INTEGRATING PLANT-LEVEL CONTROL AND DATA SYSTEMS WITH
ENTERPRISE-LEVEL INFORMATION SYSTEMS
TO ACHIEVE IMPROVED OPERATIONAL EFFICIENCY AND
BOTTOM LINE FINANCIAL PERFORMANCE
Peter Lobner
Manager, Power Systems Operation
Data Systems & Solutions, LLC
A joint venture between Rolls-Royce plc and SAIC
The highly competitive, deregulated market is the primary driving force for integrating
plant-level control and data systems and enterprise-level information systems.
The primary reason for management to move forward and integrate plant-level and enterpriselevel systems is to provide itself with the information resources needed to operate and manage
assets in a manner that consistently generates improved profits in a deregulated, dynamic
marketplace. For the electric power industry, the term “plant”, as used in this paper, is a major
asset such as a power generating unit or station, a transmission and distribution (T&D)
substation, or a network management facility. The “enterprise” is the corporation, which may be
a utility, an independent power producer (IPP), or an independent system operator (ISO).
Important factors in the business case for proceeding with integrating plant-level control and data
systems and enterprise-level information systems include the following:
Business Case Factor
Issue / Solution
Enable “faster, better, and cheaper” (1) Market pressures are forcing existing utility
modes of operation.
organizations to re-invent themselves in order to
operate faster, better, and cheaper so they can continue
to sell competitively into their respective markets.
(2) Progress toward successful re-invention is enabled by
modern information technology (IT) and enterprise
application integration (EAI), which can efficiently
convert data into valuable information that is useful in
improving plant and enterprise performance.
Provide timely delivery of the right (1) Lack of the right information can be costly. It can
information needed to support
result in missed opportunities and bad decisions.
operational and business decision- (2) Determine what information is needed for decisionmaking.
making. Then provide on-line access to the applicable
information sources via an open-architecture system
with integrated applications.
(3) Enterprise application integration enables complex
decisions to be made more accurately and quickly
during operational and/or business transients.
(4) On-line simulation is a valuable resource for
performing high-fidelity “what-if” analysis.
Reduce operating and maintenance
(O&M) costs through better asset
management
(1) Evolving operational intelligence and asset
management practices support condition-based
maintenance. This has the potential for significant
savings through reduced O&M costs, but requires
access to extensive plant-level information.
(2) Managers need to know more about their plant /
enterprise in order to implement an integrated asset
management program that can balance competing
demands for performance, availability, risk, regulatory
compliance, cost, and related operational, engineering,
and business issues.
Increase operating staff productivity (1) Increased business or plant process automation can
through automation
improve staff productivity and/or reduce staff cost.
(2) A collateral benefit can be improved quantity and
quality of plant data available to plant and enterprise
users.
Increase operating flexibility and
(1) Certain remote operating strategies, which are enabled
revenue generation through
through automation, allow the plant operating cycle to
automation
be matched to the best opportunities for profitable
operation, while also reducing operating staff cost.
(2) “Just in time” business processes can be implemented,
with the potential for significant savings in inventory
and spare parts management.
Increase the value derived from
(1) Many modern data systems are being implemented
operational data
without the enterprise having defined an overall data
integration philosophy and system architecture that
satisfies both operational and business needs.
(2) The data needed to support operational and business
optimization have not been adequately defined.
(3) To date much of enterprise IT focus has been on
integrated business applications and related IT systems.
(4) Examples of plant-level data systems that contain
valuable operational data include: Monitoring and
control systems; Work management / Computerized
Maintenance Management Systems (CMMS);
Environmental Information Management Systems
(EIMS); Process simulation systems.
(5) A significant amount of the needed plant data currently
exists only on paper or in subsystems that do not
support on-line communications with potential users of
the data. Technology exists to make these data broadly
available via an integrated network.
(6) Transformation and transportation of data are
expensive. Therefore, selection of the right system
architecture and integrated applications is an important
decision.
Reduce the cost of creating useful
information from raw data
Improve information distribution
while reducing the cost of
distribution
(1) Without an integrated information resource, an
inordinate amount of time and expense is expended by
staff responsible for gathering data from diverse data
sources, conducting analysis, and generating the
information needed by plant and enterprise managers.
(2) A data mining, integration, analysis, and visualization
tool must be part of the overall system architecture.
