2. Sougata Mitra
GIS for Smart Grid
TABLE OF CONTENTS
Executive Summary.......................................................................................................................................3
Note:Interview Extract.................................................................................................................................. 3
Note:R-APDRP and GIS.................................................................................................................................. 4
Technology: Global Positioning System ........................................................................................................ 5
Technology: Diffrential Global Positioning System.......................................................................................6
Technology: Geographical Information System............................................................................................ 7
GIS for Distribution Business......................................................................................................................... 7
Components of GIS: .........................................................................................................................8
Software.............................................................................................................................. 8
GIS Data .............................................................................................................................. 8
GIS Infrastructure................................................................................................................ 8
Nucleas of GIS Data: Consumer Indexing...................................................................................................... 9
The Future: Smart Grid ...............................................................................................................................10
The Critical Role of Enterprise GIS in Smart Grid Technology .................................................................... 12
Challenges on Implementation of GIS in Power Industry...........................................................................14
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EXECUTIVE SUMMARY NOTE:INTERVIEW EXTRACT
MoP/GoI has taken numerous strategic
initiatives aiming at providing reliable quality Extracts from the Interview of Mr Devender
power supply to consumers at affordable rates Singh, Joint Secretary, Ministry of Power with
GISDevelopment.net
and towards improvement of power
distribution which is the real interface between
power utilities and millions of consumers. The Union Ministry of Power (MoP) has
Inadequate data of distribution assets facilities incorporated the use of GIS as a policy initiative in
coupled with lack of information of customer National Electricity Policy 2005 and Integrated
Energy Policy (IEP). What has been the driving
base are the main concerns of distribution
force for this?
companies. Many DISCOMs have started using
GIS for developing accurate database, improve
internal efficiency levels pertaining to power Geospatial technologies are very relevant in
supply monitoring, commercial and customer distribution and other areas of power sector. In
services. This valuable tool, GIS, is also being the Restructured Accelerated Power
Development and Reform Programme (RAPDRP),
employed for important functions like network
a major initiative of the Government of India,
analysis, FM, energy audit, trouble call reduction of aggregate technical and commercial
management, load management, theft losses in the distribution sector is a priority. One of
detection etc., Power is the most critical the important components we are targeting at is
infrastructure for the progress of any country. the proper energy auditing and accounting and
The facilitating policy framework, the the extensive use of information technology for
regulatory mechanism for investment in this purpose. As part of this, it is important to be
generation, transmission, distribution and able to do consumer indexing. If you can map right
other associated activities have already been up to the transformer and down to the last
put in place by the government. The need of consumer, you can find out exactly how many
customers are connected to each transformer and
the hour is for efficient management and
if there are any pilferages and power theft
optimum utilization of installed capacity to .Similarly, mapping can be done for all the assets in
meet the demand. the distribution network. Regular maintenance of
these systems would be possible if you deploy
Sub- Transmission and Distribution systems geospatial technologies. In generation sector,
constitute the link between electricity utilities geospatial data could be used for locating ideal
and consumers, for extending supply and sites for hydro power generation. Hydro power has
revenue realization segment. Therefore for tremendous potential in the country - to a tune of
consumers, these systems represent the face 1,50,000 MW and with 60% PLF, we can harvest
of the utility. Efficient functioning of this close to 90,000 MW. If mapping of assets is done,
segment of the utility is essential to sustain the whether it is transmission or distribution, it is easy
to locate a fault, to attend to a fault or to operate
growth of power sector and the economy.
the lines. This can also be used to plan the location
and direction of new lines based on the new
The planning and the design of the electrical generation projects that are being built.
supply system are everyday tasks for engineers
in the DISCOMs. The goal of power distribution
system planning is to satisfy the growing and changing system load demand during the planning period
within operational constraints and with minimal costs. The planning process comprises several phases,
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and one of the most important is the optimization of the
electric distribution network. The network optimization is
considered a hard combinatorial optimization problem due
to a number of limitations (network voltage level, network
structure, quantums and locations of loads, routes and types NOTE: R-APDRP AND GIS
of feeders, voltage drops, etc.). An additional complexity is
imposed by the geographically referenced data. In this Nearly every state is implementing
process it is important to have on time accurate relevant the program R-APDRP which is
(related) data and information on the electric distribution giving a new lease of life for the
system and its assets, and possibly to have data from other utilities to uplift their IT Backbone.
utilities.
