ArticlePDF Available

Abstract and Figures

In this paper, the OPC UA is introduced as a key technology for realizing a variety of Smart Grid use cases enabling relevant tasks of automation and control. OPC UA is the successor of the established Classic OPC specification and state of the art regarding information exchange in the industrial automation branch. One of its key improvements over the Classic OPC is that the area of application is no longer restricted to industrial automation but OPC UA can be applied almost in every domain facing challenges in automated control. This improvement stems from a more generic and object-oriented approach. For the adoption of OPC UA to Smart Grids, two of the most important data models - the Common Information Model (CIM) and the IEC 61850 - have been identified to be integrated into OPC UA communication. In this contribution, basic OPC UA features and functionalities (information modeling, communication services, and information security) are introduced and discussed in the context of Smart Grids.
Content may be subject to copyright.
OPC Unified Architecture: A Service-Oriented Architecture for Smart Grids
Sebastian Lehnhoff, Sebastian Rohjans, Mathias Uslar
R&D Department Energy
OFFIS - Institute for Information Technology
Oldenburg, Germany
{lehnhoff, rohjans, uslar}
Wolfgang Mahnke
Industrial Software Systems
ABB Corporate Research Germany
Ladenburg, Germany
Abstract—In this paper, the OPC UA is introduced as a
key technology for realizing a variety of Smart Grid use cases
enabling relevant tasks of automation and control. OPC UA
is the successor of the established Classic OPC specification
and state of the art regarding information exchange in the
industrial automation branch. One of its key improvements
over the Classic OPC is that the area of application is no
longer restricted to industrial automation but OPC UA can be
applied almost in every domain facing challenges in automated
control. This improvement stems from a more generic and
object-oriented approach. For the adoption of OPC UA to
Smart Grids, two of the most important data models the
Common Information Model (CIM) and the IEC 61850 have
been identified to be integrated into OPC UA communication.
In this contribution, basic OPC UA features and functionalities
(information modeling, communication services, and informa-
tion security) are introduced and discussed in the context of
Smart Grids.
Keywords-Automation, Communication, Service-Oriented
Architectures, Smart Grids, Standardization, OPC UA
The current transition process in the electric utilities
domain and power systems in general aims at establishing
the so called Smart Grid combining different views, defini-
tions, and aspects of existing concepts in the electric energy
domain. One aspect appears to be a commonality between
all existing definitions: the increasing use of Information
and Communication Technologies (ICT) in order to support
automation and energy distribution functionalities for Energy
Management Systems (EMS) and Distribution Management
Systems (DMS). The result of an integration of those two
technological scopes will be an increasingly complex and
highly dynamic power system with a multi-dimensional
Looking at other domains, e.g. commerce, manufacturing
or logistics, the introduction of ICT-based technologies and
mechanisms lead to profound changes in the processes
behind core services and businesses. When looking at indus-
trial automation strong parallels to the utility domain become
apparent. Both application domains were, respectively are
characterized by monolithic software systems and their sup-
ported processes. In industrial automation, the introduction
of re-usable software components replaced this approach.
However, aside from real and obvious advantages, this
posed novel challenges, e.g. standardized interfaces became
more and more important to avoid costly and labor-intensive
integration work. Furthermore, the need for high perfor-
mance Human Machine Interface (HMI) and Supervisory
Control and Data Acquisition (SCADA) applications and
their vendor-specific proprietary interfaces required the de-
velopment of appropriate standards in terms of both syntax
and semantics. For this purpose, joined vendor-driven ini-
tiatives like the OPC Foundation established basic building
Initially, the OPC task force aimed at creating a stan-
dard for accessing real-time data based on Microsoft’s
OLE/DCOM technology for Windows operating systems.
This work resulted in the creation of the OPC Classic,
which is the prevailing standard in industrial automation,
today [1]. OPC Classic covers aspects like data reading,
writing and supervision of procedures (OPC Data Access),
sending alarms (OPC Alarms & Events) and accessing
saved historical process data (OPC Historical Data Access).
Furthermore, extensions to those basic building blocks exist
(OPC Complex Data, OPC Batch, OPC Data exchange)
and some first platform-independent specifications for web
service-based interaction (OPC XML-DA).
In [2], the ten most important drivers to create the new
OPC Unified Architecture (UA) are discussed, among which
the end-of-life cycle of COM/DCOM, the rising need for
Internet-based communication, platform-independence, and
using a common information model are listed as the most
prominent factors.
The following sections of this contribution provide an
overview of OPC UA and focus on its application to Smart
Grid communications for both automation and communica-
tion systems. Section II provides two relevant scenarios of
automated control and monitoring in the context of Smart
Grids. Section III discusses the OPC Unified Architecture.
In Section IV, we introduce the mapping of common energy
domain data models onto the OPC UA and finally in Section
V, we argue for OPC UA adoptions to the Smart Grids
scenarios. Section VI provides some concluding remarks and
provides an outlook on our current and future work.
2012 IEEE
SE-SmartGrids 2012, Zurich, Switzerland
Future Smart Grids emphasize the (at least) partial co-
ordination of a large number of stochastic appliances to
balance consumption and generation of electrical energy.
Due to the sheer number and complexity of the overall
system automated means of measurement and (partially
unsupervised) control are indispensable.
A vivid example of the need for automated monitoring and
control is the supervision and operation of offshore wind
farms using the example of the German ”Alpha Ventus”,
which is the first German offshore installation that was
constructed on the high seas. The pilot project is located
some 45 kilometers from the coast of Borkum and pro-
vides fundamental experience not only in the construction
of an offshore wind farm but also on the operation of
such a system that may not be directly accessible due
to varying weather conditions. Twelve 5-megawatt class
wind power turbines are operating at the Alpha Ventus test
field: six AREVA Wind M5000 turbines and six REpower
5M turbines, resting on two different foundations. Whereas
the AREVA wind turbines stand on tripods, the REpower
turbines are mounted on jacket foundations in a water depth
of 30 meters. In order to provide the required wind yield
which is considerably higher compared to its onshore
counterpart to compensate for the significantly higher
investment and operational costs individual turbines have to
be monitored in real-time and appropriate control actions
optimizing turbine configuration (angle, speed etc.) have to
be calculated and taken immediately.
