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Review article
Renewable energy communities or ecosystems: An analysis of selected cases
Kankam O. Adu-Kankam
a
,
b
,
*
, Luis M. Camarinha-Matos
a
,
**
a
Nova University of Lisbon, School of Science and Technology and UNINOVA - CTS, Campus de Caparica, 2829-516 Monte de Caparica, Portugal
b
School of Engineering, University of Energy and Natural Resources (UENR), P. O. Box 214, Sunyani, Ghana
ARTICLE INFO
Keywords:
Collaborative networks
Energy ecosystems
Peer-to-peer energy exchange
Sharing economy
Renewable energy communities
Virtual power plants
ABSTRACT
The rapid proliferation of renewable energy communities/ecosystems is an indication of their potential contri-
bution to the ongoing energy transition. A common characteristic of these ecosystems is their complex compo-
sition, which often involves the interaction of multiple actors. Currently, the notions of "networking",
"collaboration", "coordination", and "cooperation", although having different meanings, are often loosely used to
describe these interactions, which creates a sense of ambiguity and confusion. To better characterize the nature of
interactions in current and emerging ecosystems, this article uses the systematic literature review method to
analyse 34 emerging cases. The objective is threefold (a) to study the interactions and engagements between the
involved actors, aiming at identifying elements of collaboration. (b) Identify the adopted technological enablers,
and (c) ascertain how the composition and functions of these ecosystems compare to virtual power plants. The
outcome revealed that the interactions between the members of these ecosystems can be described as cooperation
and not necessarily as collaboration, except in a few cases. Regarding technological enablers, a vast panoply of
technologies, such as IoT devices, smart meters, intelligent software agents, peer-to-peer networks, distributed
ledger systems/blockchain technology (including smart contracts, blockchain as a platform service, and crypto-
currencies) were found. In comparison with virtual power plants, these ecosystems have similar composition,
thus, having multiple actors, comprised of decentralized and heterogeneous technologies, and are formed by
aggregating various distributed energy resources. They are also supported by ICT and are characterized by the
simultaneous flow of information and energy.
1. Introduction
Electrical energy is crucial nowadays, and without it, contemporary
societies cannot function adequately. This claim stems from the fact that
critical sectors of modern society, which include industries, housing,
communication, road infrastructure, education, health, and the financial
sectors, depend largely on electrical energy. However, unlike past soci-
eties, the modern society, which is touted as the Fourth Industrial Rev-
olution has heavily been dependent on fossil fuels energy sources. As
published by “our world in data”[1], Fossil fuels have been the funda-
mental driver or enabler of the technological, social, economic and
developmental progress of this current Industrial Revolution. In [2],
Forbes claimed that fossil fuels account for 84% of global energy use,
although this conventional energy source is known for its limited avail-
ability [3] and adverse impact on the environment [4], human health
[5], and economic activities [6]. Moreover, the dominant literature
suggests that severe exploitation of the Earth's resources to satisfy
society's growing demands for energy is troubling, and has contributed to
the ongoing climate change catastrophe, which poses a ruinous risk to the
sustainability of the planet. Due to the many environmental concerns that
are associated with fossil fuels, the need for safer, greener and more
sustainable energy sources is imminent. Currently, researchers and pol-
icymakers have realized the potential benefits of transitioning from fossil
fuel sources to renewable sources [7]. This is because, unlike fossil fuels,
renewable energy is known to be inexhaustible [8] and can replenish
itself in a relatively short period, thus helping to overcome the
finite-supply problem associated with fossil fuels. In addition, renewable
energy sources are cleaner, self-replenishing, environmentally friendly,
and less harmful to human existence on planet Earth.
Regarding the transition from fossil fuels to renewable sources,
Navigant [9] asserted that the future of energy would be cleaner, mobile,
intelligent, and smarter as it would be dominated by renewable sources.
Evidence of this claim is visible in the form of new and widespread
renewable energy-related technologies and services that are currently
* Corresponding author.
** Corresponding author.
E-mail addresses: k.adu@campus.fct.unl.pt (K.O. Adu-Kankam), cam@uninova.pt (L.M. Camarinha-Matos).
Contents lists available at ScienceDirect
Heliyon
journal homepage: www.cell.com/heliyon
https://doi.org/10.1016/j.heliyon.2022.e12617
Received 11 May 2022; Received in revised form 25 July 2022; Accepted 16 December 2022
2405-8440/©2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Heliyon 8 (2023) e12617
emerging at the peripheries of the power grid. The expectation is that
these advances could be the technological drivers or enablers of the
transition agenda, which aims to transform the current power grid to-
wards a "digitized," "decentralized," "decarbonized," "democratized" and
“smart”power network [10]. The projections of Navigant, as well as the
ongoing energy transition, are also affirmed by other researchers, such as
[11] and [12], regarding the future of energy. Some of the advances
claimed by Navigant include (a) widespread integration of distributed
generation, (b) peer-to-peer energy trading, (c) renewable energy com-
munities, and many more. Besides these claims, several cutting-edge,
innovative, and complementary technologies, such as (a) artificial in-
telligence, (b) cloud computing, (c) the Internet of Things, (d)
cyber-physical systems, and (e) blockchain technology are also emerging
within the energy terrain. The integration of these diverse, innovative
and complementary technologies into the renewable energy landscape is
paving the way for new types of organizations, relationships, partner-
ships, business models, and services that are beginning to show within
the energy space [11,13,14]. Other aspects of the transition, as
mentioned by Gartner in [10], involve new roles that are played by
autonomous actors, such as asset owners, system operators, and other
economic entities, who have also evolved to become active participants
and key players in the transition.