GIS forms the crux of the solutions
With the radical changes that the electric utility industry is to be implemented. The time bound
facing, customer choice has become the buzzword for the ambitious project requires urban
entire country. Computerization and development of various mapping of 1:2000 & even higher
geographic information systems have opened new horizons scale maps. There has been no
for all decision-making processes as well as for manipulation Government body in India who has
and dissemination of information taken such high scale mapping
before this project. The success of
Use of GIS will facilitate easily updatable and accessible the whole program depends on the
database to cater to the needs of monitoring and success of GIS Database.
maintaining reliable quality power supply, efficient MBC
(metering, billing and collections), comprehensive energy Due to such level of investments
audit, theft detection and reduction of T&D losses. All these mainstream IT majors like TCS, HCL
measures will ultimately improve the overall internal & Infosys have ramped up their GIS
efficiency of the DISCOMs and help accelerate achieving Practice to address the project
commercial viability execution.
For further information please visit
A new period of higher significance has arrived for the www.rapdrp.gov.in
GPS/GIS function at electric utilities. To a degree never
equaled before, utility managers are looking to their GIS
programs, filled with increasingly accurate data collected by
GPS technology, before making decisions. With this capability
comes an expectation for GIS/GPS professionals to provide higher levels of planning and management of
their data collection process
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TECHNOLOGY: GLOBAL POSITIONING S
SYSTEM
GPS is a space-based radio navigation system that provides reliable
based
positioning, navigation, and timing services to civilian users on a
continuous worldwide basis -- freely available to all. For anyone with a GPS
receiver, the system will provide location and time. GPS provides accurate
location and time information for an unlimited number of people in all
weather, day and night, anywhere in the world.
The GPS is made up of three parts: satellites orbiting the Earth; control and monitoring stations on
Earth; and the GPS receivers owned by users.
The space segment consists of a nominal constellation of 24 operating satellites that transmit
one-way signals that give the current GPS satellite position and time.
way
The control segment consists of worldwide monitor and control stations that maintain the
monitor
satellites in their proper orbits through occasional command maneuvers, and adjust the satellite
clocks. It tracks the GPS satellites, uploads updated navigational data, and maintains health and
status of the satellite constellation.
ite
The user segment consists of the GPS receiver equipment, which receives the signals from the
GPS satellites and uses the transmitted information to calculate the user’s three
three-dimensional
position and time
Using the near pinpoint accuracy provided by the Global Positioning System (GPS) with ground
y
augmentations, highly accurate surveying and mapping results can be rapidly obtained, thereby
significantly reducing the amount of equipment and labor hours that are normally required of other
conventional surveying and mapping techniques. Today it is possible for a single surveyor to accomplish
onventional
in one day what used to take weeks with an entire team. GPS is unaffected by rain, wind, or reduced
sunlight, and is rapidly being adopted by professional surveyors and mapping personnel throughout the
professional
world. GPS position information for these features serves as a prime input to geographic information
systems (GIS), that assemble, store, manipulate, and display geographically referenced information.
Throughout the world, government agencies, scientific organizations, and commercial operations are
hout
using the surveys and maps deriving from GPS and GIS for timely decision making and wiser use of
decision-making
resources. Any organization or agency that requires accurate location information can benefit from the
location
efficiency and productivity provided by the positioning capability of GPS.
