Implementing Energy Flexibility Measures in an Industrial Smart
Grid: A Systematic Approach
Alejandro Tristán
1
, Alexander Emde
2
, Martin Reisinger
1
, Martin Stauch
1
and Alexander Sauer
2
1
Fraunhofer Institute for Manufacturing Engineering and Automation IPA, 70569 Nobelstr. 12, Germany
2
Institute for Energy Efficiency in Production (EEP), University of Stuttgart, 70569 Nobelstr. 12, Germany
Keywords: Demand Side Response, Industrial Energy Flexibility, Demand Side Management.
Abstract: Industrial energy flexibility (DSEF) is the capacity of industrial systems to adapt (increase, reduce or shift)
their energy consumption over a specific period based on changes in the energy context. These capabilities
acquire an exploitable form as Energy Flexibility Measures (EFMs), meaning conscious and quantifiable
actions that carry out a defined change in the operative state in an industrial system. Modern factories usually
present a wide variety of available EFMs, that to be implemented and managed effectively demand the
transformation of industrial energy grids into DSEF capable smart micro-grids. For this purpose, this paper
presents a methodological approach that employs a variation of the Use Case Methodology and the Smart
Grid Architecture Model (SGAM) to design comprehensive energy flexible Industrial Smart Grid (ISG). The
developed ISG-design outlines the necessary physical and virtual elements to incorporate multiple EFMs into
Brown- and Greenfield industrial sites. The paper concludes with a summary of the lessons learned during
the application of the developed approach in a brownfield automobile manufacturing plant.
1 INTRODUCTION
Demand-side energy flexibility (DSEF) has a
considerable capability for providing the power grid
with the added necessary flexibility to help guarantee
secure and resilient operation. (Alemany et al. 2018).
DSEF from industrial processes, or industrial energy
flexibility (IEF), is strongly relevant due to the high
share that the industrial sector represents in the
overall electrical consumption. Moreover, energy-
intensive Factories can also cause a high level of
stress and instability on the power grid, which could
also be mitigated via IEF (Dulău et al. 2016). Various
analyses have already quantified the energy
flexibility potentials of the German manufacturing
sector with promising results (Eisenhauer et al. 2017)
(Ausfelder et al. 2018).
Currently, one of the main challenges to exploit
IEF is the implementation of the previously identified
energy flexibility measures (EFMs) in the industrial
systems across a production site, i.e. a factory. EFMs
are usually highly complex as they influence the
material, information and energy flows in the factory.
This paper presents a systematic approach to
overcome this challenge via the development of a
multidimensional design (physical, functional,
technological and economic) of energy flexible ISG.
The approach, as an abstract concept, was proposed
in previous work (Tristan et al. 2019). In this
publication, the concept has been, revised,
concretized and complemented with the experiences
from its application in brownfield sites. The article
concludes with a summary of the insights gained
through the application of the developed approach
and an outlook of its prospective applications.
2 KEY CONCEPTS OF IEF AND
INDUSTRIAL SMART GRIDS
(ISG)
In this section, the key concepts of IEF and ISGs
necessary for the development of the proposed
approach are presented, starting by defining the
concept of energy flexibility measures in industrial
systems.
Tristán, A., Emde, A., Reisinger, M., Stauch, M. and Sauer, A.
Implementing Energy Flexibility Measures in an Industrial Smart Grid: A Systematic Approach.
