Managing and Controlling Decentralized Corporate Energy Systems
Transferring Best-practice Methods to the Energy Domain
Christine Koppenhoefer, Jan Fauser and Dieter Hertweck
Herman Hollerith Zentrum, Reutlingen University, Danziger Str. 6, Böblingen, Germany
Keywords: Decentralized Power Production, Management of Multi-Dimensional Business Objectives, Complexity
Management, Balanced Scorecard, Energy Balanced Scorecard, Enterprise Architecture Management, Energy
Enterprise Architecture.
Abstract: Managing decentralized corporate energy systems is a challenging task for enterprises. However, the
integration of energy objectives into business strategy creates difficulties resulting in inefficient decisions. To
improve this, practice-proven methods such as the Balanced Scorecard and Enterprise Architecture
Management are transferred to the energy domain. The methods are evaluated based on a case study.
Managing multi-dimensionality and high complexity are the main drivers for an effective and efficient energy
management system. Both methods show a positive impact on managing decentralized corporate energy
systems and are adaptable to the energy domain.
1 INTRODUCTION
More and more decentralized power generating sites
have evolved in recent years. Decentralized power (or
energy) generation is defined as a production close to
where it is used, which aims at self-consumption and
usually focuses on renewable energy (Breyer et al.
2013). Enterprises in particular have changed the
traditional energy supply chain from a 100% energy
consuming to a prosumer role (combination of
producer and consumer), building up their own
power production sites. Several reasons for this are
stated by the companies, such as the price advantage,
energy price stability, acceptable amortization time of
power facilities, flexibility of power demand and, of
course, environment and resource protection (DIHK -
Deutscher Industrie- und Handelskammertag & VEA
- Bundesverband der Energie-Abnehmer e.V. 2014),
(Döring 2015). The last argument is especially
growing in importance due to changing cultural
values, legal issues and environmental challenges. As
a result, enterprises end up with a decentralized
corporate energy system resolving corporate energy
goals. Research done in the last years shows, that
corporate energy management is seldom aligned with
the overall corporate strategy ending in suboptimal
energy system decisions or in business decisions
contrary to energy goals (Manthey & Pietsch 2013),
(Posch 2011) ending up in “accidental” energy
architectures (Giroti 2009). Additionally, digital
transformation changes the energy domain which
causes serious challenges for managing energy
systems (Doleski 2016).
This paper aims to analyze the challenges of
managing decentralized corporate energy systems
and to research the applicability of the best-practice
methods to the energy domain. Therefore, the
following research questions have been formulated:
1. What are the main challenges for an effective
corporate energy management system?
2. Which best-practice-proven methods address
the identified challenges, and
3. What has to be taken into account by an
application to the energy domain?
The feasibility and benefit of the approach is
demonstrated on a case study. Clustering findings
along an energy management framework enables
barriers to be detected. These results are combined
with two widely used modelling methods, the
Balanced Scorecard and Enterprise Architecture
Management, which help to overcome the obstacles.
2 METHODOLOGY
Although the relationship between business strategy
and smart grid design is stated in the Smart Grid
Reference Architecture, there´s a lack of empirical
research that shows the alignment between business
strategy and decentralized corporate energy systems.
532
Koppenhoefer, C., Fauser, J. and Hertweck, D.
Managing and Controlling Decentralized Corporate Energy Systems - Transferring Best-practice Methods to the Energy Domain.
DOI: 10.5220/0006388605320540
In Proceedings of the 19th International Conference on Enterprise Information Systems (ICEIS 2017) - Volume 3, pages 532-540
ISBN: 978-989-758-249-3
Copyright © 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

The company which was studied in our research
offers a unique botanical garden to its visitors and
focuses on recreation and relaxation. With over 300
employees in summer and about 150 in winter, it is
categorized as a medium-sized company. The
company has several decentralized renewable energy
generating sites on its property. Ecological goals are
clearly stated in its corporate strategy. When the
enterprise started implementing an energy
management system, various obstacles were detected.
Therefore, this case study, which was one of five in a
bigger research initiative, focuses on energy
efficiency topics, reflecting our research interest and
goals and helping us to answer the previously
introduced research questions.
Since the aim of this research is to analyze,
design, implement and evaluate a new energy
management solution, the authors adopt an active role
in the development of corporate energy management.
Hence, our research activity conforms to the tenets of
action research (AR). Baskerville (1999) defines
action research as an iterative process involving
researchers and practitioners acting together on a
particular cycle of activities, including problem
diagnosis, action intervention, and reflective learning.