Unlike traditional techniques, GPS surveying is not bound by constraints such as line line-of-sight visibility
between reference stations. The increased flexibility of GPS also permits survey stations to be
increased
established at easily accessible sites rather than being confined to hilltops as previously required.
Remote GPS systems may be carried by one person in a backpack, mounted on the roof of an
automobile, or fastened atop an all terrain vehicle to permit rapid and accurate field data collection.
obile, all-terrain
With a GPS radio communication link, real real-time, continuous centimeter-level accuracy makes possible a
level
productivity level that is virtually unattainable using optical survey instruments.
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TECHNOLOGY: DIFFRENTIAL GLOBAL POSITIONING SYSTEM
DGPS (Differential Global Positioning System) is an enhancement to Global Positioning
System that uses a network of fixed,
ground-based reference stations to broadcast the
difference between the positions indicated by the
satellite systems and the known fixed positions.
Differential GPS works through two receivers one of
which is stationary and the other moving around
making position measurements.
Here is the underlying principle. GPS receivers
calculate distances by using the time signals take to
travel from satellites. This work needs signals from at
least four satellites. Each of these signals has some
errors due to different factors like disturbances in the
atmosphere. These errors can have a cumulative
effect in the final result the GPS gets. However the
satellites are so far away in space, the distances we
travel on earth are pretty insignificant in comparison.
This way the signals two receivers within a distance of
a few hundred kilometers receive have the same
amount of errors, as they have traveled the same amount of distance in atmosphere. This is the
principle put to use in DGPS. The stationary (reference) receiver is placed at a point that has been very
accurately marked and surveyed. This station is considered to receive the same GPS signals with the
same amount of error as the moving receiver. The stationary receiver then works backwards on the
equation. This means that instead of using timing signals to work out its position, it uses its already
measured position to calculate timing. It then compares how long the signals should take to travel with
the actual time they took to reach the station. The difference in the two readings gives the error
component which is common to it and the moving receiver. The stationary receiver repeats this process
for all the visible satellites encodes the information into a standard format and then relays the
information to the moving receiver. The moving receiver is thus able to make appropriate corrections.
Error Transmissions- the nitty-gritty DGPS receivers cannot transmit the corrections on their own, but
use attached radio transmitters for the corrections. The moving receiver gets a complete list of errors,
meaning errors with reference to each satellite, and applies whichever data is applicable to them. Limits
Differential GPS can eliminate only those errors that are common to both the stationary and moving
receivers. This does not include multi-path errors (these are errors that happen due to the signals
reflecting off objects like mountains, tall buildings and dense foliage), as these are happening very
close to the receiver. Further, DGPS cannot account for any internal errors within an individual receiver.
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TECHNOLOGY: GEOGRAPHICAL INFORMATION
SYSTEM
A geographic information system (GIS) integrates hardware,
software, and data for capturing, managing, analyzing, and
displaying all forms of geographically referenced
information.
Significance of GIS:
While Computer technology increases the decision maker’s
access to relevant data, the GIS provides tools to interpret that data i.e., it allows one to see
relationships, patterns, or trends intuitively that are not possible to see with traditional charts, graphs
and spreadsheets.
GIS FOR DISTRIBUTION BUSINESS
GIS (Geographic Information Systems) is a system of mapping of complete electrical network
including low voltage system and customer supply points with latitude and longitudes
overload on satellite imaging and/or survey of India maps. Layers of information are contained in these
map representations. The first layer corresponds to the distribution network coverage. The second layer
corresponds to the land background containing roads, landmarks, buildings, rivers, railway crossings etc.
The next layer could contain information on the equipment viz poles, conductors transformers etc. Most
of the electrical network/equipment has a geographical location and the full benefit of any network
improvement can be had only if the work is carried out in the geographical context. Business processes
such as network planning, repair operations and maintenance connection and reconnection has also to
be based around the network model. Even while doing something as relatively simple as adding a new
service connection; it is vital to know that users of the system are not affected by this addition. GIS in
conjunction with system analysis tools helps to do just this.