DOI: 10.5220/0011105100003355
In Proceedings of the 1st International Joint Conference on Energy and Environmental Engineering (CoEEE 2021), pages 31-38
ISBN: 978-989-758-599-9
Copyright
c
 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
31

2.1 Energy Flexibility Measures in
Industrial Systems
Energy flexibility measures (EFMs) are conscious,
and quantifiable actions to carry out a defined change
of an operative state in industrial systems (Reinhart et
al.). The identification of prospective EFMs is a
three-part process that involves: (1) identifying those
systems suitable for energy flexible operation, (2)
recognizing the nature of the flexibility they could
offer and, (3) characterizing the EFM, which consists
in the quantification of the characterization
parameters of an EFM. An EFM is fully characterized
when its functional, performance, temporal and
economic dimensions are established. For this
purpose, the characterization framework presented in
(Tristán et al. 2020). The most relevant
characterization parameters in this framework,
necessary for the implementation are (VDI 5207):
• Flexibility Type: the direction on which the
operative state will be changed by the
activation of the EFM. (Load increase,
decrease, temporal shift)
• Flexible Power, ∆P
flex
: the maximum
difference of rate of energy demand between
the reference operative state and the EFM-
induced operative state. The unit for this
parameter is usually kW
flex
.
• Active Duration, ∆t
active
: comprises the
minimum and maximum period on which
the EFM is active, meaning the duration on
which the industrial system operates under
the EFM-induced operative state(s).
• Activation Frequency, N
activation,T
: the
activation frequency parameter quantifies
the maximum number of times an EFM can
be executed over a specific period, T,
usually a calendar year.
• Flexible Energy, E
flex,T
: the average amount
of energy that could be flexibilized as a
result of activating an EFM over a specific
period, T, typically a year.
• EFM specific cost, c
flex,T
: cost summary
indicator of the EFM, it represents the cost
of the EFM by a unit of flexible energy over
a specific period (T).
Once the identification of prospective EFMs has
concluded, they need to be evaluated regarding their
viability. This evaluation consists of balancing the
costs, benefits and risks of implementing each
prospective EFMs. The evaluation analysis has then
as output, a catalogue of viable and ready-to-be-
implemented EFMs.
2.2 Micro Grids and Industrial Smart
Grids
A smart grid is defined as an electricity network that
uses information exchange, control technologies,
distributed computing and associated sensors to
integrate the behaviour and actions of the network
users and other stakeholders (DIN Spec 42913-1;
Wilker et al. 2017). Meanwhile, microgrids are
electricity distribution networks containing loads and
distributed energy resources, (such as distributed
generators, storage devices, or controllable loads)
with the ability to be operated in a controlled,
coordinated manner either while connected to the
main power network or in isolation. The electrical
grid in a production site is, under this definition, a
microgrid that is delimited by the physical boundaries
of the site.
Therefore, in the research context, the concept
Industrial Smart Grid (ISG) was introduced to
conceptually describe smart microgrids aimed
towards the smart integration of the industrial systems
in a production site. (Sauer and Weckmann 2017).
The development of an ISG, nevertheless,
differentiates itself from the classic understanding of
a microgrid, due to the multidisciplinary nature of its
requirements. The conception, planning and
implementation of an ISG entail the balance of the
expectations and necessities of a broad range of
stakeholders (DIN Spec 42913-1; Sauer and
Weckmann 2017). A general overview of the relevant
stakeholders for the development of an ISG is
presented in Figure 1.
Figure 1. Relevant stakeholders within the development of
an ISG (VDI 5207).
As can be seen in Figure 1, the ISG stakeholders
can be divided between external, which are actors that
are not directly affiliated to the site’s managing
organization and internal, i.e. actors under the
purview of the organization managing the site.
Internal stakeholders might or not be present in the
site’s physical location. Depending on the size and
CoEEE 2021 - International Joint Conference on Energy and Environmental Engineering
32

complexity of the industrial processes, some
additional actors might also be relevant for the ISG.
2.3 The Need for an ISG in Production
Sites
From a general standpoint, the need to develop ISGs
is comparable to that for the Smart Grid as a whole.
The ISG allows the energy consumption of the
different industrial systems in a production site to be
coordinated dynamically based on the changing
conditions within the site and in the electrical grid.
The ISG, therefore, transforms previously energy
consuming-only loads into reactive, intelligent, loads.