A second example that is becoming increasingly important
is distribution grid automation. Future Smart Grids will con-
sist of flexible appliances and controllable operating equip-
ment actively contributing to power quality and guaranteeing
high supply reliability for its customers. Main tasks will be
operation and maintenance of distribution system assets in
order to improve quality of service, reducing operating costs,
and increasing operational efficiency. In liberalized markets,
utilities are sometimes even required to report on reliability
performance and issues of quality, or have to define explicit
performance targets, which may be penalized in case of
violation. Distribution grid automation may also support
applications such as fault detection and location as well
as providing safety-critical ancillary services in real-time.
In order to meet customer expectations of supply reliability
inexpensive technological concepts for system development
and operation are necessary.
Both examples presented here illustrate and exemplify
the need for a service oriented automation and control
architecture within current, respectively future Smart Grid
scenarios and will be picked-up in Section V.
OPC UA defines a set of services in a Service-oriented
Architecture (SOA)-based fashion for communicating data.
In order to understand the services’ functionality first the
information modeling capabilities of OPC UA are described
explaining the data the services have to deal with. Af-
terwards, the communication services are explained and
information security is considered. Finally, the approaches
on standardizing information models based on OPC UA are
A. Information Modeling with OPC UA
In addition to the transport of data, i.e. the communica-
tion, OPC UA also provides the possibility of information
modeling. Information modeling allows enriching data with
meta-data and thus exchanging information with known
semantic rather than just exchanging pure data. Using the
OPC UA mechanisms the information modeling can be done
vendor-specific or using standardized information models.
Especially when using a standardized information model, a
new level of interoperability can be reached. Not only data
is exchanged in an interoperable way, but information with a
clearly defined semantic. To define information models OPC
UA provides a meta-model, called address space model in
the specification (Part 3 [3]). This model consists mainly
of nodes and references between nodes. Depending on their
meaning the nodes are separated into node classes. For each
node class there is a set of attributes describing the node.
Common attributes cover the name and an unique identifier
(NodeId). Other attributes are only deployed on specific node
Objects serve structuring the address space.
Object types define the semantic of objects, complex
object types also the structure of connected nodes like
variables and methods.
Variables contain data, provided by the attribute called
value. Another attribute defines the data type of the
value, like String or Int16.
Variable types define the semantic of variables and
complex variable types in addition the structure of
connected nodes, in case of variables in particular sub-
Methods define the signature of methods that can be
called via the OPC UA interface.
Data types define user defined data types that can be
used in variables. This contains the encoding of the
data type, thus clients can ask during run time for the
encoding and use the user-defined types.
Reference types define the semantic of references be-
tween nodes. Each reference is assigned to a reference
type. In addition to a set of predefined reference types
like composition and inheritance, user-defined reference
types can be defined with their own semantic.
Views define an excerpt of the address space by con-
necting only nodes needed for a specific task.
Using complex object types complex structures can be
defined in the address space, reused in each application of
Device Information Model
Analyser Information Model
Information Model
Data Access Model
Base Information Model
(DataType: Number)
Definition :
ValuePrecision :
InstrumentRange :
EURange :
EngineeringUnits :
(DataType: Boolean)
(DataType: UInteger)
TrueState :
EngineeringUnits :
EnumStrings :
VendorType XYZ
Type Reference
Figure 1. Example of OPC UA information modeling
the object type. This is comparable to a class in object-
oriented programming languages. Accordingly there is sup-
port for inheritance of object types including the possibility
to add characteristics to subtypes, like methods or variables.
Based on the meta-model OPC UA already provides a base
information model containing for example the base object
type. The introduced concepts provide a variety of extension
mechanisms. This starts at defining subtypes of the base
object type or the base variable type, adding additional
methods, variables or objects to object types or sub-variables
to variable types, goes to the definition of user-defined data
types and ends by defining user-defined reference types to
bring additional semantic into the relations of nodes. Figure
1 contains an example applying information modeling using
existing standardized information models based on OPC UA.
The used notation is standardized by OPC UA and can be
seen as the usage of UML (Unified Modeling Language)
by applying UML stereotypes. The base information model
defines the base types, where the device information model
(also called DI - Device Integration) provides common
types to describe devices like flow meter or temperature
sensor, but also controller or IEDs (Intelligent Electronic
Devices). Derived from that, the analyzer device model (also
called ADI - Analyzer Device Integration) defines types of
analyzer devices having concrete characteristics w.r.t. the
configuration or supported methods (e.g. GetConfiguration
in Figure 1). Each object of that type has the same structure
and thus supports the same method. Finally, using subtyp-
ing vendor-specific extensions can be added, in Figure 1
indicated by VendorTypeXYZ. Variable types are already
defined by the data access model which is part of the OPC
UA specification. Those extended types offer the possibility
to provide standardized information about the engineering
unit (
C, bar, etc.) or the precision.
B. OPC UA Communication Services
Communication in OPC UA is initially defined by ab-
stract services (Part 4 of the specification [4]) that are
mapped to different technologies (Part 6 [5]). This allows
supporting new arising communication technologies in the
future without changing the information modeling or the
style of communication, just by defining another technology
1) Abstract Services: OPC UA provides a client-server
based connection-oriented communication. To start a client
one must establish a session. By doing this certificates and
authentication information are exchanged between client and
server. As soon as a session is established, the client can
read and write data. This includes current data, i.e. attribute
values of a node like the value of a variable but also other
attributes to access the meta-data. The history of the data can
also be accessed, for example the measured values of the last
ten seconds or the last ten years. Using browsing or querying
the structure of the address space can be accessed, including
information about the nodes and references between them. In
addition to those simple access methods OPC UA provides
a subscription mechanism. Here, a value is not only read
once but each change of the value is communicated to the
client. In this exception-based communication approach only
those data are submitted, that are needed. Using mecha-
nisms like dead-band (small changes in the dead-band are
not submitted, e.g. a temperature change from 22.0
C to
C) and a sampling rate (defines the minimal time
interval when a change should be propagated) the amount
of submitted data is further reduced. Using this mechanism
a client can for example easily show the current state of
a wind power plant to the user. Mechanisms like heartbeat
and acknowledgements guarantee a reliable communication,
even if the underlying communication technology does not.