For efficient and reliable operation of a distribution system, a reliable and well knit communication
network is required to facilitate project coordination of the maintenance and fault activities of the
distribution system. GIS when integrated with real time SCADA can help in sending the right signals to
the communication network. Some examples:
• When integrated with customer information systems with geodata or geodata related
information, fast identification of locations and related information for maintenance and
emergency cases is made possible as The system enables to identify each consumer, type of
consumer, location, pole from supply is given, Distribution Transformer & Feeder from where
supply is fed
• Reliable data of network when accurately integrated with land base map aids in design,
planning, and analyzing of network thereby enabling technical loss calculation
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8. COMPONENTS OF GIS:
SOFTWARE
GIS software ranges from simple business
mapping tools to high-end technology used to
manage complex systems. GIS can be divided into
four categories:
Desktop GIS helps to analyze, map,
manage, share, and publish geographic
information on desktop computers.
Server GIS, which allows GIS functionality,
helps the data to be deployed from a
central environment.
Embedded GIS, technology that lets the GIS functionality and data to be embedded inside other
applications.
Mobile or field GIS, technologies that run on mobile devices such as PDAs, laptops, and Tablet
PCs.
GIS DATA
The backbone of GIS is good data. Inaccurate data can result in inaccurate models and maps, skewing
the results of the analysis and ultimately resulting in poor decisions. The past 10 years has seen an
explosion in the amount of data available, much of it free, with the advent of the Internet and
proliferation of commercial sources of data. Internet mapping and Web services technology has made it
possible for anyone anywhere to share or access data from around the globe. This wide availability
makes it critical to understand what GIS data is, how it is used, and how to select the right data for one’s
needs.
GIS INFRASTRUCTURE
Hardware is really a simplistic term used to describe the technology infrastructure needed to support
your GIS implementation. The infrastructure developed depends on the system requirements
determined as needed during that phase of implementation planning. Using Web services for GIS needs
minimal investment for infrastructure, while an enterprise GIS implementation requires careful planning
and a fairly significant investment for computerization, networking, database connectivity etc.,
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NUCLEAS OF GIS DATA: CONSUMER INDEXING
Customer indexing (CI) is a method for enumerating the total A customer with the
number of consumers in a utility and tagging them to their CIN as 030412900618
respective poles, transformers and feeders. would mean the
following:
The purpose of CI is to identify revenue leakages by way of
consumers who are not billed or billed under improper category The customer is
and to generate a master list of consumers. Distribution utilities drawing power
in the country, today, suffer from lack of Management from the Station
Information System (MIS) based on validated and correct data of no.03,
entities and consumers. Owing to the wide geographical spread
of utilities and dynamic nature of huge data of consumers, it is The Feeder number
always a challenge to obtain data from field on real time basis to 04 is running from
generate MIS for quick and timely decision making. Data created the station to the
manually in registers/ledgers by line men and meter readers distribution
travels to the top management without adequate checks and transformer,
balances en-route. This results in defective work estimates and
consequent delays. Customer indexing and asset codification The Distribution
system provides a platform to enable the utilities to generate Transformer (DTR)
verifiable and validated data of consumers and entities of the number is 129,
utilities.
The Pole number
006 is used to drop
Through door-to-door survey and with the help of the DGPS
wire to customer
instrument, it is possible to carry out consumer identification and
premises, and
collect data about customers such as their paying capacity,
connected load, consumer category, meter details and linkage to The Customer
last pole or service pillar from the service connection taken out Number is 18.
for consumer. Customer indexing has to be carried out in a way,
which makes it possible to relate the customer’s geographical and
electrical address with his/her revenue address. Each customer,
indexed on the basis of the initial record available with the owner
and later verified by field survey, should have an exclusive six to
eight digit numeric/alphanumeric code. Consumer code number should be used for metering, billing and
all other service functions. For generating consumer indexing, each consumer is indexed based on the
Electrical System Codification and the source of supply to the particular customer which should enable
the feeder/DT wise energy accounting. Each customer is assigned a unique Customer Identification
Number or CIN based on the source/pole/DT/Customer Number.