Furthermore, as mentioned, there is a
decarbonisation effort in the electrical grid that hinges
considerably on the electrification of the demand
sectors. The effort is particularly strong on industrial
systems that were previously supplied on energy
vectors with high carbon footprints. The shift towards
electricity, adds additional stress on the power grid,
and increments the need for grid resilience but also
presents an opportunity (Smart Grid Coordination
Group 2012).
The implementation of Smart Grids in general and
of ISGs in particular, enables better autonomous
control actions, operator assistance, integration of
renewable sources, better market efficiency through
innovative solutions for different types of products,
better service quality, situational awareness,
efficiency enhancement, and overall resilience
(Dulău et al. 2016). And, in the particular case of IEF
allows companies to optimize their energy
consumption while collaborating with the energy
transition.
2.4 The Required Capabilities of an
Energy Flexible ISG
The functions of an ISG will not be limited to the
support of the energy flexible operation of industrial
systems. Nonetheless to support IEF the ISG must a-
) swiftly detect a change in behaviours in the internal
and external energy grids, e.g. considerable price
variations), b-) calculate the magnitude and expected
duration of these variations and, c-) deliver an optimal
response. These responses can be divided between
proactive and reactive. A proactive flexibility
response asks production sites to offer ahead of their
flexibility potential so that other external stakeholders
can retrieve it at short notice. In this case,
communication is bidirectional, i.e. the company and
1
TSO: Transmission System Operator
the respective stakeholders exchange information, in
real-time, regarding the specific characteristics of the
flexibility response. The ISG should then maintain a
considerable level of readiness to energy flexible
operation. In reactive flexibility, production sites,
adapt their consumption as a response to fluctuations
in the peripheral energy context. The communication
for reactive flexibility is, in principle, unidirectional,
as the site does not provide any information to
external stakeholders (VDI 5207). In this case, the
ISG should be capable of projecting the optimal
magnitude and duration of the response. The optimal
energy flexible ISG should be capable to provide both
proactive and reactive flexibility responses.
Moreover, the nature of flexibility responses
should prioritize the organization’s motivation to
deliver IEF and balance them with potential risks that
the retrieval of EFMs might entail. The overarching
motivation for IEF from a macro-perspective should
be to serve the demand-side balance of the volatility
of renewable energy supply sources. While at a
micro-scale, IEF should create a direct or indirect
benefit, usually economic, for the industrial site as an
energy consumer. Potential risks from retrieving
EFMs can be summarized as the deterioration of the
optimal operation of the site’s material and energy
flows and/or, potential impacts on the industrial
systems lifetime (Simon et al. 2018).
The heterogeneous nature of these requirements
demands a more specific analysis than the one
performed during the architecture design of the entire
smart grid nonetheless, due to their similar end-goal
the smart grid design tools can be adapted for the ISG
development.
2.5 Smart Grid Architecture Model
and the Use Case Methodology
The Smart Grid Architecture Model (SGAM) and the
Use Case Methodology have been selected by the
Smart Grid coordination group behind the EU
Mandate M/490 as the basis to standardize the
development of the European Smart Grid. Currently,
both tools, in combination, are used by TSOs
1
and
DSOs
2
to develop their respective electrical smart
grids (DIN Spec 42913-1).
The SGAM is based on interoperability and
allows the creation and formalization of solutions that
can then be implemented as Smart Grid
Functionalities. It is subdivided into five so-called
interoperability layers. The component layer is the
foundational layer. It serves to map and describe
2
DSO: Distribution System Operator
Implementing Energy Flexibility Measures in an Industrial Smart Grid: A Systematic Approach
33

every physical component from information,
communication and control equipment to the power
network itself. The function layer describes functions
and services, and, hence the relationships, between
the components in the component layer. The
information layer describes information objects
within these described components, which are
transferred with specified tools inside protocols
described in the communication layer (Wilker et al.
2017).