(1) Electronic distribution of information using available
e-mail and web-based technologies can greatly
simplify how information is distributed, improve the
timeliness of the information, and reduce the cost of
distribution.
(2) Access to information and applications via a web
browser interface reduces network configuration
management issues and software license cost.
The business case for data integration centers on the following points:
A powerful market-based reason to proceed with integration exists now: potential loss of
competitiveness and ability to sell in the intended market.
Transformation and transportation of data are expensive. Intelligent choices during design
and implementation of an integrated information resource can reduce the cost of information
to the enterprise.
The technical means exist to accomplish integration with currently available technology.
Effective integration of plant-level and enterprise-level systems
requires attention at all levels of the integrated system and
implementation of an “appropriate” system architecture with integrated applications.
Technically, it is easier than ever before to deploy a cost-effective solution that integrates plantlevel control and data systems and enterprise-level information systems. From the perspective of
a systems integrator, an “appropriate” open-architecture solution can maximize the benefits of
installed data sources and systems while enabling integration of new, best-in-class technologies
and products that meet the specific needs of the enterprise. Goals for an “appropriate” openarchitecture solution include:
Increased data availability,
Increased data quality and delivery speed,
Reduced multiple processing of the same data, and
Improved system scalability and adaptability to changing needs
A tailored approach built on industry standard hardware and software to the extent practical, but
with an eye toward emerging technologies, can meet these goals.
Issues related to selection of an “appropriate” open-architecture are discussed in following text.
Conventional Data Integration Architecture
A conventional representation of the data integration process within an enterprise is a multi-level
triangle, with each higher level integrating data from the lower levels and yielding analysis
results and summary operational and business information of value to the enterprise. An
important goal is to accomplish significant data reduction while generating value-added
information for the plant and enterprise managers. This conventional representation of a
hierarchical information system is shown in Figure 1.
Functions associated with each level are described briefly below. High-bandwidth connectivity
between levels tends to make the levels transparent to the user.
Level 1:
This is where the original data sources interface directly with the plant. At the lowest level of
the triangle, field sensors define the current value or state of each parameter that is monitored.
Also at Level 1 are the output devices actuated by local or supervisory control systems. Note that
Level 1 also includes simple gauges, meters, and other indicators that are read manually by the
operating staff, with readings often logged only on paper. A significant amount of data exists on
paper media and is not generally accessible to plant or enterprise users unless it is converted to
electronic form.
Level 2:
The Level 1 input signals are processed at Level 2 by a data acquisition subsystem (DAS), a
local control subsystem, a programmable logic controller (PLC), a remote telemetry unit (RTU)
or similar device. Many existing subsystems at Level 2 are proprietary and do not provide
connectivity to modern, open-architecture networks. Hand-held computers can be considered as
Level 2 devices that can be used to originally collect in electronic form some or all of the
manually acquired data. Web technology can be implemented to allow some Level 2 devices
and subsystems to communicate via Internet protocols to Level 3, 4, or 5.
Level 3:
These are the supervisory control systems and plant monitoring system. Data from these systems
can be archived to an on-line “historian” database server or an off-line archive. In some cases,
only a short-term circular archive file exists and data are written over when the circular file is
full. Integration of data systems at Levels 1, 2 and 3 has long been common practice in the
electric power industry. Nuclear power generating station plant process computer (PPC)
systems, fossil generating station digital control systems, and T&D substation control systems
are among the types of Level 3 systems that integrate data from Levels 1 and 2. Web technology
can be implemented to allow some Level 3 subsystems to communicate via Internet protocols to
Level 4 or 5. This approach can be used to implement distributed remote controls.
Level 4:
Plant-level data and information integration focuses on various applications for operational
process optimization and reduction of O&M cost. In many cases, these plant-level applications
are not integrated and value-added data are not shared effectively within the plant or between the
plant and the enterprise. Application integration is an important issue at level 4. A data mining,
integration, and visualization application also is an important resource at this level. “Thick
client” and “thin client” interfaces exist between Levels 4 and 5.