Among the plethora of approaches that have been suggested to help
increase the penetration of renewable energy sources, in support of the
transition, is the notion of Renewable Energy Communities (RECs) or
energy exchange/sharing ecosystems, as described in [15]. These eco-
systems are gradually becoming an integral part of the grid system due to
their potential benefits [16]. According to the European Parliament and
the Council of the European Union [5], RECs are based on free and
voluntary participation. They are autonomous and managed by stake-
holders. REC members can produce their own energy, which can be used
locally, stored, sold, or shared with others in the framework of a com-
munity. According to the European Commission [17], at least 2 million
people in the European Union are involved in more than 7700 RECs.
These RECs have contributed nearly 7% of the Union's installed capacity,
with an estimated total renewable capacity of no less than 6.3 GW. In
terms of financial investment, some 2.6 billion Euros have been invested
in RECs to date. Similarly, in the United Kingdom, there are over 5000
RECs that have contributed over 60MW of energy to the country's energy
stock, with over 23 million Pounds contributed to community benefit
funds for the benefit of local communities.
This notwithstanding, the number, types, composition, and charac-
teristics of actors who are found to participate in these RECs have
changed in recent years. The new actors are currently found to be
constituted of several diverse autonomous and heterogeneous entities
that can participate in the exchange of goods and services either “for-
profit" or "non-profit" within these ecosystems. Usually, these actors are
driven by a common interest or some objective that is compatible or
common to the involved actors. These actors may constitute (a) con-
sumers, (b) prosumers, (c) third-party energy service providers, (d) dis-
tribution service operators, (e) utility companies, (f) non-profit
organizations, (g) financial institutions, (h) academic/research in-
stitutions, and (i) decentralized autonomous organizations, among many
others. According to [18], when all of these autonomous and heteroge-
nous entities work together in the context of a community, it could help
uncover new ways to generate value, such as earning revenue that could
help participants mitigate the rising cost of energy in these communities,
as well as promote investment in renewable energy.
The rationale behind the sharing principles that underline these
ecosystems, and their operation follows the current trends in the notion
of the “sharing economy”, which is also aliased as (a) the collaborative
economy, (b) collaborative consumption, (c) on-demand collaborative
economy, (d) peer-to-peer (P2P) economy, (e) zero-marginal cost econ-
omy, and (f) crowd-based capitalism [14]. In [19], the authors shed more
light on this economy and emphasized that its proliferation is the result of
a technological phenomenon that has enabled the advancement of online
platforms that promote user-generated content, sharing, and collabora-
tion. These platforms function as intermediaries or marketplaces that
enable the exchange or shared use of goods and services from peers, both
for-profit and non-profit, through intermediation, matchmaking, and
value-added services [20]. In the European Union H2020 Ps2Share
research project [20], eight different definitions of the sharing economy
are mentioned. For their relevance to this study, five of them are quoted
below:
a. “.......... peer to peer sharing or access to underutilized goods and services,
which priorities utilization and accessibility over ownership.”
b. “..........group of online platforms facilitating peer-to-peer forms of eco-
nomic activity.”
c. “…......the use of online marketplaces and social networking technologies
to facilitate peer-to-peer sharing of resources (such as space, money, goods,
skills, and services) between individuals, who may be both suppliers and
consumers.”
d. “…the peer-to-peer-based activity of obtaining, giving, or sharing the access
to goods and services, coordinated through community-based online
services.”
e. “……...consumers granting each other temporary access to under-utilized
physical assets (“idle capacity, possibly for money.”).
From the above definitions, it can be argued that products, services,
and market relationships are changing radically in this new economy.
Goods and services are currently moving away from centralized owner-
ship to decentralized sharing, impacting businesses and their modus
operandi in a very disruptive way. Juxtaposing the sharing economy with
the REC concept, it is observed that community members who generate
their energy locally from renewable sources, which are located in their
homes, offices, and factories, can share or trade their surplus or excess
with other community members in a localized market for-profit or non-
profit. This fact, therefore, helps to situate the REC concept in the
context of the sharing economy.
Following the above, we propose the objectives of this study, which is
to conduct a case study on 34 selected emerging cases of energy-sharing
ecosystems. Our objectives are threefold. First, to gain some insight into
the nature of the interactions that exist between the various actors
participating in these energy-sharing ecosystems, namely, to study the
interactions and engagements that occur between the involved actors to
ascertain whether the interactions that govern these sharing behaviours
emerge out of (a) networking, (b) coordination (c) cooperation or (e)
collaboration relationships. The motivation for this objective is gleaned
from the fact that the ongoing energy transition is likely to create a future
scenario where thousand or possibly, millions of interconnected actors,
smart devices, and intelligent systems co-exist and do work together. For
such a synergy to be efficient, beneficial, and reliable, the involved en-
tities must cooperate in a trustful way that brings mutual benefit to all. As
claimed by [21] collaboration is the process through which a group of
entities enhance the capabilities of each other. The process involves the
mutual engagement of the participants so that they can together, solve, a
common problem using a collective approach. Furthermore, collabora-
tion enables entities to be more competitive against other competing
entities or groups. It can also increase the survivability of the group in
times of turbulence. Therefore, knowing the nature of interactions that
exist between actors within these ecosystems could provide a good base
to explore possible avenues to strengthen or increase the survivability,
resilience and competitiveness of these ecosystems using collaborative
techniques. To help achieve this objective we adopted concepts and
background knowledge from the domain of collaborative networks (CNs)
to help analyze these cases.
Our second objective is based on the fact that these ecosystems thrive
and continue to proliferate as long as they are able to provide participants
with secure, fast, trustful, efficient, and transparent services. Therefore,
understanding the trends and the types of technologies that are being
used to support these ecosystems also form a relevant aspect of this work.
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
2
The motivation for this aspect of the study is to determine the extent to
which digitalization and the digital transformation are impacting the
energy sector, particularly RECs. The anticipation is that knowledge
about the kinds of digital technologies that are currently trending in this
space could help provide a fair assessment of the level of penetration of
these technologies within the mentioned energy environment.