The SGAM can be understood as a 3-D model
where the layers stack vertically and cover two
dimensions the Domains (Generation, Transmission,
Distribution, Distributed Energy Resources and
Customer Premises) and Zones (Process, Field,
Station, Operation, Enterprise and Market).
The Use Case Methodology is a software-based
method that allows describing, statically and
dynamically, a to-be-developed system and its
functionalities. It is usually then used, to establish
specific applications that are desired in the smart grid.
The different use cases are then aggregated to develop
the different layers of the SGAM (Gottschalk et al.
2017).
3 DEVELOPING THE ENERGY
FLEXIBLE ISG THROUGH
PREVIOUSLY IDENTIFIED
EFMS
The proposed systematic approach employs the Use
Case Methodology to translate EFMs into fully
described use cases of the energy flexible ISG. The
individual interoperability layers are built then, by
aggregating the different elements describing each
use case and merge them into an Industrial Smart Grid
Model (ISGM). The resulting ISGM can thereafter be
used to map the gaps between the current and desired
topology in the production site and facilitate the
implementation of the energy flexible ISG. An
overview of the individual steps of the developed
approach is presented in Figure 2. The individual
steps in Figure 3 are described in the following
subsections.
Figure 2. ISGM development steps.
3.1 Input Definition
The first step is to define the EFMs, which, are
intended to be implemented on the production site.
The EFMs should be fully characterized, meaning
that their different features should be enumerated to
the point that a use case could be built for each EFM.
As a part of the characterization a brief
comprehensive understanding of the industrial
system on which the EFM acts should also be
available. In addition, the current relationships
between the system and the relevant stakeholders
should be known.
3.2 Scope and Objectives
Step 2 is to define the implementation objectives of
the intended energy flexible ISG and its scope. These
implementation objectives can be internal, involving
only stakeholders and activities under the company’s
purview, or external, involving stakeholders and
activities in the site’s periphery. Internal objectives
include, for example, the postponement of
infrastructure expansions, the improvement of
voltage quality, increased system resilience, the
maximization of the self-consumption of local
renewable sources and peak-shaving. These
objectives are usually limited to reactive flexibility
responses. Examples of external objectives may be,
maximising the usage of their renewable energy
portfolio, offering energy flexibility in the energy
markets and/or optimising energy consumption as a
function of energy costs (VDI 5207). External
objectives usually combine proactive and reactive
flexibility responses.
The second part of Step 2 is to delimit the scope
of the intended ISG. The delimitation consists of
identifying, out of the current topology of the
industrial site, which components will need to be
retrofitted to implement the ISG on site. The scope
should be wide enough to encompass the relevant
components to implement the EFMs and achieve the
CoEEE 2021 - International Joint Conference on Energy and Environmental Engineering
34

intended objectives but should be specific enough to
limit potential risks in the implementation of the ISG.
3.3 Define Zones and Domains
Similar to the SGAM, the definition of zones and
domains for the ISGM forms the frame of reference
within the ISG. As is the case for Industry 4.0
concepts, the ISGM merges the physical and cyber
systems of the production sites. (VDI 2015).
Therefore, the domains of the ISGM represent the
different physical elements that define an industrial
site. These units can be visualized hierarchically e.g.
Site/Building, Energy Infrastructure (Technical
Building Services), Hall, Manufacturing/Auxiliary
Systems and Machine/Tool (Weeber et al. 2017;
Posselt 2016). The specific domains that will be
present in the ISGM depend on the elements of the
analysed manufacturing site. The zones are, in turn,
based on the classical automation pyramid, which
consists of Field, Control, Supervision, Operation and
Organization.(Sauer and Weckmann 2017) Due to
their hierarchical nature, both, the zones and domains
for ISGM can be represented as pyramids, as shown
in Figure 3. Depending on the complexity of the
industrial site and the selected scope, the ISG
description may require adding or remove zones and
domains.
Figure 3. Visualization of ISGM zones and domains.