AR is a widely discussed collaborative research
approach and a significant amount of literature on this
topic is available (Avison et al. 1999).
To increase construct validity and reliability (Yin
2009), three data collection methods were used
during the case study: semi-structured interviews,
participating observation and document analysis.
Conducted research is part of a public research
program named ENsource (www.ensource.de) which
focuses on decentralized and flexible solutions for
future energy production and distribution. This
project is funded by the Ministry of Science, Research
and the Arts of the State of Baden-Wuerttemberg,
Germany and the European Regional Development
Fund (EFRE).
3 CASE ANALYSIS
Establishing decentralized renewable energy
generators on the company´s territory is based on the
corporate vision to create an economic and ecological
balance. The company’s founder, who felt a high
environmental responsibility, set this goal in place
one generation ago. The corporate energy system
mainly encompasses four photovoltaic sites, a gas
block heat and power station, a wood distillation
block heat and power station, a wood pellet power
generation site and gas-fired boilers. A local energy
provider supplies the additionally needed electrical
power and gas. An additional biomass energy site is
in discussion. The generating sites are owned and
managed by several stakeholders. The traditional
Figure 1: Energy Value Network (own illustration).
Managing and Controlling Decentralized Corporate Energy Systems - Transferring Best-practice Methods to the Energy Domain
533

energy value chain (centralized power generation =>
transmission => distribution => Retail through an
energy supplier) evolves thereby to an energy value
network (Figure 1) where power generation,
distribution and retail are combined transactions.
The value network demonstrates the multiplicity of
actors and their complex relationships with each other
which result in a highly complex and diverse system.
Managing such a corporate energy system requires an
efficient and effective management system to
implement and support the corporate vision.
The scientific literature concerned with energy
management systems (EnMS) is still limited and
publications focus on practice-oriented books
(Hubbuch 2016). A report from Natural Resources
Canada proposes a best practice method for energy
management and is based on results of training
thousands of organizations in energy management
(Natural Resources Canada 2015).
Figure 2: Energy management categories (Natural
resources Canada, 2015).
According to this best practice guide, effective
energy management requires a holistic approach that
considers actions in eight categories, which are:
Commitment, Planning, Organisation, Projects,
Financing, Tracking, Communication, and Training
(figure 2). The performance in each category is rated
on a scale of 1-5. Level 5 means the organisations
works in an optimal way, while level 1 means no
action or successful activities can be noted in this
category. This method can be used to set an energy
policy or to check the state of an EnMS within an
organisation.
The findings of the case study are examined and
rated using this method to detect gaps in the
company’s decentralized corporate energy system
and then to identify practice-proven methods aiming
to close these gaps.
Commitment: The company’s vision of an
economic and ecological balance is clearly
formulated and published. The management board
has a high commitment towards this vision and the
continuous improvement of the environment is a
corporate goal. Three main energy goals (energy
saving, energy efficiency and decentralized
renewable power generation) were set up in 2013.
However, none of these goals are connected with
quantifiable numbers nor with a timeline. A tracking
of target achievement is not possible. Therefore, the
level is set at 4.
Planning: The enterprise started to establish an
EnMS according to ISO 50001, a specification
created by the International Organization for
Standardization for an energy management system..
Accordingly, the company established multiple
detailed energy targets. But an outlined roadmap
connecting measures to the top energy objectives or
vice versa, measures derived from the objectives, is
missing. The chosen targets seem unsystematic and
have, yet again no quantification. As well, no
deadlines are fixed. The published energy targets are
either very detailed (e.g. changing a specific catering
oven) or very broad (e.g. reconstruction of the green
houses). A combining energy concept is missing. This
criterion is rated at level 2, aiming to 3 only.
Organisation: There is one person working as an
energy manager. His authority to give directions is
limited and restricted to recommendations toward
other business divisions. The rating of this criterion is
3.
Projects: The development of energy measures
and projects are rather ad hoc and opportunity-driven
and not systematically connected to the energy
objectives. Several identified and published energy
targets were not converted into projects due to
economic reasons. Therefore, this criterion is rated at
level 3 again.
Financing: The energy investments are based on
short-term criteria and are, in the end, economically
driven. No business case towards monetary effects
through energy savings or efficiency has been
conducted. The rating is 3 again.