Finally, we aim at exploring how the composition and functions of
these ecosystems compare to the concept of Virtual Power Plants (VPPs).
This is because, superficially, these two concepts appear to be similar in
terms of their composition, organization, and behaviour. Again, this
research objective is motivated by the fact that VPPs are extensively used
to provide ancillary services to the power grid. According to [22] VPPs
are constituted of networks of distributed energy resources such as
photovoltaic systems, wind turbines, Combined Heat and Power (CHP)
units etc. By aggregating all these resources, a VPP can deliver similar
services and subsequently trade in the same energy markets just like large
central power plants. Furthermore, VPPs can be used to stabilize the
power grids and create the preconditions for the integration of renewable
energy sources into the grid. Superficially, these two ecosystems appear
to have a similar composition. However, in terms of their organization,
performance, and objectives, the case is not always the same. Having an
in-depth understanding of the deficiencies of RECs in comparison to
VPPS could open a new research opportunity to investigate how to
reconfigure RECs in a way that could enable them to perform functions
that are similar to VPPs. From these backgrounds, the following research
questions are therefore suggested to guide the study:
RQ-1: How can the interaction between members of the selected
energy ecosystems be described?
RQ-2: What technological enablers and trends underlie the estab-
lishment, operation, and service provision of these ecosystems?
RQ-3: How do the characteristics and functions of virtual power
plants (VPPs) compare to those of renewable energy ecosystems?
The remaining sections of the article are as follows: Section 2focuses
on discussing background knowledge and some base concepts. Section 3
is dedicated to the research methodology, followed by the "focus cases" in
Section 4. Finally, Section 5draws some conclusions and provides some
recommendations for future work.
2. Background knowledge and concepts
This section introduces some base concepts, namely from the domain
of collaborative networks (CNs). The section also gives an overview of
one case study, which is intended as an illustration to help map out and
further establish the complex synergies or interactions that take place
between the different players in the studied energy ecosystems.
2.1. Collaborative networks
In the last 20 years, the field of collaborative networks (CN) has
grown, which is a good sign for a society that is based on knowledge. The
rapid evolution of this body of knowledge emanated from challenges
faced by engineering systems, business entities, and the general society to
participate in collaborative ventures. Collaboration is known to bring
benefits to the involved entities as mentioned in [21]. From this domain
of study, we borrow some concepts that are typically used to describe
joint endeavours. We use these definitions as a guide to help us analyse
the considered cases, especially in the context of RQ-1.
2.2. Networking
A concept that involves communication and information exchange for
the mutual benefit of the participants. A simple example of networking is
the case where a group of entities share information about their experi-
ence using a specific tool. All of them can benefit from the information
made available/shared. However, there is no common goal or structure
that influences the form and timing of individual contributions, and
therefore there is no common generation of value [23].
Key features of networking: communication and information exchange
for mutual benefit; no targeted generation of common value.
2.3. Coordination
In addition to the exchange of information, coordination also involves
the alignment/alteration of activities to achieve more efficient results.
Coordination, which is the “act of working together harmoniously”,is
one of the main components of collaboration. An example of coordinated
activities happens when it is beneficial for several heterogeneous entities
to share some information and adjust the timing of their lobbying ac-
tivities for a new product to maximize their impact. However, each entity
may have a different goal and use different resources and methods to
make an impact. Value, in this sense, is mainly created at the individual
level [23,24].
Key features of coordination: communication and information ex-
change for mutual benefit; coordinated activities; each entity might have
a different goal and may use its own resources and methods; value is
created at the individual level.
2.4. Cooperation
Cooperation involves not only the exchange of information and
adjustment of activities but also the division of some (non-extensive)
labour among the participants. In this case, the added value results from
the addition of individual "components" of value generated by the various
participants almost independently. Based on client-supplier relationships
and predefined roles in the value chain. A traditional supply chain is an
example of a cooperative system. Each participant performs their part of
the work almost independently (although coordinated with others).
There is, however, a common plan, which in most cases is not jointly
defined but instead designed by a single entity, and which requires some
limited level of co-working, at least at the points where the results of one
partner are delivered to the next partner. However, their goals are
compatible because their results can be added or composed in a value
chain leading to an end-product or service [23,24].
Key features of cooperation: Communication and information exchange
for mutual benefit; coordinated activities; division of labour; common
plan but not jointly defined; sharing resources for achieving compatible
goals; aggregated value is a result of value generated by the various
participants in a quasi-independent manner.
2.5. Collaboration
Collaboration is a process by which entities share information, re-
sources, and responsibilities to jointly plan, implement, and evaluate a
program of activities to achieve a common goal. This concept is derived
from the Latin word "collaborare" which means “to work together”. It can
be seen as a process of shared creation, thus a process by which a group of
entities enhance each other's capabilities. It implies sharing risks, re-
sources, responsibilities, and rewards, which can also give an outside
observer the image of a collective identity if desired by the group.
Collaboration involves the mutual engagement of participants in solving
a problem together, which implies mutual trust and therefore requires
time, effort, and dedication. With collaboration, it is much harder to
realize how much each person has added to the creation of value [23,
24]. There must always be a common purpose (goal) for the collabora-
tion. This purpose could be expressed as a joint goal or problem to be
solved together. Parties' having their individual goals is not enough for
collaboration.
The following are some characteristics of collaboration:
- Preconditions for collaboration:
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
3
Parties mutually agree to collaborate, which implies accepting to
share.
Parties keep a model of each other's capabilities.
Parties share a goal and keep some common vision during the
collaborative process.
Parties maintain a shared understanding of the problem at hand,
which implies discussing the state of their progress (state awareness
of each other).