3.4 Building up Use Cases from EFMs
The Use Case methodology is an ideal tool for
converting fully characterized EFMs into the
functionalities that will constitute the building blocks
on the energy flexible ISG. This methodology is
described in the IEC 62559-2 standard. The
procedure is divided into the following basic stages
(Gottschalk et al. 2017):1-) Use Case description, 2-)
Use Case diagrams, 3-) Technical Details 4-) Step-
by-step analysis, 5-) Information exchange, 6-)
Requirements.
The Use Case description is already completed
during the EFM identification and characterization
analysis and constitutes an input, as explained in
section 3.1. The Use Case diagrams, are based on Use
Case, Activity and Sequence diagrams from the
Unified Modelling Language (UML) and enable a
dynamic and static representation of the sequential
activities that constitute the retrieval of each EFM.
The Technical Details stage should describe the
actors and roles. Actors are physical or virtual entities
that communicate or interact during the activation of
an EFM. A role describes the actor's responsibilities
and hence, their decision-making authority. The Step-
by-step analysis describes, in detail, the activation
procedure of an EFM. Based on the desired result, this
procedure can follow different paths or modes of
operation. The modes of operation are divided into
individual actions that constitute the functionalities
necessary to achieve the intended goal of the EFM.
The information exchange creates a description of the
necessary information that has to be traded between
actors to achieve each mode of operation. The
Requirements stage describes the necessary internal
and external contexts, on which each mode of
operation takes place. It consists of a description of
the triggering event that demands the activation of the
described EFM.
3.5 ISG M Component Layer
The content of the Component Layer is derived from
the Use Case descriptions of the respective actors.
Each actor îs represented either directly or indirectly
by a component in the Component Layer. Since the
actors are not necessarily physical units, several
actors can be replaced by one component. The various
components must be assigned to their specific
domains and zones. Once all the Use Cases have been
aggregated into the Component Layer, the
components here constitute the necessary common
infrastructure necessary to achieve the different
EFMs from the energy, information and control flows
perspectives. Figure 4 shows a generic Component
Layer with the previously defined zones, domains and
potential components located across them.
Implementing Energy Flexibility Measures in an Industrial Smart Grid: A Systematic Approach
35

Figure 4. Conceptual Component Layer.
3.6 ISGM Function Layer
The Function Layer shall represent the functionalities
and relationships between components across the
domains and zones. Functionalities are derived from
the use cases by transforming each, mode of operation
from the characterized EFM (As described in Section
3.4) into the specific set of commands to be
performed by the relevant components.
Functionalities within the Function Layer are usually
decided and triggered at the supervision, operation
and/or enterprise zones. On the other hand, depending
on the scope of the EFM, these functionalities
represent, their scope extends across different
domains.
3.7 ISGM Business Layer
The Business Layer integrates the intended
objectives, as defined in section 3.2, with the
Requirements, from the Use Case methodology of
section 3.4, and serves as the main input to build a
business case for the energy flexible ISG. The
Business Layer is intended to harmonize intentions,
in the form of the intended objectives of the ISG, with
the current and future context on which the
production site finds itself, in the form of the
Requirements. As mentioned, the end output is a
business model or models that make the case to
implement the designed energy flexible ISG. The
creation of these business models is crucial as they
are the cornerstone on which the energy management
strategies for the energy flexible ISG are built.
3.8 ISGM Information and
Communications Layers
The development of the Information and
Communications Layers are based on the aggregation
of the information exchange stage of each Use Case,
as described in section 3.4., and their correlation with
the Component and Function Layer. The Information
Layer will assign to each component, all the
information packages that it should be able to swap
with the other components, thus defining the
necessary capabilities of those components in charge
of information and control (The components located
in the ISG Zones, see section 3.3). If a component in
the Component Layer is unable to gather and
exchange any of the assigned information packages,
it needs to be retrofitted.