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THE FUTURE: SMART GRID
s mart grid is not a piece of hardware or a computer system but, rather, a concept. As its name
implies, the smart grid is about an intelligent electric delivery system that responds to the needs of
and directly communicates with consumers. While there are many facets to the concept, the smart grid
is really about three things: managing loads more effectively, providing significantly more automation
during restoration after an outage event, and enabling more interaction between energy providers
and consumers.
A smart grid gives utilities more time to increase capacity, improve energy efficiency, and help lower
greenhouse gas production. By managing loads, utilities can better leverage their lower-cost and better-
performing generating plants to reduce fuel consumption and greenhouse gases and gain higher
utilization of existing equipment. Electric companies will know the consumption of individual consumers
at any given time because smart grid technology helps markets interact with consumers. Utilities will
give consumers price signals and information about the implications of their energy usage. For example,
customers could discover the price (or cost) of turning on their air conditioners. A smart grid could
detect areas of theft of current and take measures to cut off supply.
The electric system will adapt to new conditions without human intervention once a smart grid is in
place. If a circuit were nearing its load limit, the smart grid could take action to automatically
reconfigure the network in an attempt to relieve the overloading condition. The grid can be "self-
healing" by switching around problem areas to minimize outages. Since electricity demands tend to
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spike during the hottest part of the day and year, electric companies have to maintain large reserves of
capacity. A smart grid makes best use of resources. By allowing the grid to smooth out the demands,
utilities can better utilize existing facilities. With thousands of sensors and operators equipped with a
better understanding of the way the system is running, a smart grid is predictive rather than reactive to
prevent emergencies. A smart grid will supply operators with the tools to predict a failure before it
happens. Appropriate action may be automatic. Even with today's sophisticated SCADA and
distribution management systems, operators do most of the switching based on individual
interpretation of the situation.
The key to the smart grid is the complete installation of smart meters that provide
a link between consumer behavior and electric energy consumption. A smart
meter is an electric meter that measures consumption for a very small
interval of time (seconds or less), saves that data to memory, and
communicates directly with the utility. The smart meter can also
communicate energy use to the consumer. Some smart meters can
automatically disconnect the load and block power from flowing. For a smart
meter to work, there must be a link from the meter to devices within the
consumer's home or facility as well as communication between the smart meter
and the utility. Many electrical appliances are equipped with internal devices that
connect to smart meters. Smart meters will be able to communicate and even control devices within the
consumer's home or business. When there is a power failure, the smart meter alerts the utility of
outages. During a peak power emergency, the utility tells the smart meter to shut off selected loads as
allowed by tariffs. Since smart meters are not limited to measuring electricity, we may see smart meters
used by gas and water utilities as well.
A smart grid will require energy storage systems to level the peak and enable utilities to access the most
efficient and environmentally sound power generation options. Energy storage systems could be
enhanced batteries, flywheels, or compressed air systems. Most outage management systems (OMS)
use sophisticated prediction engines based on customer phone calls and network models to determine
outage locations. An OMS linked to a smart grid will rely on a sensor network for faster, more accurate
response. In a smart grid, the OMS will converge with the distribution management system (DMS) to
form an automated analytic engine. The DMS provides the means to reconfigure and analyze the electric
network. A DMS integrated with an OMS will enable utilities to make decisions based on information
from the sensor network and smart meters about loading, predictive equipment failures, outages, and
restoration.