In addition, OPC UA provides alarms and events. Events
are transient and can be accessed via subscriptions. An event
contains fields like Message, Severity and a unique identifier
and can be extended by additional fields. Meta-data about the
types of events are accessible in the server. Alarms contain
states which can be read out of the server. They can be
acknowledged and commented. An event is for example
reaching a certain level of a boiler, whereas an alarm is
reaching a critical level. Alarms and events are often shown
to the user by specific alarm and event lists. The history of
alarms and events is also accessible. The granularity of the
services is service-oriented, i.e. a service call does not access
a single value but a set of values at once. This reduces the
number of service calls and the accompanying overhead.
2) Technology Mappings: To support different require-
ments, OPC UA offers different technology mappings of the
abstract services. The mapping applies to the encoding of
the data as well as the transport protocol. To allow a simple
communication over the Internet to business applications like
ERP (Enterprise-Resource Planning), a mapping to SOAP-
based web services exist. The data can either be encoded
in XML (Extensible Markup Language) or in an OPC
UA specific binary format. The first mapping simplifies
integration into the world of XML whereas the second
option allows a fast and performing transfer of the data. To
further increase the performance, a mapping to a self-defined
TCP/IP based transport protocol is available. Using this
variant the high requirements on communication in control
systems can be fulfilled. In Figure 2 the different profiles and
their technology mappings for transport and encoding are
shown, including the used security mechanisms. The security
mechanisms use the existing WS’ specifications directly (in
case of SOAP-based transport), or an adoption of them to
the TCP/IP based transport protocol. Using an adequate
architecture with a communication stack having interfaces
based on the abstract services an application (client or
server) can be built independent of the technology mapping.
Additional technology mappings can be later added to the
stack only. Such stacks are for example provided by the OPC
C. Information Security
One particular aim during the development of the OPC
UA was the aspect of information security. Unlike the
predecessor Classic OPC and its standards, OPC UA cannot
only be used in closed and isolated automation environ-
ments, which pose new requirements in terms of security.
Automation systems can now be easily linked to company
intranets or Internet-based systems which put them also in
XML Web Services
Native Binary
Profile: UA-TCP UA-SC UA Binary
UA XML UA Binary
WS Secure Conversation UA Secure Conversation
Binary encoded Web Services
Profile: SOAP-HTTP WS-SC UA Binary
Figure 2. Technology mapping of OPC UA
the focus of malware and viruses. In order to cope with
those problems, OPC UA provides a secure communica-
tion infrastructure. Within its scope, six protection goals
are recognized: authenticity, authorization, confidentiality,
completeness, availability, and traceability. Possible threats
to OPC UA-based systems include different protection goals
and communication layers and may be prone to message
flooding, eavesdropping, and message spoofing. A generic
approach for the security architecture was chosen at de-
sign time allowing implementing the needed functionali-
ties within the security architecture. Based on the chosen
technology mapping protection goals are addressed on dif-
ferent levels whereas the security architecture differentiates
between transport, communication and application layer.
Session services are used at application level in order to
provide sessions based on secure channels from the com-
munication level. Depending on the layer to be addressed,
established non domain related security technologies are re-
used. SSL/TLS based specifications or WS Security, WS
Secure Conversations, XML encryption, and XML Signature
are used just to name a few.
D. Standardized Information Models
Standardized information models, i.e. specifications for a
certain domain, have already been developed for different
application areas. The OPC Foundation identified several
potential cooperation partners (EDDL, FDI, ISA (S88 and
S95), MIMOSA, PLCopen, and IEC TC 57 WG 13) in
order to jointly develop Companion Specifications. Cur-
rently, (May 2012) three companion specification have been
published but it can be assumed that further Companion
Specifications will follow:
OPC UA for Devices: Defined in a combined
effort of the FDT-Group, Fieldbus Foundation,
HART-Communication Foundation, OPC Foundation,
and PROFIBUS-Nutzerorganisation (PNO), a generic
model was developed representing devices. This model
is the foundation for FDI (Field Device Integration), the
current solution for field device integration, combining
the advantages of FDT (Field Device Tool) and EDD
(Electronic Device Description) [6].
OPC UA Information Model for IEC 61131-3: In a
joint effort of the OPC Foundation and PLCOpen and
information model for the programming model of IEC
61131-3 is defined allowing a standardized mapping of
function blocks, variables etc. defined in IEC 61131-3
to OPC UA [7].
OPC UA for Analyzer Devices: Developed by a
working group of the OPC Foundation the analyzer
devices model defines a concrete model of several
different types of analyzer devices like spectrometers
or chromatographs [3].
Concluding, this introduction of OPC UA emphasizes
that almost all requirements of a SOA are met. Beside
the obvious service-orientation covering all required service
characteristics, also the interoperability and loose coupling
issues are dealt with.
With its information modeling capabilities, OPC UA of-
fers a high potential for becoming the standardized commu-
nication infrastructure for various information models from
different domains. In the following, mappings of existing
information models in the power domain to OPC UA are
described: the Common Information Model (CIM; IEC
61970/ 61968) [8] and IEC 61850.
A. Common Information Model IEC 61970/61968
The mapping of CIM to OPC UA is already discussed
within the IEC who are working on a draft version of the
mapping (IEC 61970-502-8). In this context, CIMbaT has
been developed at the OFFIS - Institute for Information
Technology as a publicly available Enterprise Architect Add-
In implemented with C# in Visual Studio supporting the
generation of CIM-based address spaces [9].