The creation of the Communications Layer is
based on the actor-information assignment performed
in the Information Layer, and consists of
synthesizing, the necessary protocols and
mechanisms for interoperable exchange of the
information packages between components. The
Information and Communications Layer should be
homologated with platforms developed for the
marketing of energy flexibility (Körner et al. 2019).
3.9 Implementation Plan
Once the ISGM has been developed, it serves as the
blueprint to implement the energy flexible ISG. The
Component Layer will describe the physical topology
of the ISG. For greenfield sites, it will provide the
necessary IT-component topology. In the case of a
brownfield site, it will serve to identify the
shortcoming of the current IT infrastructure. The
CoEEE 2021 - International Joint Conference on Energy and Environmental Engineering
36

Function Layer will provide the basic input to
develop the energy management system (EMS) that
will control the ISG. The Business Layer provides the
necessary logic that the EMS needs to follow to
techno-economically optimize the energy
performance of the site. The information and
communications layer allow for the homologation of
the new infrastructure with the existing one in the
case of brownfield sites, or the selection of the most
optimal configuration in the case of greenfield sites.
In a nutshell, the ISGM is a multi-disciplinary tool
allowing production sites to transform their existing
electrical, and also other energy, grids into ISGs.
4 INSIGHTS AND OUTLOOK
The systematic approach presented in this article was
applied to develop an energy flexible ISGM based on
3 previously identified EFMs in an existing
automotive manufacturing plant. Two primary
objectives were defined for the implementation of
these EFMs: a-) Internal “Peak Shaving” and b-) the
intelligent response to the volatility of energy prices.
The scope was determined by the selected EFMs,
which were two energy storage measures at a hall and
TBS level respectively and one measure dealing with
the adaptation of process parameters also at the TBS
level. The involved domains, as can be inferred from
the scope, were until the auxiliary processes level, as
explained in section 3.3 and, due to the current
automation strategy of the site, all of the identified
zones were involved in this specific ISG. The
application of the approach provided the following
insights:
• The implementation of the use case
methodology, in particular of the Use Case
diagrams, Technical Details and Step-by-
step analysis stages, is crucial to fully
understand the effect the implementation
EFMs might have on the production site.
The subdivision of the EFM in individual
activities, as performed during the
development of the Use Case diagrams,
allowed to fully identifying the sequence in
which events should take place to achieve
the different modes of operation, identify
which are their triggering events, and the
actor-activity relationships. Based on the
developed diagrams, the building up of the
Technical Details, which consists of the
creation of the actors' list of each EFM and
the assignment of roles to some of these
actors, was considerably straightforward.
The diagrams allowed the identification of
actors that initially were not considered
relevant for the activation of the specific
EFMs. Likewise, the step by step analysis
allowed for potential previously unidentified
influences and risks of the retrieval of EFMs
on the material, energy, information flows to
also become clear.
• The build-up of the Component Layer serves
as a comparison between the current and
should IT infrastructure of the site. It served
to also identify components, that are
currently available on-site but for which
relevant capabilities are not yet being used.
• The construction of the Business, Function
and Information Layers outlined in detail the
necessary specifications that are required in
hardware and software to connect the
industrial systems with the external
stakeholders. They also served as a crucial
input for innovative plant management
strategies to optimize the energy flows
within the plant.
Overall, the implementation of the proposed
approach allowed to identify gaps in the current
energy and information flows, which can
substantially improve the transparency, resilience
and, of course, flexibility, of the analysed production
site. Furthermore, once the design was concluded it
was clear that although its main goal was the
inclusion of IEF, other energy management goal, i.e.
efficiency, resilience, can also be easily achieved by
the designed ISG. The presented approach, therefore,
allows for industrial sites, of any nature, to develop
smarter energy grids that increase the productivity
and competitiveness of the site.
ACKNOWLEDGEMENTS
The authors would like to thank the
Bundesministerium für Bildung und Forschung
(BMBF) and the Projektträger Jülich, which have
funded and promoted the Kopernikus Project
SynErgie, on which the development of the work here
described took place.
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