Tracking: Momentarily one of the main tasks of
the energy manager is collecting and organizing
energy data. At present the available data and its
quality is not sufficient for implementing the aspired
goals. The unavailability is based upon three factors:
AEM 2017 - 1st International Workshop on Advanced Enterprise Modelling
534

no data is measured at relevant local spots, energy
data is not digitized and finally the data is not
available in the needed aggregation level. For
example, it is not possible to assign the energy
consumption to the profit centers of the company.
Therefore, this criterion is rated with 2.
Communication: Energy communication towards
the public and the internal staff exists. On a yearly
basis, the company publishes its sustainability report,
which includes an overview about energy
consumption, targets and projects. Via the company’s
intranet, energy information is supplied to the staff.
The rating of this criterion is 3.
Training: Energy saving and efficiency trainings
for staff members takes place. However, results are
hardly seen. According to the energy manager a
rejection of these topics even occurred due to too
many ecological training measures. Taking the results
into account, the rating of this criterion is split into 2
(training takes place) and 4 (poor results).
Figure 3: Overview of the ratings and resolving challenges
(own illustration).
Figure 3 gives an overview of the case study ratings.
The results show that the company and its
management board have a high commitment towards
energy objectives and have started energy
transformation measures in different areas. Yet,
further progress is hindered through two specific
categories: planning and tracking. The corporate
vision of a balanced economical-ecological strategy
(criteria “Commitment”) requires an alignment of
economic and energy-related objectives and
measures (criteria “Planning”). The implemented
EnMS doesn´t support such functionality so far.
Therefore, the needed energy reflection for corporate
decisions has not been implemented and corporate
decision making processes are mostly economically
driven. To overcome this obstacle multi-
dimensional viewpoints have to be included into the
company’s strategy.
Managing and controlling a decentralized
corporate energy system is based on energy data.
However, the result in the category “Tracking” shows
an essential gap in this area. Missing measurement
spots, heterogeneous data formats and missing
digitization processes are the main barriers. On top of
that, the high diversity of decentralized power
generation systems (figure 1) leads to a highly
complex system.
4 IDENTIFICATION AND
TRANSFER OF PRACTICE-
PROVEN METHODS
Based on the case analysis two main challenges are
identified: Management of multi-dimensionality and
of complexity.
Integrating different viewpoints into a company´s
strategy is the basis of the management and
controlling method “Balanced Scorecard (BSC)”.
The BSC approach introduced by Kaplan & Norton
in 1992 (Kaplan & Norton 1992) addresses a
combination of four business perspectives (financial,
customer, internal business processes, and learning
and growth) and offers the possibility to integrate
further strategic views (Kaplan & Norton 1996).
Various new perspectives, for example an IT-
perspective were implemented successfully in the last
years (Huang & Hu 2007), (Van Grembergen & Saull
2001). The BSC is a global standard for managing
complex systems and is in widespread use in private
(Van Grembergen & Saull 2001), (Huang & Hu 2007)
and public sectors (U.S. Departement of Energy
2017). Objectives are linked to measures and
quantified through key performance indicators (KPI).
Because of this a constant controlling of the
improvements is possible. Such a holistic approach
enables the integration of energy objectives into
multiple corporate strategy dimensions. BSC
information systems are widely used and numerous
tools exist on the market. Therefore a quick initial
implementation of an Energy Balanced Scorecard
(EBSC) to improve decentralized corporate energy
systems is possible and enables an evaluation of the
method adoption.
The Enterprise Architecture Management (EAM)
approach has been proven to be an efficient
instrument to align business and IT from a holistic
perspective and to control the complexity of IT
landscapes (Hanschke 2012), (Hauder et al. 2014).
EAM is used to model the as-is state landscape and to
derive further on to the to-be state. The decentralized
energy system reflects a complex energy landscape,
which has to be aligned to the corporate objectives.
Therefore EAM characteristics provide positive
impact for establishing an effective EnMS.
Managing and Controlling Decentralized Corporate Energy Systems - Transferring Best-practice Methods to the Energy Domain
535

EAM is an accepted methodology in practice and
academia (Uslar et al. 2013). One of the most used
EAM modelling languages is Archimate (The Open
Group 2016). Archimate is hosted by The Open
Group which also provides “The Open Group
Architecture Framework” (TOGAF) (Haren 2011).
TOGAF is a widespread and established enterprise
architecture framework, which has been elaborated
by several large industry actors as members of The
Open Group.