In the design steps the user is offered to set OPC UA prop-
erties like IsAbstract, SupportsEvents, Historizing, DataType
etc. for each CIM-class and their attributes and associations.
That means, for example the engineer can override the
default OPC data type integer or float. Furthermore, the
decision whether a CIM-class attribute shall be mapped
to an OPC Property or DataVariable is possible in the
CIM-designer. The manipulable CIM-elements can be easily
selected within a tree-structure. For each setting there is a
specific stereotype within the CIM-UML-model which will
be added to the updated CIM-element. These UA-specific
stereotypes are unique and include a value like true or
false. They will be recognized in the mapping. If the tool
cannot find an UA-specific stereotype for a CIM-element,
then the default values from the configuration file will be
used. It is also possible to design UA Views and manage
them. The Views are used for limiting the visible Nodes
and References. The designed Views will also be saved as
UA-specific stereotypes and mapped to an OPC View-Node.
Because the changes can be saved as stereotypes in the CIM-
model, the design choices are preserved without changing
the CIM-model except regarding added stereotypes.
In coordination with the IEC and the decisions from the
engineer the CIM-elements will be mapped as depicted in
Figure 3. Thereby, the two branching arrows mean that the
designer can choose between different options. It depends
on his flavor of modeling and on the overall environment.
Merging arrows only express that different CIM-elements
may be mapped onto the same OPC UA structure.
Figure 3. Mapping of the CIM data structure onto the OPC UA address
space [9]
B. IEC 61850
Unlike the CIM the IEC 61850 does not only provide
a simple data model but in addition mechanisms for the
communication infrastructure like Functional Constraints
(FC) for filtering the data, or timestamps and quality of the
exchanged data. The IEC 61850 uses its own mechanisms to
define its model and is not based on a pure object-oriented
approach using UML (although the latest version of the IEC
61850 uses UML to document their approach [10]). Thus,
the mapping cannot be performed in the same fashion as
with the CIM. Different approaches may be chosen to map
the IEC 61850 model to an OPC UA information model. For
example, it has to be decided whether specific attributes of
the IEC 61850 like quality and timestamp should be mapped
the same way as all other attributes or handled specifically
using the built-in OPC UA mechanisms having status codes
and timestamps on each value. Furthermore, the FC defined
for attributes in IEC 61850 could be made available in OPC
UA using different modeling alternatives. In this section one
possibility for the mapping is introduced. For the introduced
mapping, the following decision were made and depicted in
Figure 4:
Logical Node (LN) Classes as defined in IEC 61850-
7-x are generally mapped onto UA object types.
LNodeTypes are generally mapped onto UA object
types subtyping the LN Class.
LN are generally mapped onto UA objects as instances
of LNodeTypes.
LN Data as the attributes of LN are mapped onto UA
CDC are also generally mapped onto UA object types.
CDC DataAttributes as the attributes of CDC are
mapped onto UA variables.
CDC DataAttribute Types are the types of the CDC at-
tributes and mainly mapped onto existing UA standard
data types like Integer, Float and String.
FC are mapped onto UA objects.
Figure 4. Mapping IEC 61850 data structure onto OPC UA address space
In order to structure the objects three standard UA
reference-types are used:
HasComponent describes a part-of relationship between
LN and its attributes as well as between CDC and its
attributes. Furthermore, it is used for the grouping by
Organizes is used to group the CDC attributes by FC.
HasTypeDefinition connects the LN attributes with the
according CDC.
Mapping Example: The example includes the Logical
Node Class (LN Class) MMXU and the Common Data Class
(CDC) MV as well as their attributes. MMXU is a LN Class
which shall be used for calculation of currents, voltages,
powers and impedances in a three-phase system. It is mainly
used for operative applications. The CDC MV represents
measured values. We focus on only three attributes of
the MMXU: TotVA (Total Apparent Power), TotVAr (Total
Reactive Power) and TotW (Total Active Power). Also for
the MV, we consider a limited number of attributes which
can be divided by the FC. FC shall indicate the services that
are allowed to be operated on a specific attribute. The at-
tributes instMag (magnitude of a the instantaneous value of a
measured value), mag (current value of instMag considering
deadband), q (quality of the measured value), t (timestamp
of the measured value) and range (range of the current
value of instMag) belong to the FC MX (Measurands) and
the attributes subEna (used to enable substitution), subMag
(used to substitute the data attribute instMag) and subID
(shows the address of the device that made the substitution)
to the FC SV (Substitution). This is similar to modeling
parameters for devices as defined in [6]. The mapping shows
that it is possible to expose the IEC 61850 model in OPC
UA. By providing the LN Class and the LNodeTypes in the
UA address space, it is possible that pure OPC UA clients
without any previous knowledge of the IEC 61850 can make
use of the type model and design for example specific HMI
elements for any MMXU.
In the light of the general discussion on features of SOA
and OPC UA in as well as the possibility to map certain data
models relevant in the context of Smart Grids to the OPC
UA, we come back to the scenarios introduced in Section
In order to fulfill the monitoring and control tasks, the
offshore wind turbines of Alpha Ventus have been equipped
with an OPC UA interface by the company Beckhoff Au-
tomation using an SDK by Unified Automation, a software
distribution and development company specialized in OPC-
based solutions and components for industrial automation
Even though the wind turbines are stand-alone (that is self-
controlled i.e. being able to run in basic feasible operation
mode without supervision), onshore monitoring from the
mainland is mandatory for safety reasons and necessary for
optimal configuration and maximum yield. Hence, OPC UA
was chosen due to its security model and mechanisms of
authentication. With the integration of the OPC UA com-
munication into Programmable Logic Controllers (PLC), the
risk of failures has been minimized since no additional
software had to be installed. In order to monitor, supervise
and control these wind turbines the SCADA system had to be
expanded by OPC UA client functionality fully supporting
Alpha Ventus control.