- Generic steps for a collaboration process:
Identifying the parties and bringing them together.
Defining the scope of the collaboration and defining the desired
outcome.
Defining the collaboration structure in terms of leadership, roles,
responsibilities, ownership, communication means and processes,
decision-making, resource access, scheduling, and milestones.
Defining policies. For example, handling disagreements and con-
flicts, accountability, reward, recognition, and ownership of
generated assets.
Defining the evaluation and assessment measures, mechanism, and
process.
Identifying risks and planning contingency measures.
Establishing commitment.
- Key features of collaboration:
Communication and information exchange for mutual benefit.
Coordinated activities.
Joint planning and implementation.
Mutual engagement for joint creation.
Sharing risk, resources, responsibilities, and rewards.
Having an image of joint identity.
Having common or compatible goals.
Individual contributions to value created are difficult to determine.
Figure 1 is an illustration of the types of joint ventures described
above.
2.6. A panoramic view of interactions existing between actors in a sample
of energy ecosystems
As mentioned at the beginning of this section, the result of a case
study conducted in [15] is adopted here to shed further light on the
assertion that these energy ecosystems are usually comprised of multiple,
autonomous, and heterogeneous actors who happen to share a common
environment and engage with each other in some form of interactions or
relationships. From the many cases considered in the study, we borrowed
the case of Feldheim [26], which is located in Germany, and shown in
Table 1. This case is chosen because it has most of the traits that can be
used to substantiate the claims that are being made. In Table 1,we
illustrate these claims under six taxonomies: (a) key stakeholders of the
ecosystem, (b) their key roles, (c) the kinds of energy resources that are
owned by the ecosystem or its members, (d) the characteristics and re-
lationships that exist between the roles, (e) the types of governance
systems that have been implemented, and finally (f) the interaction of the
community with the power grid.
Referring to Table 1, it can be observed that some of the “main actors/
key stakeholders”for this community are: (a) the Feldheim New Energy
Forum Foundation, (b) the Municipality of Treuenbrietzen, (c) residents
of Feldheim and Treuenbrietzen, (d) Feldheim Energiequelle GmbH, and
(e) Farmers’Cooperatives. Furthermore, focusing on the “Feldheim New
Energy Forum Foundation”under the heading “main actors/key stake-
holders,”it can be observed that the role of this stakeholder includes the
following. Acting as (i) project financier, (ii) management body, and (iii)
education and information provider.
In terms of energy resource ownership, it is found that all the energy
assets located in the community are collectively owned by the commu-
nity. The types of assets that are found are diverse and are constituted of
(1) a wind turbine, (2) photovoltaic modules (PVs), (3) biomass/biogas,
(4) Combined Heat and Power (CHP), and (5) lithium-ion battery storage
system.
Similarly, the following outcomes are observed about the “charac-
teristics and relationships between roles.”Two key descriptors are
considered here: (I) the description of the “characteristics of roles”and
(II) the description of the “relationships between roles.”Considering the
characteristics between roles it is discovered that this is principally a
public-private partnership. On the other hand, the “relationship between
roles”is found to be a “distributed system with centralized management
and hierarchical governance.”
Another key aspect of the case study is the governance structure that
is observed in the case. The “governance type”as mentioned in subsec-
tion (A) of Table 1 is “non-profit self-governance.”Additionally, the
“governance structure”as mentioned in subsection (B) is “executive
Figure 1. Classes of joint endeavours (adapted from [25]).
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
4
boards”and a “general assembly with voting rights.”Thus, one man, one
vote.
Finally, the interaction of the community with the power grid shows
that the community consumes 10% of the locally generated energy and
sends about 90% to the grid.
While this is a single example among many, the general observation
for almost all the cases discussed in [15] seems to follow a similar or
common trend in terms of composition, thus having multiple and
autonomous actors, heterogeneity of actors, relationships between ac-
tors, and ownership of different kinds of energy resources. The types of
ownership were wide-ranging, and the kinds of governance systems were
also diverse.
3. Research method
In this study, the Systematic Literature Review (SLR) method is used
to extract and analyse data from relevant works. SLR provides a rigorous
and transparent method of literature review, assisting in the generation
of robust and empirically derived answers to the focused research
questions [27,28]. In this section, we briefly discuss the different steps
that were taken to select the articles that were used in the study.
3.1. Search criteria, cases identification and selection processes
Here we describe the various stages through which energy commu-
nity cases were identified and selected. The section describes the inclu-
sion and exclusion criteria of these cases. Figure 2 and Table 2 are used to
illustrate the various steps and processes that were used in selecting the
cases. Cases that were considered are recent cases that were published
between the years 2010 and 2020. The involved stages are as follows:
1Case identification stage: The first stage of the review process in-
volves searching and gathering cases that are deemed relevant to the
subject matter, in this case, the proposed research questions. The
search is conducted from known databases of academic literature.
The databases consulted included Scopus, Web of Science, IEEE
Xplore, Google Scholar, Google Search, JSTOR, and Science Direct.
Additional information is also gleaned from other sources, such as
books and YouTube. Cases are selected from the search using the
selection criteria described below. Articles that are initially collected
from the search, which met the case selection criteria were sixty-eight
cases. At this stage of the process, six cases were excluded due to
duplication. The case selection criteria consisted of a set of keywords
that were used in combination as shown in Table 2. Each keyword
from column 1 is used in combination with all the keywords from
columns 2, column 3, and column 4. For instance:
Renewable energy –Sharing –Online –Community.
Renewable energy –Sharing –Online- Ecosystem.
Renewable energy –Sharing –Online –Marketplace.
Distributed energy –Collaborations–Portal –Platform.
Distributed generation –Coalition –Portal–Platform.
For most of these cases, our primary or preferred source of informa-
tion is the case's white paper, if it is available. This is because these
documents provided detailed information about the related cases.