In most electric utility systems today, the utility is virtually blind to problems in the field. The smart grid
will have sensors to detect fault, voltage, and current along the distribution network and communicate
with the central smart grid processors. Most electric systems around the world are able to communicate
very little about the state of the system other than the main supply substations. The crux of the smart
grid is the ability to communicate the state of the system from the sensor network to both the utility
and the customers. The electric distribution system will grow from a single network to an integrated
dual network system. One network will represent the power system, and the other will represent an
advanced communication network. Utilities need a means of collecting data from the sensors and smart
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meters to make decisions about self-healing the grid, load shifting, and billing. Self-healing means that
the electric distribution system will configure itself to limit the extent of customer outages without
human intervention. A sophisticated data management system will store historic and current real-time
data about the system from meters and sensors. Traditional SCADA systems are early smart grid
technologies. However, the reach of SCADA is usually limited to substations and a few major distribution
automation devices like remote-controlled disconnect switches. The data managed by SCADA plays an
important part in any smart grid implementation. A smart grid will need real-time analytic engines able
to analyze the network, determine the current state and condition of the system, predict what may
happen, and develop a plan. These engines will need data from the utility and outside parties such as
weather services. The combination of smart meters, data management, communication network, and
applications specific to metering is advanced metering infrastructure (AMI). AMI plays a key role in
smart grid technology, and many utilities begin smart grid implementation with AMI.
THE CRITICAL ROLE OF ENTERPRISE GIS IN SMART GRID TECHNOLOGY
GIS is widely recognized for its strong role in managing traditional electric power transmission and
distribution and telecommunications
networks. GIS will likewise play a
strong role in managing the smart grid.
For utilities, GIS already provides the
most comprehensive inventory of the
electrical distribution network
components and their spatial locations.
With the smart grid's sophisticated
communication network superimposed
on the electric network, data
management with GIS becomes utterly
critical. Enterprise GIS is a framework
or platform that underpins an electric
utility information technology system.
Other platforms that make up the
utility IT system include SCADA,
customer billing/financial systems, and
document management systems.
Enterprise GIS authors, or creates, spatial information about utility assets (poles, wires, transformers,
duct banks, customers) and serves that information to the enterprise. The core business applications
then mash up, or combine, the data served from the GIS, SCADA, and customer systems along with
other information from outside the utility such as traffic, weather systems, or satellite imagery. Utilities
use this combined information for business applications, from visualizing a common operating picture to
inspection and maintenance to network analysis and planning.
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GIS will help manage data about the condition of utility assets. After parts of the system go into
service, utilities must manage the system through the collection and maintenance of asset
condition data. Some condition data can come from automated systems, and other data can
come from inspection systems. Utilities are rapidly adopting GIS-based mobile devices for
inspection and maintenance. Enterprise GIS, with its desktop, server, and mobile components,
allows utilities to gather condition data.
The power of GIS helps utilities understand the relationship of its assets to each other. Since
the smart grid is composed of two networks—electric and communications—utilities must
understand physical and spatial relationships among all network components. These
relationships will form the basis for some of the advanced decision making the smart grid
makes. A smart grid must have a solid understanding of the connectivity of both networks. GIS
provides the tools and workflows for network modeling and advanced tracing.
GIS also helps utilities understand the relationship of networks with surroundings. GIS can help
identify relationships between systems and the environment.
From a smart grid perspective, GIS allows utilities to visualize the electric and communications
systems and the relationship that exists
between them. In the United States, utilities do not
monitor the vast majority of distribution
It goes well beyond the traditional "stare and transformers. If the load on any of these
compare" method commonly used by transformers rises beyond capability, they
utilities to a notion of seeing relationships. fail. With monitoring, the smart grid would
GIS provides a means to monitor and express be able to determine whether the
the health of the system in an obvious way transformer has experienced past stresses
with commands such as, "Show me all the and therefore lost longevity. As the
sensors that have failed to report results in transformer approaches a dangerous limit,
the last hour." GIS can show the real-time the smart grid could take preventive
view of the grid and note where things are measures to avoid the catastrophic failure
changing. In effect, GIS (as compared with a of the transformer. Within GIS, operators
SCADA system) shows the complete state of would then perform a spatial analysis to
the grid, represented by a realistic model in determine the risk of failure and customer
a way that people understand. As the heart impact. The smart grid algorithms, in
of the distribution system, GIS can actually concert with the GIS, could determine
control parts of the grid. The technology can whether to reduce the load at customer
recommend ways to get the grid back to sites, reconfigure the network to relieve
normal after an abnormal event. Or it can the load, or perform preemptive
automatically have the grid do something switching.