Level 5:
The enterprise-level links the various plant-level networks and serves as the environment for
running broader enterprise-level operational and business applications. These may be run via
“thick client” or “thin client” interfaces between the applications and the users. The “thin-client”
interface allows users to access applications and data sources directly from a browser
environment. Level 5 business and operational applications are becoming increasingly
integrated, so some value-added data are shared effectively. Application integration is an
important issue at level 5. A data mining, integration, analysis, and visualization application also
is an important resource at this level. The corporate Intranet is hosted at this level along with
interfaces to external value-added networks and the Internet, which link the enterprise to the
world of customers, vendors, subcontractors, and others outside the boundary of the enterprise.
Architectures for Implementing Web-based Technology
Layers in information system architectures can be detrimental to system performance. Layers
can impede data flow, reduce system reliability and availability, and require some data
duplication. Technological advances are enabling alternate architectures that can reduce the
number of layers in some portions of an integrated information system. For example,
deployment of Internet technology into lower-level devices and subsystems allows these webenabled objects to establish connectivity directly to the enterprise Intranet, bypassing one or
more of the intervening layers shown in Figure 1.
The availability of a very inexpensive “web server on a chip” sets the stage for widespread
introduction of web-enabled, low-level devices and subsystems. With this type of web-based
connectivity, enterprise-level systems at Level 5 can have the capability to communicate directly
with many lower-level subsystems to implement remote monitoring and diagnostics, archive data
retrieval, and distributed remote control, including operational optimization.
In the near-term, an integrated system architecture implementing web technologies will be a
hybrid system. There will still be a conventional hierarchical component of the architecture
linked via the Intranet / Internet to web-enabled devices and subsystems. An example of this
type of hybrid system architecture is shown in Figure 2.
In the longer-term, there will be greater use of web-based technologies, including “thin-client”
user interfaces and web-enabled devices and subsystems, and a continuing migration of data
systems toward a flatter (fewer layers) architecture.
Opportunities for Improvement
With the continuing evolution of IT hardware and software, opportunities for improving the
integration of plant-level control and data systems with enterprise-level information systems
need to be periodically reassessed. Good opportunities currently exist in the following areas:
Collection and integration of plant-level data to yield value-added information,
Flow of plant-level information into enterprise-level systems, and
Use of plant-level information in operational and business processes.
A summary of such opportunities is provided in Table 1. The relative merits of each opportunity
should be evaluated on a case-by-case basis as part of an overall systems engineering effort to
define a tailored solution set that meets a particular utility’s needs.
The business case needs to address how various impediments to integration
will be overcome.
There are many plant and enterprise-specific impediments to integration that should be addressed
in the business case for integration. Examples of issues to be resolved when planning for
integration include the following:
Some local control subsystems, supervisory control systems, and monitoring systems are not
connected to a plant-level network. There is no connectivity to Levels 4 and 5.
Some local control subsystems were originally designed as stand-alone systems.
Some are proprietary systems that require custom communications drivers.
Some plants do not yet have a complete plant-level network and some plant-level networks
are not connected to an enterprise-level network. There is incomplete connectivity between
Levels 4 and 5.
Organizational priorities and associated budget constraints may limit the resources available
to accomplish integration of plant and enterprise systems. A phased approach may be needed
to match budget authority.
Organizational “fiefdoms” may hinder integration and/or sharing of information resources.
Protective feelings of “ownership” of specific information resources need to be overcome or
ways must be found to access the data without significantly changing organizational
responsibilities for “ownership”.
Data security issues need to be addressed to ensure that mission-critical and proprietary data
are not compromised.
Some benefits of integration may not be obvious.
We don’t exactly know what to do with all the data when we finally get access to it.
For example, a standard, comprehensive set of condition monitoring algorithms does not
yet exist for the electric power industry.
The basic solution set for integrating plant-level and enterprise level systems is an openarchitecture, distributed system with best-in-class applications that are effective at
mining, integrating, analyzing, visualizing, sharing, and reporting data.
There are many ways to implement the basic solution set described above. Unique customer
requirements will necessitate custom solutions. However, underlying each custom solution will
be a common core technology. Two examples of open-architecture solutions incorporating
certain web technologies are shown in Figures 3 and 4.
The system in Figure 3 shows a possible integrated solution set for a representative fossil power
generating plant. The plant-level portion of this solution set is linked to the enterprise-level via
“thick-client” and “thin-client” interfaces. Major features shown in this figure are the following:
Conventional digital control systems (DCS) are linked to optimization applications to
improve operational performance (i.e., reduce NOx emissions consistent with other
operational and/or business constraints).