Described below are the steps used for search criteria and case identifi-
cation. These steps are further illustrated using Figure 2 below.
Case selection stage. Using Table 2 as a reference, four key compo-
nents came together to determine a case's eligibility. These components
are:
Description of energy source: Under this item, the requirement for a case
to be selected is that the energy within the ecosystem must be from a
renewable source. The keywords, that were used included: renew-
able, distributed, sustainable, and green energy.
Types of interaction: The type of interaction between the actors in the
ecosystem is also of utmost importance. Our focus is on collaborative
interactions. However, keywords such as sharing, cooperation, coor-
dination, networks, partnership, joint, co-evolution, and coalition are
considered for the search.
Place of interaction: The place of interaction is expected to be
described as online or a portal.
Description of the ecosystem: Community, Platform, Portal, Market-
place, and Ecosystem are some of the keywords that are used to
describe the expected ecosystems.
At the case identification stage, a total number of sixty-eight (68)
potential cases are identified. Out of this number, six (6) cases are
excluded for duplication.
2. Case screening stage: An overview analysis of the sixty-two cases that
remained is conducted. At this stage, out-of-scope cases were identi-
fied and purged. A total of twelve (12) cases are screened out.
3. case eligibility stage: Eligible cases are cases that met the search
criteria, fit the scope of the study and were not duplicates. These cases
are retained for further analysis. At this stage, fifty (50) cases are
considered. Further screening, involved a thorough study of each case
to see if they meet the inclusion or exclusion criteria. At this stage of
the process, a total of sixteen (16) cases are excluded for not meeting
Table 1. The Feldheim community showing the various actors, their roles, relationships, and governance type [15].
Main
Actors/Key
stakeholders
Roles Governance structure Interaction with the power
grid
Roles of Actors Energy resources
ownership
Characteristics &relationships
between actors
a) Feldheim New
Energy Forum
Foundation
i. Project financiers
ii. Management body
iii. Education and
information
Community-owned
assets. These include:
1. Wind turbine
2. Photovoltaic
modules (PVs)
3. Biomass/Biogas
4. Combined heat and
power (CHP)
5. Lithium-ion battery
system
I. Characteristics of roles:
Public-private partnership
II. Relationship between roles:
Distributed system with
centralized management and
hierarchical governance
A. Governance type:
Non-profit self-governance
B. Structure:
Executive boards.
General assembly with
voting rights. One
member, one vote
Sends 90 % of the energy
produced in the community
to the grid.
The community uses only
10%
b) Municipality of
Treuenbrietzen
iv. Project financiers
v. Project initiation and
implementation
c) Residents of
Feldheim and
Treuenbrietzen
vi. Project financiers
vii. Centre of excellence
viii. Energy consumers
d) Feldheim
Energiequelle GmbH
ix. Project initiation and
implementation
x. Project
e) Farmers' Cooperative xi. Project financiers
xii. Landowners
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
5
the inclusion criteria. All cases that did not meet the inclusion criteria
are automatically excluded.
4. Case inclusion stage: In total, 34 cases are excluded, and 34 cases are
retained for the analysis.
4. Results and discussion
4.1. Overview of the selected cases
During the process of search and selection process for the cases, it was
found that the chosen cases came from many different types of busi-
nesses. The categories that are found include trading companies, finan-
cial/investment companies, solution developers, sole proprietorships,
limited liability companies, ecosystems, platforms, and finally non-profit
organizations (e.g., Prosume foundation). Although diverse, they all
share some common characteristics that are relevant to the study. For
instance, in almost all cases, the business entity brings together sellers
and buyers on a single platform, portal, ecosystem, or community to
facilitate the exchange of energy and related services that promote sus-
tainable energy generation, consumption, and trading. In almost all
cases, blockchain technology is used to facilitate secure and trustworthy
transactions. Besides the fact that all these cases meet the inclusion
criteria, their inclusion in the study also helps to widen the scope of the
study by providing diversity in the cases considered. In addition, the
cases were also found to be at different stages of development. Some
cases are in the conceptual stage, others are in the developmental/pro-
totype stages, and some are active/operational businesses.
In this section of the study, a detailed analysis of the 34 selected cases
is performed. In Table 3, a brief description of each case and its core
functions are tabulated.
4.2. Summary and cases comparison
Table 4 below provides a summary of the cases, detailing how they
compare to one another. Generally, all the cases can be categorized under
two generic groups, namely: (a) Platform as a Service (PaaS) and (b)
Software as a Service (SaaS). Under the PaaS category, we identified
several types of sub-services. These include (i) IoT integration services
(ii) renewable energy project financing services (iii) creating a market-
place for trading (iv) encouraging green behaviours (vi) compensation
schemes (vii) providing energy storage services (viii) facilitating the
integration of renewable energy sources into the grid (ix) offering
charging services for electric vehicles (x) offering load balancing services
and (xi) supporting the idea of a "smart city" The corresponding cases for
each sub-service and their total numbers are also shown in the table.
Table 2. A combination of keywords that were used to search for cases from the
search databases and other sources.
Column-1
Keywords
describing the
energy source
Column-2
Keywords describing
the type of
interaction
Column-3
Keywords
describing the
place of interaction
Columns-4
Keywords
describing the type
of ecosystem
Renewable energy
Distributed energy
Sustainable
energy
Green energy
Distributed
generation
Sharing
Collaboration
Cooperation
Coordination
Network
Partnership
Joint
Co-evolution
Coalition
Online
Portal
Community
Ecosystem
Platform
Portal
Market place
Figure 2. The flow of the systematic literature review process.
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
6
Table 3. A Summary of the selected cases for the study.
Index Cases Description Core functions
1 BittWatt A smart and flexible system that makes the most of all energy sources
and enables users to exceed their customer's needs in a balanced and
financially efficient ecosystem that learns and evolves [29].