4.1 Improving EnMS with the
Balanced Scorecard Method
The BSC offers several advantages: First, with this
method it is possible to monitor present performances
as well as obtaining information about the future
ability to perform. Second, it assists in translating an
organization’s vision into actions through strategic
objectives and a set of performance measures
supported by specific targets and concrete initiatives.
Third, using the BSC facilitates the identification of
success drivers, allowing managers to focus on a
small number of critical indicators, thereby avoiding
information overload (Vieira et al. 2016). Several
adoptions of the BSC towards sustainability
addressing social and environmental dimensions have
been implemented in the last years (Figge et al. 2002),
(Arnold et al. 2003), (Sidiropoulos et al. 2004) and
proved that integrating ecological perspectives is
successful. However, the implementation of an
energy viewpoint is hardly dealt with in scientific
literature (Vieira et al. 2016) and seldom found in
practice (Laue 2016).
Based on the results of the case analysis an
Energy BSC was modelled using the software
“ADOSCORE” from BOC. A typical corporate
objective was selected to demonstrate the usefulness
of managing multi-dimensional corporate goals with
an inclusion of energy perspectives. “Increasing the
number of park visitors (customers)” is a typical
business goal and reflects the interdependencies
between customer-, financial- and energy
dimensions. The relations between these dimensions
illustrates the impact of customer measures on
financial and energy goals and vice versa. The energy
BSC is illustrated in figure 4.
Pyramids with connected KPIs to enable an
ongoing controlling process, symbolize objectives in
each perspective. Red or green dots signal a positive
or negative development according to pre-quantified
goals. An aspired increase of visitors (green dot) leads
in the financial perspective to a revenue increase and
higher profits which results in a rise of the equity
ratio. Simultaneously on the energy perspective due
to higher power demands through e.g. higher catering
Figure 4: Energy BSC (own illustration).
activities, the KPI for decentralized renewable power
generation is turning negative as well as the energy
objective “Energy savings”. The Energy BSC signals
the energy manager, and respectively the board of
management, when there is a need for adjustments.
The implementation of an Energy BSC showed
that the method provides corporate management with
a transparent controlling process integrating energy
goals into corporate strategy. Taking the studied case,
the model indicates direct negative consequences on
the energy goals through increasing visitor numbers.
Identifying such goal conflicts between strategic
dimensions enables the management to set up
compensating energy measures or to adjust customer
goals.
For an effective EnMS an on-going controlling
and decision making process with up-to–date
information is necessary. A data-warehouse-based
BSC standard software like ADOSCORE offers the
possibility to integrate energy data via Excel or SQL-
database-statements enabling a continuous digital
data integration. However, the analysis of the studied
case expresses a gap regarding data tracking,
grounded on the heterogeneous database and the non-
existing digital energy data flow that significantly
hinders the multi-dimensional controlling process.
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Managing and controlling energy goals in a
corporate strategy with BSC has been applied
positively. The BSC offers the possibility to manage
the multi-dimensionality of a corporate energy
system. Therefore, transferring the BSC method onto
the energy domain is possible and results in a positive
impact. Yet, the analyzed BSC approach focused test
wise on one business goal only. An expansion of the
BSC combing all relevant corporate perspectives has
not been conducted yet. Further, the BSC method is
only as good as the selected measures and KPIs.
Finally, the findings of the case study indicate
clearly that a fully digital energy data process is the
foundation of an effective and efficient usage of the
BSC.
4.2 Modelling Corporate Energy
Systems with Enterprise
Architecture Management
An enterprise is a complex and highly integrated
system consisting of processes, organizations,
information and technologies, with interrelationships
and dependencies in order to reach common goals
(Razavi et al. 2011). A common problem of many
medium-sized enterprises is the diverse IT-landscape.
A mostly unsystematic growth of applications in
enterprises over time results in “accidental
architectures” (Giroti 2009). The corporate energy
system with its high diversity and its unsystematic
growth leads to a similar development with similar
difficulties like in the area of IT. Taking the case
study results (criteria “Tracking”), data heterogeneity
and non-existent digital energy data processes
resemble the IT-domain. In order to solve these
problems enterprises need to be aware of their
relations among strategy, business processes,
applications, information infrastructures and roles.