Integrated master sequencing controls interface with existing DCS and provide the capability
for “single pushbutton” startup and shutdown of a generating unit.
Distributed remote controls using a web interface allow the enterprise to exercise certain
controls to optimize revenue generation by the generating unit.
A long-term archive is the primary repository of field and calculated data from plant systems.
Other on-line data sources also exist at the plant.
Manually acquired data are collected in electronic form and uploaded to the long-term
archive.
A data mining, integration, and visualization application provides access to key on-line plant
data sources via a common user interface. This application also provides “thick client” and
“thin client” interfaces to enterprise applications and users. Plant-level information can be
placed on the web automatically and managed by this application.
An integrated maintenance optimization application is comprised of the data integration
application and a work management application. The integration application collects current
data, performs condition assessments, and passes maintenance priorities to the CMMS for
execution.
Control room automation applications assist the operator in managing logs, equipment
tagouts, key control, specification compliance, and other traditionally manual tasks.
The plant simulator can “snap” to current plant conditions based on current values in the
long-term archive and then be used to support operational “what-if” analysis.
A comparable integrated solution set for a representative U.S. nuclear power generating plant is
shown in Figure 4. The primary differences in comparison to the representative fossil power
generating plant are to the left of the long-term archive in Figure 4:
No distributed remote controls.
Addition of a plant process computer (PPC) running various nuclear applications.
Addition of a real-time server to act as a “firewall” between the real-time monitoring system
and other users of real-time data.
For a transmission and distribution (T&D) utility, the integrated solution set shown in Figure 5
embodies many of the same features as the representative fossil power generating plant solution
set:
Distributed remote controls implemented in the Energy Management System (EMS), which
manages the transmission network.
On-line simulation and optimization applications to guide EMS operators.
“Thin client” and “thick client” communications pathways where appropriate.
A substation computer (substation control point) which enables data from proprietary and
non-open architecture low-level subsystems and devices to be collected and made available
to plant and enterprise users.
The basic architecture of the systems shown in Figures 3, 4, and 5 and many of the information
subsystems are the same. In fact, the same basic architecture and information subsystems apply
to other industries.
With reference to Figures 1 and 2, the key challenges to integrating plant-level control and data
systems and enterprise-level information systems are the following:
(1) expanding the scope of monitoring at Levels 1 and 2 to meet the growing information needs
for condition monitoring and integrated asset management at Levels 4 and 5,
(2) linking Level 2 and 3 systems to Levels 4 and 5, and
(3) implementing comprehensive Level 4 and 5 systems with the integrated analytical and
information management capabilities needed by plant-level and enterprise-level managers.
The balance of this paper describes technical solutions for meeting these challenges.
Solutions for expanding the scope of monitoring at Levels 1 and 2
Determine what data you need and what you are willing to pay for acquiring it
The need for expanded plant-level data acquisition is driven largely by the operational desire to
provide more comprehensive status and condition monitoring of assets. The basis for defining
equipment condition can be derived from utility experience or industry best practices. Models
for status and condition monitoring of electric power utility assets are being developed and/or
implemented under several Electric Power Research Institute (EPRI) initiatives, including
Maintenance Monitoring Workstation (MMW) and Utility Communications Architecture (UCA).
For an individual utility, the business case needs to define a prioritized data acquisition
expansion strategy. Expansion should be justifiable for:
Improving condition monitoring of high-value assets and other assets with long-lead
replacement times. Loss of such assets can have significant financial implications.
Supporting decision-making processes and tradeoff analyses used by management to guide
the profitable operation of the enterprise.
As the monitoring capability is expanded, there should be a decreasing return on investment
from additional monitoring. At some point, the enterprise will determine that it has on-line
access to sufficient data to support most operational and business decisions and further
expansion is not cost-effective. However, future technological advances, particularly in the area
of miniature sensor technology, wireless local area network (LAN) technology, and “web server
on a chip” may allow future expansions in monitoring capability that are not economically
justified today. Periodic re-evaluation is advised.