1. To provide blockchain-enabled peer-to-peer energy trading platforms
and services.
2. A new marketplace for electricity balancing and trading
2 Electrify Network A technology start-up that aims to bring the process of investing in
renewable energy plants, smart micro-grid deployment, transactive
energy marketplaces, and self-sustained smart city development to a
grass-root level [30].
1. To build renewable power systems and produce exclusively green
energy that will be sold to utility providers and government-owned
entities.
2. To build a dynamic platform for peer-to-peer (P2P) energy trading
using blockchain.
3. Contribute to the building of self-sustaining smart city pilot projects.
4. To provide venture capital for renewable energy projects.
3 Electrify.Asia An ecosystem that allows consumers to buy their energy directly from
peers or electricity retailers using the blockchain and smart contracts
[31].
1. P2P energy trading platform.
2. Promote the use of "synergy" and "marketplace 2.0," which are web and
mobile application interfaces that let people make smart contracts with
their energy providers.
4 ElectronConnect Provides marketplace infrastructure, in the form of a multi-market
launch and hosting facility, that enables network operators, distributed
energy resource operators, and others to interact and unlock market-
based efficiencies [32].
1. A service provider that provides a marketplace or platform as a service
5 EnergiMine A platform that matches customers with small generators.
Aims at creating a global ecosystem where users are rewarded with
tokens for energy-efficient behaviours. For example, if a commuter is
encouraged to use public transport by the local city authorities, they
could be rewarded by being given an ETK token [33].
1. A service provider with a platform that achieves two objectives:
P2P marketplace for energy trading over the blockchain.
Incentivization &reward scheme for energy-saving behaviours.
6 Energo Labs Start-up with the intent of creating a P2P platform for a distributed
energy system using blockchain technology with a particular focus on
microgrids [34].
1. The company provides a platform that integrates blockchain technology
into the energy sector to establish Decentralized Autonomous Energy
(DAE) communities, enabling enterprises to convert energy into digital
assets and use them in P2P, machine-to-machine, electric vehicle-to-
virtual grid, green card trading, carbon trading, and virtual net electricity
billing forms.
7 Energy Web Foundation A low-carbon, customer-centric electricity system that enables any
energy asset owned by any customer to participate in an energy market
[35].
1. Peer-to-peer energy trading service provider.
8 EnergyNet A secure and cloud-based software-as-a-service platform that solves the
most crucial challenges of Transactive Energy. Thus compensation for
providing distributed energy services via the distributed electric grid
[36].
1. To provide a blockchain-enabled peer-to-peer energy trading platform.
9 Enosi Foundation The Enosi Platform permits energy providers to offer less expensive
community-based energy programs. Using the Enosi Protocol,
households with solar energy systems can become prosumers and sell
excess energy to buyers of their choosing at prices they determine. They
will be able to engage in peer-to-peer trading and community-owned
generation, as well as take advantage of offers from innovative new
energy retailers that benefit from the Enosi Platform's lower cost
structure.
[37].
1. Leverages smart meter technology that digitizes energy data, and
combines this data with recent advances in distributed ledger
technology to deliver:
A more efficient and secure transactive services platform.
Access to competition throughout the value chain
The ability for distributed renewable generation to be accessed
through community energy schemes and markets
Market-led adoption of decentralized energy solutions
10 EtainPower A platform that creates a compelling new channel for global investors to
access and invest in renewable energy projects [38].
1. To provide renewable energy financing and a trading platform that is
empowered by both blockchain and AI technologies.
11 Greeneum Blockchain-powered, sustainable, scalable, and secure energy and data
trading platform [39].
1. Provide Software as a Service (SaaS) for grid operators and utilities
2. Premium services (obtain financial and performance reports,
maintenance operation reports, and actionable insights that can
potentially lead to higher profitability) for solar and green energy
producers
3. Provide smart contract services
4. Advertisements: The platform will attract a high volume of repeat
users, which will allow companies to advertise their products and
services for a fee.
12 GridþThe Grid þagent leverages AI to understand and predict consumers'
energy usage habits. With real-time pricing data, the agent makes smart
decisions on behalf of the purchaser of energy in the most cost-effective
way with zero effort from users [40].
1. Develop cutting-edge secure hardware and software to enable the use
of cryptocurrency.
2. Management of digital assets
3. Trading in energy.
13 GridX This provides a financial operating system to enable utilities, retail
energy suppliers, distributed energy resource providers, energy service
providers, and their customers to operate and participate in
decentralized energy markets [41].
1. Enable utilities, retail energy suppliers, third-party energy services
providers, and their customers to operate and participate in decen-
tralized energy economies.
14 Hive Power A turnkey solution to create and manage local energy communities on
the blockchain called the “Hives”, provides economic optimization for
participants. A Hive is a distributed energy market platform regulated
through smart contracts where every user can buy and sell electrical
energy [42].
1. P2P energy trading platform service provider.
15 Jouliette (Spectral) A blockchain-based platform that enables individuals and communities
to manage and share renewable energy produced locally [43].
1. Selling renewable energy.
2. Purchasing renewable energy.
(continued on next page)
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
7
Table 3 (continued )
Index Cases Description Core functions
16 KWHCoin A blockchain-based solution for a platform that makes it easy and cheap
to add renewable energy and distributed energy resources to the grid
[44].
1. A digital currency that uses a blockchain to turn information about
distributed energy resources into digital tokens.
17 Lition It is a P2P energy trading platform that connects renewable energy
producers with smart consumers directly [45].
1. Aims to make green electricity simple and flexible by directly
connecting producers and customers.
18 LO3 Energy/Brooklyn
Microgrid
A blockchain-based platform that enables decentralized business
models and innovative technologies related to energy [46].