An increasing amount of generation from distributed
energy resources (DER) as well as from high-capacity con-
sumption, e.g. from electric vehicles, poses novel challenges
to distribution grid automation in terms of protection as well
as automated control and monitoring. Substation automation
systems in this area have to be modernized considerably.
Major disadvantages to current systems are the high costs
associated with proprietary and single-application-systems
(it often happens that a system supports only a single
function) as well as complex project set-up planning often
causing high follow-up costs for updates and maintenance.
In order to allow for application scenarios in the domain of
substation automation in future Smart Grids. a more flexible
architecture is needed that supports functional detachment
of software, hardware and communication. Thus, rendering
efficient project planning possible. With the application of
OPC UA capable systems, functions may be migrated on the
fly among different devices supporting scenarios mentioned
in Section II. The most prominent Use Cases in this scenario
Reconfiguration of protection settings according to cur-
rent DER set points taking into account the real-time
requirements associated with the response characteris-
tics of protection systems.
Increasing availability through functional redundancy
and dynamic device allocation supported by OPC UA-
based separation of hardware and software (functions)
in a standardized system.
Adjustment to regulatory updates and directives through
software patches easily deployed within an OPC UA
client server system.
Easy migration of functions on to new or updated
hardware systems allowing for a more efficient project
planning across hardware life cycles.
A consequent and consistent application of OPC UA
in substation automation enables these use cases amongst
others, due to various provided features. First, the concept
of UA profiles enables both implementing embedded servers
for small devices and complex servers for large SCADA
systems. This also enables modeling simple as well as very
complex information sets. Furthermore, UA fosters backend
integration of different data models like CIM and IEC 61850
[12] which both play a vital role in the context of substation
automation. Components, systems, and devices could be
integrated seamlessly if the representing UA server provides
information about the implemented data model. UA clients
could use that information easily to establish a connection.
Third, a comprehensive use of UA technologies in the con-
text of substation automation offers a use cases dependent
choice between XML-based data exchange for complex in-
formation, e.g. topologies being exchanged beyond firewalls
and binary encoded data for time-critical communication
like real-time control. This automation scenario is subject to
ongoing R&D projects and we will present first exemplary
results in further publications.
In this paper we introduced OPC UA as a successor to
the widely-used Classic OPC specification enabling existing,
respectively future Smart Grid scenarios. It represents the
state-of-the-art in communication in the domain of industrial
automation. Due to the advances and upgrades of OPC UA
over the Classic OPC its area of application is no longer
limited to industrial automation. With its object-oriented
generic approach it meets the requirements on data exchange
in even the most challenging areas of application, e.g. future
Smart Grids.
For the adoption of the OPC UA to the energy domain
two dis-similar information models have been discussed,
which rely on core data models for the representation
of information in Smart Grids that can be integrated by
OPC UA. Especially, the progress on the specification of
a CIM-based information model has gone far and yields
an advanced and sophisticated model. As a result, both the
OPC Foundation as well as the IEC (IEC 61970-502-8) are
working on mappings between the UA and CIM. In the same
way, the OPC Foundation aims at implementing working
groups that focus on companion specifications in the domain
of Smart Grids, e.g. a mapping between the ZigBee Smart
Energy Profile (SEP) 2.0.
In conclusion, the application of the OPC UA offers a high
potential in the domain of Smart Grids and it is foreseeable
that many companies will follow successful ”early adopters”
like ABB, Beckhoff and Siemens in implementing the OPC
[1] W. Mahnke, S.-H. Leitner, and M. Damm, OPC Unified
Architecture. Springer, 2009.
[2] J. Lange, F. Iwanitz, and T. J. Burke, OPC: From Data Access
to Unified Architecture. Huethig, 2010.
[3] OPC Foundation, “OPC Unified Architecture Companion
Specification for Analyser Devices - Release 1.00, 2009.
[4] ——, “OPC Unified Architecture Specification Part 4: Ser-
vices - Release 1.01, 2009.
[5] ——, “OPC Unified Architecture Specification Part 6: Map-
pings - Release 1.00, 2009.
[6] ——, “OPC Unified Architecture for Devices (DI) Compan-
ion Specification - Release 1.00, 2009.
[7] OPC Foundation and PLCopen, “OPC UA Information Model
for IEC 61131-3 - Release 1.00, 2010.
[8] M. Uslar, M. Specht, S. Rohjans, J. Trefke, and J. M.
alez, The Common Information Model CIM: IEC
61968/61970 and 62325 - A practical introduction to the CIM.
Springer, 2012.
[9] S. Rohjans, K. Piech, M. Uslar, and J.-F. Cabadi, “CIMbaT
- Automated Generation of CIM-based OPC UA-Address
Spaces, in IEEE SmartGridComm 2011, Brussels, 2011.
[10] A. Apostolov, “IEC 61850 Substation Configuration Lan-
guage and Its Impact on the Engineering of Distribution Sub-
station Systems, in Congreso Internacional de Distribuci
ectrica (CIDEL2010), 2010, pp. 1–6.
[11] S. Lehnhoff, W. Mahnke, S. Rohjans, and M. Uslar, “IEC
61850 based OPC UA Communication - The Future of
Smart Grid Automation,” in 17th Power Systems Computation
Conference (PSCC’11), Stockholm, 2011.
[12] S. Rohjans, K. Piech, and W. Mahnke, “Standardized Smart
Grid Semantics using OPC UA for Communication, IBIS
- Interoperability in Business Information Systems, vol. 6,
no. 10, 2011.
... From a technological perspective, this study focuses on the adaptation of concepts and technologies developed in the field of augmented reality technology. In this proposed system, students will learn the following: (1) to plan an augmented reality technology project, (2) to implement programs, (3) to monitor processes, (4) to grasp automation concepts, and (5) to understand how augmented reality technology processes work. In addition to augmented reality (AR) technology, the virtual-real integrated network system platform in this study integrated communication technologies of plants to use IIoT in Industrial 4.0 intelligent manufacturing. ...