Choose a cost-effective approach for acquiring the additional data
A significant investment by utilities has been made in existing field data systems, some of which
do not communicate effectively, or at all, to higher levels in the network. To maximize the use
of installed plant and substation hardware, it is possible and practical to add data
communications links between the plant-level network and existing field sensor subsystems
and/or local control subsystems. Pilot demonstrations of this approach are being conducted
under the EPRI-sponsored Integrated Monitoring and Diagnostics (IMD) program. While open
communications protocols are preferred (i.e., TCP/IP, OPC), other communications protocols
have to be used with proprietary subsystems from some vendors.
Miniature, low-cost sensor technology, wireless LAN technology, and web-based technologies
are rapidly advancing. It is practical to combine these technologies and add new, low-cost
sensors with wireless data acquisition hardware that can communicate to higher-level systems
via TCP/IP or web protocols . The wireless LAN avoids the cost of hard-wiring the sensors, and
should allow more rapid deployment and integration of new sensors.
A great deal of operating data is acquired using manual logs on paper media. Instead of adding
sensors, a more cost-effective approach may be to use hand-held computers and a data
management application to collect field data in specified, electronic form. Once collected, the
data can be upload to an on-line archive at the completion of a plant tour.
Solutions for linking Level 2 and 3 systems to Levels 4 and 5
Add communications connectivity where it currently does not exist
The desired connectivity can be implemented in several ways. One approach is to replace
existing hardware with all new modern subsystems that use standard communications protocols
to communicate to higher-level systems. This approach can require a significant capital outlay to
purchase the new hardware. In addition, the wholesale replacement of legacy systems can result
in an outage that is longer than desired.
Another approach is to add communications connectivity in a phased approach until all desired
subsystems are linked to Levels 4 and 5. This approach can allow capital outlays to be spread
over several budget cycles while shortening the time required to implement any of the individual
upgrade phases. An added benefit should be reduced impact of the upgrades on the critical path
for completing an outage.
EPRI’s UCA defines the architecture for a T&D substation local network in which a hub device
(i.e., a substation computer subsystem) communicates with the various substation Level 1 and 2
devices and then communicates directly to higher level systems. This approach is intended to
reduce cost by eliminating independent communications links between individual Level 1 and 2
devices [remote telemetry units (RTUs), protection relays, breaker wear analysis (I 2T)
subsystem, transformer oil gas subsystem, load tap changer subsystem, remote pole-mounted
devices] and higher-level systems. This approach can allow a utility to retain existing
subsystems while adding a modest substation computer subsystem, which can include a web
portal for direct communications to higher-level systems via the Intranet / Internet.
Add local condition monitoring and exception reporting capabilities
Another potential benefit is derived from using the substation computer to perform local
condition monitoring and other value-added analysis and record keeping. This approach
distributes some of the computational load to low-cost local computers, which reduces the load
on higher-level systems. Routine data and analysis results can be scheduled for upload to a
designated server during periods of low network activity. The substation computer can report by
exception when an off-normal condition exists and warrants timely attention. This approach
helps manage network traffic and limit the bandwidth needed to support all network users.
Improve communications bandwidth between field subsystems and higher-level systems
Some existing field systems communicate to the plant-level network via relatively slow modems
(1200-baud modems are still in use in some cases). As new monitoring capabilities and remote
control capabilities are added, the need for greater communications throughput may become a
pressing issue. Adequate communications capability between levels is a key requirement for
integrating field and plant-level systems with the enterprise-level system.
Solutions for implementing comprehensive Level 4 and 5 systems with
integrated analytical and information management capabilities
Provide means for integrating data from disparate data sources
A data mining, integration, and visualization application is needed to “drill-down” through data
sources and simplify examination and analysis of related data from multiple, disparate data
sources. This application should allow access to data from disparate data sources via a common
user interface. In effect, this type of application creates a “virtual” data warehouse that can be
used in conjunction with, or as an alternative to a physical data warehouse. Careful definition of
asset nomenclature and open database structures greatly simplify integration of data from
disparate sources.
Implement improved means to interpret operational data
Automated condition monitoring and ranking applications such as EPRI’s Maintenance
Monitoring Workstation (MMW) enable complex performance assessments to be accomplished,
ranked based on values determined by the enterprise, and linked to a work management /
computerized maintenance management system (CMMS). The ranking algorithms can take into
account a simple or complex set of parameters and can invoke computational intelligence tools
that support neural net analyses such as pattern recognition and footprint analysis. The resulting
guidance from MMW helps keep day-to-day maintenance activities focused on the priority goals
of the enterprise.
