test
laboratories;
• entering the results/values of tests performed on the equipment into the ERP
database from various sites and oil test laboratories;
• acquiring the selective test data from ERP database to Health assessment server
in predefined structured tables;
• computing parameter, test and component scores from this refined test
results/values based on a scoring matrix that calculates numeric health index;
• assigning hybrid health indices for each transformer/reactor; and
• presenting the hybrid health indices to the end user on a user-friendly
comprehensive dashboard having several buttons that displays the health of all the
transformers and reactors.
5. The method as claimed in Claim 4, wherein said method derives health indicator by
assessing raw test data wherein the parameters (21 parameters for inter-connecting
transformers, 20 parameters for converter transformers, 19 parameters for coupling
transformers and 20 parameters for line and bus reactors) are chosen for evaluation and
their assigned unique weightages, provides concrete information on health of
Transformer/Reactors.
6. The method as claimed in Claim 4, wherein said method makes optimal utilization of
multiple indexing techniques (Numeric Health index (0 to 10), Non-numeric i.e. colour
coding, Count per category and Worst-case approach) to accurately evaluate and
represent the health of transformers and reactors.