... (2) The IIoT gateway was provided to the control system for OPC UA protocol conversion and cloud data concatenation and integration, including for communication devices, sensors, and remote servers. (3) In this study, the vertically integrated infrastructure of Industry 4.0 was realized, and equipment information in the perception layer and network layer were exchanged through the IIoT gateway. ...
Full-text available
This study presented work considering the development and initial assessment of an augmented reality approach to provide a user interface for operators that could be a part of an equipment maintenance and diagnostics system. Its purpose was to provide an equipment system for graduate students of engineering and technology to experiment with the design of augmented reality technology. The proposed system took place three hours per week over a period of four weeks of corrective actions that were triggered in the Department of Industrial Education and Technology at the National Changhua University of Education, Taiwan. The students adopted augmented reality technology to achieve big data acquisition and analysis for pre-diagnostic and maintenance applications. Preliminary assessment of the proposed system was encouraging and showed that it achieved success in helping students understand concepts and using augmented reality technology for equipment maintenance and diagnostics. The study provided important initial insights into its impact on student learning.
... One of the big challenges facing the discipline is how to make each of them "speak the same language" and seamlessly communicate (back-and-forth) with one other. The emergence of the Industrial Internet of Things (IIoT) [441] and open communication standards/platforms and advanced advanced M2M communication protocols, such as the Open Platform Communication Unified Architecture (OPC UA) [219,442,443] and MQ Telemetry Transport (MQTT), has advanced data collection and synchronization efforts. A lot of research still needs to go into developing new and improved communication standards and framework. ...
Full-text available
In a dynamic and rapidly changing world, customers’ often conflicting demands have continued to evolve, outstripping the ability of the traditional factory to address modern-day production challenges. To fix these challenges, several manufacturing paradigms have been proposed. Some of these have monikers such as the smart factory, intelligent factory, digital factory, and cloud-based factory. Due to a lack of consensus on general nomenclature, the term Factory of the Future (or Future Factory) has been used in this paper as a collective euphemism for these paradigms. The Factory of the Future constitutes a creative convergence of multiple technologies, techniques, and capabilities that represent a significant change in current production capabilities, models, and practices. Using the semi-narrative research methodology in concert with the snowballing approach, the authors reviewed the open literature to understand the organizing principles behind the most common smart manufacturing paradigms with a view to developing a creative reference that articulates their shared characteristics and features under a collective lingua franca, viz., Factory of the Future. Serving as a review article and a reference monograph, the paper details the meanings, characteristics, technological framework, and applications of the modern factory and its various connotations. Amongst other objectives, it characterizes the next-generation factory and provides an overview of reference architectures/models that guide their structured development and deployment. Three advanced communication technologies capable of advancing the goals of the Factory of the Future and rapidly scaling advancements in the field are discussed. It was established that next-generation factories would be data rich environments. The realization of their ultimate value would depend on the ability of stakeholders to develop the appropriate infrastructure to extract, store, and process data to support decision making and process optimization.
... In [40], various services and their interface are designed using a RESTful architecture to facilitate microgrid applications, but this lacks a service registry and allocation mechanisms. In [41], Open Platform Communications Unified Architecture (OPC UA, a service-oriented communication framework) is analyzed in smart grid applications deriving the data model mappings to CIM and IEC 61850. The conventional OPC UA is based on client-server communication, which can hamper scalability if the server becomes a bottleneck [42]. ...
Full-text available
The current advancements of energy, information, communication, and automation technologies and their integration have provided ways for the energy industry to transform into cleaner energy systems. This transition has contributed to the concept called energy internet. The recent energy technologies provide clean energy generation, storage and demand response through distributed energy resources. Information, communication, and automation technologies aim to provide supporting software tools and enabling mechanisms to automate the operation and control of those resources in a coordinated way. Thus, researchers and the software industry are developing software frameworks and platforms to support energy system automation. Commonly, most of the frameworks follow the design principles of either multi-agent systems (MAS) or service-oriented architecture (SOA). However, there are many frameworks and no straightforward criteria to select which one to implement in energy systems’ automation applications to fulfil the energy internet vision. This study provides a conceptual investigation of MAS- and SOA-based software solutions by designing a use case for microgrid application automation considering its expansion for enabling energy internet. Two software frameworks, RIAPS and Arrowhead, have been selected as the candidates of MAS and SOA from the literature study. This study shows that neither MAS or SOA approach alone might not meet the requirements of microgrid automation and energy internet. Consequently, a combined approach of MAS and SOA is proposed.
... Considering the requirements outlined in this section the OPC-UA protocol described in Lehnhoff et al. (2012) also offers the required capabilities. On the one hand, this technology offers to create sessions between a client and a server using HTTP to exchange variables as required for the setpoint communication; on the other hand, the subscription mechanism it offers is suitable to allow for a publish-subscribe scheme to be implemented. ...
Full-text available
Smart Grids are electrical grids that require a decentralised way of controlling electric power conditioning and thereby control the production and distribution of energy. Yet, the integration of Distributed Renewable Energy Sources (DRESs) in the Smart Grid introduces new challenges with regards to electrical grid balancing and storing of electrical energy, as well as additional monetary costs. Furthermore, the future smart grid also has to take over the provision of Ancillary Services (ASs). In this paper, a distributed ICT infrastructure to solve such challenges, specifically related to ASs in future Smart Grids, is described. The proposed infrastructure is developed on the basis of the Smart Grid Architecture Model (SGAM) framework, which is defined by the European Commission in Smart Grid Mandate M/490. A testbed that provides a flexible, secure, and low-cost version of this architecture, illustrating the separation of systems and responsibilities, and supporting both emulated DRESs and real hardware has been developed. The resulting system supports the integration of a variety of DRESs with a secure two-way communication channel between the monitoring and controlling components. It assists in the analysis of various inter-operabilities and in the verification of eventual system designs. To validate the system design, the mapping of the proposed architecture to the testbed is presented. Further work will help improve the architecture in two directions; first, by investigating specific-purpose use cases, instantiated using this more generic framework; and second, by investigating the effects a realistic number and variety of connected devices within different grid configurations has on the testbed infrastructure.