Advanced data visualization tools can help the user see data in new ways. For example, a data
mining, integration, and visualization application can overlay disparate time series data on a
common graph. This means that continuous performance data can be combined with discrete
data (i.e., information from maintenance records) to look for a correlation between the data. This
capability, coupled with a data “drill-down” capability, can help users identify root causes of
operational problems.
A significant amount of operational data currently is acquired manually on paper. Interpretation
of this data is difficult in its current form. A better approach may be to use hand-held computers
and a data management application to collect field data in specified, electronic form and upload
it to the long-term data archive. Then the data can be readily accessed by other applications for
analysis, interpretation, and reporting. Note that a hand-held computer also can provide the user
with downloaded information that is tailored to the specific needs of the user. The download can
be done at the start of a plant tour. Integrated with a radio-frequency link to the wireless LAN,
the hand-held computer can communicate from a field site to the plant-level or enterprise-level
networks. In this manner, unprecedented analytical and technical support capabilities can be
provided to workers in the field.
Neural network optimization applications can be applied for specific high-value subsystems and
processes. Such applications “learn” how to control key plant parameters over varying
conditions. The neural net application gets data from an on-line monitoring system and can
provide real-time outputs that adjust the control setpoints in a digital control system (DCS).
Provide the capability for on-line “what-if” analysis
On-line simulation of the system, plant, or business process of interest can provide excellent
support for “what-if” analysis. Modern object-oriented simulation models can be built and
deployed rapidly. The simulation models for operational units can be linked to on-line data
sources so that the starting point of the simulation is the current plant state. Consequences of
changes in performance or alignment (i.e., the “what-if” analysis) can be accurately and rapidly
assessed on the simulator. This resource can be used as an engineering or operational tool to
plan for or respond to transient conditions.
Make increased use of e-mail and web technology to disseminate information
An automated data mining, integration, and visualization application is capable of generating
results and complete reports that can be distributed via the corporate e-mail system or published
on Corporate Intranet sites. This approach provides timely, automated distribution in electronic
form of information to a broad audience. Significant cost savings relative to conventional hard
copy distribution can be realized.
Conclusions
Effective integration of plant-level control and data systems and enterprise-level information
systems is essential for implementation of an integrated asset management strategy that
balances operational and business concerns.
A powerful market-based reason to proceed with integration exists now: potential loss of
competitiveness and ability to sell to the intended market.
The technical means exist to accomplish integration with available technology. However,
broader implementation of Internet technologies is fundamentally changing the way users
access data and lower-level subsystems communicate to higher-level plant and enterprise
systems.
The “basic solution” for integrating plant-level and enterprise-level systems is an openarchitecture, distributed system with best-in-class integrated applications that are effective at
mining, integrating, visualizing, sharing, and reporting data.
Each plant-specific solution requires customization of the “basic solution” to meet the
enterprise’s unique operational and business needs while maximizing the benefits from the
existing investment in IT systems and infrastructure.
Acknowledgement
The author wishes to thank Mr. John Maio (DS&S Houston, TX), Mr. Walter Carr (DS&S
Gateshead, UK), and Mr. Thomas Storey (DS&S Reston, VA) for their insights regarding
approaches for integrating plant-level control and data systems and enterprise-level information
systems.
Table 1. Examples of Opportunities to Improve Enterprise Data Integration
at All Levels of the Integration Hierarchy
Level of
Description
data
integration
Level 5
Enterprise-level data
(top of the network, which enables
data
integration of data from all
integration plants, supports numerous
triangle)
enterprise-level
applications, hosts the
enterprise Intranet, and
provides secure links to
networks outside of the
enterprise
Level 4
Opportunities for an enterprise to improve the
integration of plant level systems with enterpriselevel systems
(1) Implement an enterprise-wide, open architecture,
distributed data network with the capability to
integrate and process data from the diverse data
systems of all plants / facilities / business units of
interest to the enterprise.
(2) Link operational and business applications so data
can be exchanged without duplication of effort.
(3) Implement integrated asset management
applications.
(4) Use high-fidelity simulator or other operational
decision support system to assist enterprise
managers in planning for and responding to
system-wide transient / emergency conditions.