different. A smart grid driven by a GIS would
adapt to changes based on information from
the thousands of sensors to help prevent
outages and equipment failure.
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CHALLENGES ON IMPLEMENTATION OF GIS IN POWER INDUSTRY
It is hard to imagine implementing a smart grid without a detailed and comprehensive network model
contained within the GIS. Utilities face a number of challenges to ensure the effectiveness of a smart
grid program.
The data quality that exists in the GIS must be outstanding. It is one thing to have a few errors
on a planning or asset management map. While not desirable, it is even somewhat tolerable to
have some inaccuracies in the GIS data that feeds outage management systems. However, it is
not acceptable to have incorrect data in a system that automatically controls the electric
distribution system. Errors could result in increased outages or, worse, accidents.
There are a number of excellent standards for processing critical infrastructure data. Those
standards and processes should be tested and strictly adhered to. Historically, utilities
maintained a large backlog of documentation about completed work in the field (as-built
sketches and accumulated work orders) to be posted to the GIS. Utilities must measure the time
spanning from when a change occurs in the field to when the change is reflected in the GIS.
Utilities are now able to build a GIS on an accurate land base. Since GIS has been used by
utilities for more than 20 years, it predates GPS. Utilities that continue to base facility location
on antiquated grid systems will not be able to successfully use GIS until they make the land base
and facility information spatially correct. There are advanced tools to assist in the corrective
process, but it is still highly labor intensive and time consuming. For utilities that have not yet
built a comprehensive GIS for infrastructure, the goal should be an accurate, GPS-compliant land
base.
Lack of a digital model of the electrical system—whether urban, overhead, underground,
networked, radial, or some combination therein—will limit the overall effectiveness of the smart
grid. Some utilities have built a GIS piecemeal, with some parts of the service territory converted
to digital form and others still in CAD or even paper form. Many have only converted primary
data and not secondary networks. Others have converted rural overhead areas but have not
converted urban networked areas. The piecemeal approach is not effective if GIS is to be the
heart of a smart grid. Installing smart meters in areas where the utility has not modeled the
electric network will inhibit much of the usefulness of the equipment. In this case, the use of the
smart meter would probably be limited to billing.
A large problem for utilities is the lack of good customer addressing information. Even in
countries where virtually all premises have a physical address, utilities struggle to keep data
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current. Some utilities don't have tight processes to make sure new customer data is linked
directly to the GIS. If GIS does not have an exact correlation of the customer premises and the
electric system, any hope of automation and self-healing will be lost. In regions where customer
addresses don't exist, utilities will need to create some kind of coding system that uniquely
identifies a customer location to a point in space and to the electric distribution system.
Otherwise, it will be impossible to build a smart grid. Once the system is in place, it is critical
that utilities have a foolproof quality assurance process that guarantees that as they add new
customers to the system, those customers are reflected as connections to the electrical
network.
Since the idea behind the smart grid is to add more monitoring capability and control to the electric
system, enterprise GIS is fundamental to its success. It is imperative to have a solid model of all electric
assets including their condition and relationships to each other, to customers, and to the
telecommunications systems that will drive the smart grid. Utilities must have processes and procedures
in place to ensure accurate and timely GIS data so that the smart grid will be able to make automated
decisions based on correct information. Today, utility dispatchers make the vast majority of switching
decisions based on human interpretation. Without human intervention, the smart grid must rely on a
near-perfect GIS model of the electric system.
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