... The PLC's use offers several advantages, including flexibility, reliability, low power consumption and ease of expansion. In the last decade, the major PLC manufacturers have made significant improvements, notably through the introduction of OPC (Open Platform Communications) technology [11,12,13,14]. The recent development of this protocol has promoted interoperability between several environments. ...
Full-text available
Many research laboratories, which develop advanced algorithms for controlling Renewable Energy Systems (RES), lack specialized equipment to carry out research activities and perform experiments. Real-time simulation platforms are suitable for designing specific applications such as fast or real-time computation models. In addition, these platforms provide fast, accurate and reliable studies for RES control implementation. However, Real-time platforms are too expensive and not affordable for most laboratories. In this context, a cost-effective platform is designed to assist researchers in their activities. The hardware solution consists of using a Programmable Logic Control (PLC) to acquire data from the various sensors and control the system through actuators and PID controllers. From a software standpoint, a communication framework between MATLAB and the PLC is developed using the OPC-UA (Open Platform Communications Unified Architecture) technology. In this paper, the operation and efficiency of the platform have been tested using the Software in the Loop (SIL) technique. Hence, the operating model is designed using MATLAB/Simulink to simulate and analyze the appropriate control technique suitable for PLC implementation, whereas the control is executed through Siemens S7-1200 PLC using TIA PORTAL. A visualization interface is set up using WinCC-RT. Furthermore, this paper describes the design of the platform and discusses its utilization, providing examples of its usage through a case study. Indeed, a complex algorithm developed in MATLAB/Simulink can be automatically executed by any PLC using the designed framework.
ISO 11783 is a communication protocol for tractors and implements. It specifies a network of control functions connected with a CAN bus. The task controller is a control function that is used to control implements based on planned tasks. Implements expose their structure to the task controller with Device Descriptor Object Pool XML files. The guidelines for modelling implements leave room for interpretation, which can lead to compatibility issues. The agricultural industry has decided that the physical layer of the future high-speed ISOBUS will use Ethernet, but the higher OSI layers are undecided. One Ethernet-compatible middleware to be considered is OPC UA, a platform-independent communication standard for systems and devices. It uses object-oriented information modelling techniques and allows users to define new information models based on the OPC UA base information model and its standardized extensions. In this article, an OPC UA information model was designed for data exchange between the task controller and implements, and its suitability for use in the high-speed Next-Generation ISO 11,783 Task Controller was evaluated. Modelling rules for the information model were designed with a focus on modelling all types of implements that apply a product or products. OPC UA Implement Server and OPC UA Task Controller applications were developed to test the information model. The evaluation of these OPC UA applications showed that the OPC UA model (OPC UA for the Next Generation ISO 11,783 Task Controller information model) presented is suitable for communication between the task controller and implements.
Full-text available
Cognitive sensor systems (CSS) determine the future of inspection and monitoring systems for the nondestructive evaluation (NDE) of material states and their properties and key enabler of NDE 4.0 activities. CSS generate a complete NDE 4.0 data and information ecosystem, i. e. they are part of the materials data space and they are integrated in the concepts of Industry 4.0 (I4.0). Thus, they are elements of the Industrial Internet of Things (IIoT) and of the required interfaces. Applied Artificial Intelligence (AI) is a key element for the development of cognitive NDE 4.0 sensor systems. On the one side, AI can be embedded in the sensor’s microelectronics (e. g. neuromorphic hardware architectures) and on the other side, applied AI is essential for software modules in order to produce end-user-information by fusing multi-mode sensor data and measurements. Besides of applied AI, trusted AI also plays an important role in CSS, as it is able to provide reliable and trustworthy data evaluation decisions for the end user. For this recently rapidly growing demand of performant and reliable CSS, specific requirements have to be fulfilled for validation and qualification of their correct function. The concept for quality assurance of NDE 4.0 sensor and inspection systems has to cover all of the functional sub-systems, i. e. data acquisition, data processing, data evaluation and data transfer etc. Approaches to these objectives are presented in this paper after giving an overview on the most important elements of CSS for NDE 4.0 applications. Reliable and safe microelectronics is a further issue in the qualification process for CSS.
The five-volume set IFIP AICT 630, 631, 632, 633, and 634 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2021, held in Nantes, France, in September 2021.* The 378 papers presented were carefully reviewed and selected from 529 submissions. They discuss artificial intelligence techniques, decision aid and new and renewed paradigms for sustainable and resilient production systems at four-wall factory and value chain levels. The papers are organized in the following topical sections: Part I: artificial intelligence based optimization techniques for demand-driven manufacturing; hybrid approaches for production planning and scheduling; intelligent systems for manufacturing planning and control in the industry 4.0; learning and robust decision support systems for agile manufacturing environments; low-code and model-driven engineering for production system; meta-heuristics and optimization techniques for energy-oriented manufacturing systems; metaheuristics for production systems; modern analytics and new AI-based smart techniques for replenishment and production planning under uncertainty; system identification for manufacturing control applications; and the future of lean thinking and practice Part II: digital transformation of SME manufacturers: the crucial role of standard; digital transformations towards supply chain resiliency; engineering of smart-product-service-systems of the future; lean and Six Sigma in services healthcare; new trends and challenges in reconfigurable, flexible or agile production system; production management in food supply chains; and sustainability in production planning and lot-sizing Part III: autonomous robots in delivery logistics; digital transformation approaches in production management; finance-driven supply chain; gastronomic service system design; modern scheduling and applications in industry 4.0; recent advances in sustainable manufacturing; regular session: green production and circularity concepts; regular session: improvement models and methods for green and innovative systems; regular session: supply chain and routing management; regular session: robotics and human aspects; regular session: classification and data management methods; smart supply chain and production in society 5.0 era; and supply chain risk management under coronavirus Part IV: AI for resilience in global supply chain networks in the context of pandemic disruptions; blockchain in the operations and supply chain management; data-based services as key enablers for smart products, manufacturing and assembly; data-driven methods for supply chain optimization; digital twins based on systems engineering and semantic modeling; digital twins in companies first developments and future challenges; human-centered artificial intelligence in smart manufacturing for the operator 4.0; operations management in engineer-to-order manufacturing; product and asset life cycle management for smart and sustainable manufacturing systems; robotics technologies for control, smart manufacturing and logistics; serious games analytics: improving games and learning support; smart and sustainable production and supply chains; smart methods and techniques for sustainable supply chain management; the new digital lean manufacturing paradigm; and the role of emerging technologies in disaster relief operations: lessons from COVID-19 Part V: data-driven platforms and applications in production and logistics: digital twins and AI for sustainability; regular session: new approaches for routing problem solving; regular session: improvement of design and operation of manufacturing systems; regular session: crossdock and transportation issues; regular session: maintenance improvement and lifecycle management; regular session: additive manufacturing and mass customization; regular session: frameworks and conceptual modelling for systems and services efficiency; regular session: optimization of production and transportation systems; regular session: optimization of supply chain agility and reconfigurability; regular session: advanced modelling approaches; regular session: simulation and optimization of systems performances; regular session: AI-based approaches for quality and performance improvement of production systems; and regular session: risk and performance management of supply chains *The conference was held online.