Enterprise Architecture Management (EAM)
contributes to solve these problems. It is a holistic
approach providing methods and tools to establish a
complete perspective on enterprises (Lankhorst
2013). Architecture is thereby defined as a
fundamental concept of a system in its environment,
embodied in its elements, relationships, and in the
principles of its design and evolution (International
Organization Of Standardization 2011). According to
(Lankhorst 2013), EAM can be defined as “a coherent
whole of principles, methods, and models that are
used in the design and realization of an enterprise’s
organizational structure, business processes,
information systems, and infrastructure”. In this
context, EAM provides an approach for a systematic
development of the organization in accordance with
its strategic goals (Ahlemann et al. 2012). Thus, EAM
evolves as a best-practice method that positively
assists an EnMS.
In the findings of the case analysis, several
characteristics were identified indicating EAM
solution potential: First, the complex, unsystematic
development of corporate energy architecture; second
the multiple energy consumers (e.g. catering
facilities, greenhouses, administration, event
facilities), third the heterogeneous energy data
landscape resulting in missing data recording spots,
only analog data existence at various metering spots
and rough data. And finally the incoherent energy
data process.
For modelling the Enterprise Architecture, the
ArchiMate 3.0 (The Open Group 2016) modeling
language was selected because the entity “physical
elements” enables the modeling of power generation
sites. For modeling the Archimate models, we used
the modelling tool Signavio. The modelled Energy
Enterprise Architecture (figure 4 and 5) shows a
simplified representation of the energy system in our
case study. The model enables the visualization of the
current energy data process, the identification of
digital gaps, and the planning of a roadmap towards a
better fitting, future Energy Enterprise Architecture.
Figure 5 shows the energy data process on a high
granular level. The business process consists of three
steps (entity “Business process”): capturing
electricity energy production, capturing electricity
energy consumption and balancing production and
consumption data. The process is connected (entity
“Realization”) with two separate Excel-files (entity
“Application component”). For reasons of better
demonstration, just the electrical power grid is
modelled. The model points out the existence of side-
by-side energy Excel sheets.
Figure 5: Energy Data Process (own illustration).
The Energy Enterprise Architecture (figure 6)
reflects the business process “increasing park
visitors” and its resolution in higher energy demand
in catering facilities (chapter 4.1).
Managing and Controlling Decentralized Corporate Energy Systems - Transferring Best-practice Methods to the Energy Domain
537

Figure 6: Energy Enterprise Architecture (own illustration).
It describes the data sources for generated and
consumed electrical power linked to the above
mentioned Excel-files. Today, the energy data
recording process is carried out manually. Data from
electric meters is manually written into an Excel file
The Energy EA displays the decentralized power
generation system with its generation material as well
as the catering electricity consumers. Producer and
consumers are connected via the power grid.
The Energy EA reflects the as-is state of the
decentralized energy system and enables the energy
manager to identify data gaps, existing data flows, the
quality of data (analog-to-digital), data sources etc.
This information is the baseline for planning the to-
be-model based on a corresponding roadmap.
Modelling an Energy EA provides a positive
impact for an effective energy management system
and is therefore a useful method for managing the
energy domain in a digital, data driven process. By
now the modelling approach is simplified and
represents only a small part of the decentralized
energy system. Different viewpoints have to be
integrated as well. Still, designing an Energy EA and
the development of an EA-roadmap is the basis for
the implementation of an effective Energy Scorecard
and an enterprise wide, multidimensional Controlling
System.
5 CONCLUSION
Decentralized corporate energy systems have evolved
constantly in recent years, changing the role of
enterprises to energy prosumers. Companies are
motivated to build up their own power production
sites due to price advantages, energy price stability,
power demand flexibility, environmental protection
and legal obligations. However, establishing an
effective EnMS relies on challenges in eight different
categories. Applying these to the conducted case, our
study identified two main obstacles: Managing Multi-
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538

dimensional target systems and enterprise
complexity.
Two practice-methods that address these
challenges, the Balanced Scorecard and Enterprise
Architecture Management were identified and
evaluated in this paper. The Balanced Scorecard
enables enterprises to manage complex and link
multi-dimensional strategies. However, the current
energy EA can´t deliver the energy data necessary for
proper system management. EA Modelling enables
the visualization of the energy enterprise architecture
to identify gaps in data flow and digital processes.
These gaps define the roadmap towards a future
Energy Enterprise Architecture that copes with the
planned future development.
The transfer and partial integration of BSC and
EAM to the energy domain seems to offer a
promising impact for managing corporate energy
systems. Yet, further research is needed in respect of
method integration, to find standardized interfaces
between business demand and operational energy
system data sources. Future research on conceptual
models and their validation by empirical use cases
will elaborate the data driven management of
decentralized energy systems.
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