1. A blockchain-based platform that enables decentralized business
models and innovative technologies related to energy.
2. They operate the Exergy System.
19 NAD Grid A P2P energy exchange platform that is backed by advanced blockchain
technology. [47].
1. A decentralized P2P electricity trading platform.
2. It enables buyers and sellers to trade electricity using the Eden token
(cryptocurrency).
20 Peer 2 Peer Energy
Protocol (P2PEP)
A distributed energy trading application that lets both small and large
clean energy producers and consumers connect over the blockchain
[48].
1. A blockchain-enabled P2P energy trading service provider.
21 Power Ledger A trustful, transparent, and interoperable energy trading platform that
supports a growing number of energy applications [49].
1. A platform that can provide real-time metering data, collection of big
data, the right to access and dispatch assets, rapid transaction settle-
ment, and network load balancing. This is applied in areas such as:
P2P Trading.
Neo-retailing.
Microgrid/embedded network.
Wholesale market settlement.
Autonomous asset (AA) management.
-Distributed market management:
Electric vehicles charging.
Carbon trading.
Transmission exchange.
22 Prosume Foundation A Swiss foundation and non-profit organization with a vision of
empowering communities to exchange energy assets in a P2P fashion
using a blockchain-based online market [50].
1. Aims to develop a platform that will be used by utility companies, grid
operators, system integrators, and communities to easily build local
ecosystems and online marketplaces.
23 Pylon Network A blockchain network designed to create an open renewable energy
exchange community that will provide signals and financial incentives
to the energy markets [51].
1. To facilitate the growth of digital energy services, such as the
transformation of the energy market to a consumer-centric and energy-
as-a-service model, in the era of digitalization.
24 Share &Charge A marketplace/community that provides solutions for electric vehicle
charging. It enables simple, secure, and smart charging services based
on the Open Charging Network (OCN) [52].
1. A B2B service provider that provides simple, secure, and smart
charging services based on the OCN.
25 Solar Bankers Aims to develop a global network of self-sufficient, decentralized
renewable energy communities and, through digitization, which is
enabled by the Solar Bankers coin, which may transform electricity into
a globally exchangeable commodity [53].
1. An international renewable energy company that is focused on the
development of a global network of self-sufficient, decentralized,
renewable energy communities.
26 Solar IoT A P2P blockchain energy grid, that allows individuals to buy and sell
energy to others in a fully open marketplace on the Ethereum
Blockchain, where prices are low and energy is abundant [54].
1. Financing of solar projects.
2. P2P energy trading service provider.
27 SonnenCommunity A community where members (households) can store and use their self-
generated energy using Sonnen's intelligent energy storage system, the
SonnenBatterie. [55].
1. Develop and promote the use of the “sonnenBatterie”, an intelligent
energy storage system.
2. Communalization of energy storage.
3. Community-based energy sharing.
4. Provide e-mobility services.
28 Sun Exchange Sun Exchange enables people to locate their solar panels in the optimal
places on the planet for the good of the owners, and the energy users, as
well as offering an indirect benefit to the entire world population [56].
1. To provide a peer-to-peer solar leasing platform.
29 SunContract A platform for trading energy that will create the SunContract energy
pool and make it easier for people to buy and sell electricity directly
from each other using blockchain technology [57].
1. A service provider that uses the SunContract pool for the sale and
purchase of renewable energy.
30 Tarus Project Using electric vehicles (EV) as a mobile power transmission network
[58].
1. Blockchain-enabled peer-to-peer energy trading and EV charging
services.
31 Toomuch.energy Toomuch.energy transforms neighbourhoods into fully digital energy
communities with a range of P2P services and market choices [59].
1. To provide a blockchain-enabled peer-to-peer energy trading platform.
32 Verv VLUX Verv combines innovations in machine learning, blockchain, AI, IoT,
and energy storage to help develop peer-to-peer energy trading using
the Verv Trading Platform (VTP). The ecosystem has been designed to
facilitate trading at the grid edge [60].
1. Peer-to-peer energy trading service provider.
2. Deployment of IoT devices such as the VHH to manage household
energy consumption and data collection.
33 Volt Market Volt Markets disintermediate s traditional energy markets and enables
monitoring, managing, and trading of energy and energy attributes in a
P2P market on the Ethereum blockchain [61].
1. Providing a platform which is driven by smart contracts on the
Ethereum blockchain. Volt Market says it will make a system that is
more secure, clear, and efficient than the ones that are already in place
34 WePower WePower is a blockchain-based green energy financing and trading
platform. It connects energy buyers (households, investors, or market
makers) directly with green energy producers to facilitate the upfront
purchase of energy at below-market prices. It uses energy tokenization
to standardize and simplify the currently existing energy investment
ecosystem. It is claimed to provide access to live trade in renewable
energy globally for everyone [62].
1. Financing green energy projects.
2. P2P energy trading service provider.
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
8
Similarly, under the category of SaaS, two key services are found. These
are (i) software to provide reporting services (financial, performance,
and maintenance operation reports). Other services found include ad-
vertisements that could generate additional income for the platform/
ecosystem. (ii) the provision of software agents for decision-making
services.
4.3. Addressing RQ-1: how can the interaction between members of the
selected energy ecosystems be described?
The context of question “RQ-1”is to see if the interaction between the
actors in these ecosystems can be characterized as either networking,
coordination, cooperation, or collaboration. The outcome of this research
question is summarized in Table 5. To help answer this question, we
studied each case to determine the presence of some key features that are
used to describe collaboration. Ten key features are used. For a case to be
considered as engaging in collaboration all of the features of collabora-
tion must be visible in the case. In cases where these features are partially
visible, the cases were further analyzed to determine whether they could
fit the description of networking, coordination, or cooperation. For this
purpose, the following features are used:
1. Communication and information exchange for mutual benefit: Is there
evidence of communication for mutual benefit?