Flexible and reconfigurable manufacturing systems aim to enable more versatile, connected, and intelligent operations not only from a system-level perspective, but also from a field-level perspective. This paper focuses on field-level applications for peripheral intelligence and proposes a concept and architecture for an Active Device Driver (ADD) that can be actively adjusted to unforeseen situations versus repeating fixed task procedures. This new device driver is designed to permit easy and rapid transformability to systems by enabling device modulization and abstraction, control and configuration under service-oriented architecture, actively supporting control reliability, and producing well-organized manufacturing data. These features can be achieved by implementing the control I/O encapsulating module, device information model, OPC-UA server interface, and peripheral control module. Two case studies with robot grippers are conducted to validate the working principle of ADDs.
Many Industrie 4.0 use-cases require end-to-end communication between layers of the automation pyramid. Converting the existing layered communication into a peer-to-peer architecture does however require the functional bridging between protocols. In this article, we discuss Industrie 4.0 communication scenarios, constraints of the automation domain, as well as device communication requirements, and present our end-to-end communication approach based on our information bus concept, the virtual automation bus (VAB).
Full-text available
Within this contribution, we outline the use of the new automation standards family OPC Unified Architec-ture (IEC 62541) in scope with the IEC 61850 field automa-tion standard. The IEC 61850 provides both an abstract data model and an abstract communication interface. Different technology mappings to implement the model exist. With the upcoming OPC UA, a new communication model to imple-ment abstract interfaces has been introduced. We outline its use in this contribution and also give examples on how it can be used alongside the IEC 61970 Common Informa-tion Model to properly integrate ICT and field automation at communication standards level.
Full-text available
Realizations of so called smart grids imply numerous challenges for stakeholders within the energy domain. ICT plays more and more a key role as it provides methodologies and approaches fostering smart grid applications. One of the challenges addresses integrated communications among energy management systems, distribution management systems, power generation systems and SCADA systems. In this case, a key issue to be considered is interoperability in terms of both syntax and semantics. For both, using standardized components like interfaces, protocols and data models, is essential to cope with the increasing number of actors and systems. Standards covering these components are discussed in various roadmaps and studies making recommendations. The Common Information Model is one of the recommended core standards for the smart grid and provides amongst others, a comprehensive data model for the energy domain. Another recommended standard is the OPC Unified Architecture being an abstract standard for server-client-communications which could be used in domain-specific contexts. Thus, combining the CIM data model and the UA communication architecture leads to a highly interoperable infrastructure meeting syntactic and semantic requirements. In this contribution, a two-step-approach is introduced realizing such an architecture.
The OPC Foundation defines standards for online data exchange between automation systems. They address access to current data (OPC DA), alarms and events (OPC A&E) and historical data (OPC HDA). Those standards are successfully applied in industrial automation. The new OPC Unified Architecture (OPC UA) unifies the existing standards and brings them to state-of-the-art technology using service-oriented architecture (SOA). Main advantages of the new standard are: •Platform-independent technology allows the deployment of OPC UA beyond current OPC applications only running on Windows-based PC systems. OPC UA can also run on embedded systems as well as Linux / UNIX based enterprise systems. •The provided information can be generically modeled and therefore arbitrary information models can be provided using OPC UA. This book gives an easy to understand introduction into OPC UA and explains the concepts of the standard and other relevant topics that are not directly addressed by the standard. © 2009 Springer-Verlag Berlin Heidelberg. All rights are reserved.
Unified Architecture Specification Part 6: Map-pings -Release 1.00
  • ——
  • Opc
——, " OPC Unified Architecture Specification Part 6: Map-pings -Release 1.00, " 2009.
OPC Unified Architecture Companion Specification for Analyser Devices -Release 1.00
  • Opc
  • Foundation
OPC Foundation, " OPC Unified Architecture Companion Specification for Analyser Devices -Release 1.00, " 2009.
IEC 61850 Substation Configuration Language and Its Impact on the Engineering of Distribution Substation Systems
  • A Apostolov
A. Apostolov, "IEC 61850 Substation Configuration Language and Its Impact on the Engineering of Distribution Substation Systems," in Congreso Internacional de Distribución Eléctrica (CIDEL2010), 2010, pp. 1-6.
OPC UA Information Model for IEC 61131-3-Release 1.00
  • Opc Foundation
  • Plcopen
OPC Foundation and PLCopen, "OPC UA Information Model for IEC 61131-3-Release 1.00," 2010.