(5) Implement / expand the capability to internally
disseminate enterprise information via an
enterprise-wide Intranet.
(6) Implement / expand the capability to conduct
electronic commerce with external entities
(customers, vendors, subcontractors, etc.).
Plant-level data network,
(1) Implement a plant-wide, open-architecture,
which enables integration of
distributed data network with the capability to
data from diverse plant data
integrate & process data from diverse data systems.
systems, supports
(2) Enable greater staff efficiency by automating some
numerous value-added
data collection, data management, and reporting
applications, and provides
functions that now are not fully automated (i.e.,
the means to flow
automated logging, tracking of compliance with
information between the
operating technical specifications, etc.).
plant and the enterprise.
(3) Implement on-line risk monitoring to focus
attention on current risk issues during operation
and potential risk issues during proposed
maintenance / testing tasks.
(4) Enable greater staff efficiency by automating
certain operational processes. Ultimately, some
plants could be automated and operated remotely
from distributed dispatching facilities, with only
minimum on-site staff.
(5) Implement plant-level integrated asset management
/ maintenance optimization applications to focus
attention on the best opportunities for O&M cost
reductions.
Level 3
Supervisory control
systems, digital control
systems,
plant monitoring systems,
protection system
Level 2
Local control subsystems,
programmable logic
controllers (PLCs), data
acquisition subsystems
(DAS), remote telemetry
units (RTUs)
(6) Use high-fidelity simulator or other operational
decision support system to assist plant-level
managers in planning for and responding to plantlevel transient / emergency conditions (i.e., define
options for system reconfiguration with least
impact on some aspect of the business).
(7) Implement advanced plant / system performance
optimization applications to get the greatest return
per unit of operation (i.e., conventional or neural
network applications linked to digital control
systems for real-time optimization).
(8) Implement / expand capability to publish plant
summary information to enterprise web site(s).
(9) Increase communications bandwidth between
Level 4 and Level 5 to support higher data transfer
rates and effective remote control from enterpriselevel locations.
(10) Define enterprise-level performance parameters
that can fed back to individual plants to optimize
their economic performance.
(1) Perform a major upgrade to modern, open
architecture hardware and software systems that
can be linked to a plant-level data network; or
(2) As an alternative to (1), perform a lesser upgrade
by adding a new computer subsystem capable of
communicating with and acquiring data from
existing local control subsystems and linking to the
plant-level data network.
(3) Define diagnostic algorithms that can be
implemented at the SCADA system level.
(4) Implement hand-held computers to enable manual
collection of data in electronic form, with enforced
data standards, and upload to Level 3 or 4 systems.
(5) Improve the human-machine interface (HMI) data
visualization capability to enhance usability of
information.
(6) Implement web-based technology to enable some
Level 3 subsystems to communicate directly via the
Intranet / Internet to Level 4 and 5 systems.
(1) Perform an upgrade and replace existing
subsystems with modern, open architecture local
controls and data acquisition subsystems that can
communicate readily with a plant-wide data
network, or,
(2) As an alternative to (1), provide existing local
control subsystems with a communications
(3)
(4)
Level 1
Sensor / transmitter units
(bottom of and
the data
control actuators
integration
triangle)
(1)
(2)
(3)
(4)
interface to higher-level systems.
Define diagnostic algorithms that can be
implemented at the local control subsystem level.
Implement web-based technology to enable some
Level 2 devices and subsystems to communicate
directly via the Intranet / Internet to Level 3 to 5
systems.
Expand scope of what can be remotely monitored
so that adequate performance monitoring and
condition assessments can be accomplished.
Expand scope of what can be remotely controlled
so that greater process automation can be
implemented.
Implement new technology to lower the cost of
adding sensors and acquiring data from the sensors.
Where appropriate, implement “intelligent” sensor
and control actuator technology to enable remote
calibration and improved diagnostics.
Figure 1. DS&S Conventional Architecture for Integration of Plant-Level and Enterprise-Level Data
Figure 2. DS&S Hybrid Architecture for Integration of Plant-Level and Enterprise-Level Data
Figure 3. DS&S Integrated Solution Set for Fossil (Steam) Power Generation
Figure 4. DS&S Integrated Solution Set for Nuclear Power Generation
Figure 5. DS&S Integrated Solution Set for Electric Power Transmission and Distribution