2. Coordinated activities: Are the activities of these ecosystems
coordinated?
3. Joint planning and implementation: Is there evidence of joint plan-
ning and joint implementation?
4. A jointly defined common plan: Is there evidence of a common plan
that is jointly defined?
5. Mutual engagement for joint creation: Is there evidence of mutual
engagement resulting in the joint creation of a product?
6. Sharing risks, resources, responsibilities, and rewards: Is there evi-
dence of risk, resources, and rewards sharing?
7. Having an image of joint identity: Do members possess or assume a
joint or collective identity?
8. Having common or compatible goals: Is there a common goal (or
compatible goals) that is jointly agreed upon?
9. Value co-creation: Do members create value together?
10. Division of labour: Is there a division of labour?
Yes: means there is sufficient evidence to conclude.
Partial: means there is some evidence, but not concrete or suf-
ficient to conclude.
No: means there is no evidence.
Summary of review outcome for RQ-1. Based on the conducted
analysis, the following observations can be made:
1Communication and information exchange for mutual benefit.In all
cases considered, there is some form of information exchange across
the platforms for the benefit of participants. For instance, considering
Power Ledger, the platform facilitates information sharing that en-
ables participants to identify and select different clean energy sources
according to their desired preferences. In addition, members have
access to information that enables them to select and trade with their
neighbours. Additional information that is shared for the benefitof
participants involves an incentive program dubbed the "Green Energy
Loyalty Rewards Program." Although there is evidence of information
exchange, the objective of exchanging information is not aimed at
solving a common problem or creating some value together. In other
words, there is no common goal or agreed objectives, to which this
communication is intended to contribute. Since the study found some
level of communication and information exchange as well as some
level of benefits, even though they are not mutual, we can say that the
level of communication and information exchange is "partial" in
almost all cases except SonnenCommunity. In this community, the
households are installed with Sonnon intelligent batteries, which are
managed locally using the Sonnon intelligent energy management
software. This software collects information about the household's
energy generation and consumption. This information is shared with
the central Sonnon VPP software using the Sonnen digital networking
platform as the communication channel. The VPP software collects
similar information from all households in the community and uses
this information to make decisions related to the provision of VPP
services. The goal of sharing this information is common to all
households, thus facilitating decision-making towards the provision
of VPP services to the grid, which is a common goal for the
community.
2Coordinated activities.In all cases considered, there is some level of
coordination between service providers and participants. There is
also evidence of coordination among the participants. However, co-
ordination among members of these ecosystems is not based on
mutual or clearly defined common objectives or goals. Service pro-
viders often facilitate this coordination. From the perspective of
collaborative networks, coordination is defined as the act of working
together harmoniously to achieve a common goal. However, the
intent behind the type of coordination observed in these cases is not
aimed at a common or agreed-upon goal. The coordination found did
not involve the alignment or altering of individual activities so that,
mutually, more efficient results could be achieved collectively. The
types of coordination found in these cases can best be described as
administrative or managerial roles that are played by third-party
Table 4. A summary and case comparison.
Types of
Services
Nature of service Cases Total
number of
cases
Platform as
a Service
Facilitating IoT
integration
Verv VLUX 1
Financing of
renewable energy
projects
GridX, Solar Bankers, Solar IoT
Sun Exchange, WePower,
EtainPower, Electrify Network
7
Facilitating a
marketplace for
trading
Electrify.Asia, ElectronConnect,
EnergiMine, Enosi Foundation,
EtainPower, Lition, LO3 Energy/
Brooklyn Microgrid, NAD Grid,
Peer 2 Peer Energy Protocol
(P2PEP), Power Ledger,
Prosume Foundation, Pylon
Network, SunContract,
Toomuch.energy, Verv VLUX
Volt Market
18
Promoting green
behaviours
Energo Labs, Power Ledger 2
Facilitating
compensations
EnergyNet 1
Facilitating energy
storage
SonnenCommunity 1
Facilitating
integration of
renewable energy in
the grid
KWHCoin 1
Facilitating electric
vehicle charging
services
Tarus Project 1
Facilitating load
balancing
BittWatt, Power Ledger 2
Facilitating smart city
concepts
Electrify Network 1
Facilitating the
management of
energy asset and data
Energy Web Foundation,
Greeneum, Power Ledger, Volt
Market, Power Ledger
5
Software as
a Service
Reporting and
Advertisement
Greeneum 1
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
9
Table 5. Analysis of cases to determine the feature of Collaboration or Cooperation (RQ-1).
Index Cases Communication and
information exchange
for mutual benefit
coordinated
activities
Joint planning and
implementation
Common
plan jointly
defined
Mutual
engagement for
Joint creation
Sharing risk,
resources,
responsibilities, and
rewards
Image of
joint
identity
Common
goals
Value co-
creation
Division
of labour
Conclusion/
Remarks
1 BittWatt Partial Partial No No No Partial Yes Yes No Yes Cooperation
2 Electrify Network Partial Partial No No No Partial Yes Yes No Yes Cooperation
3 Electrify.Asia Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
4 ElectronConnect Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
5 EnergiMine Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
6 Energo Labs Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
7 Energy Web
Foundation
Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
8 EnergyNet Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
9 Enosi Foundation Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
10 EtainPower Partial Partial No No No Partial Yes Yes No Yes Cooperation
11 Greeneum Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
12 GridþPartial Partial No No Partial Partial Yes Yes No Yes Cooperation
13 GridX Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
14 Hive Power Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
15 Jouliette (Spectral) Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
16 KWHCoin Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
17 Lition Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
18 LO3 Energy/Brooklyn
Microgrid
Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
19 NAD Grid Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
20 Peer 2 Peer Energy
Protocol (P2PEP)
Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
21 Power Ledger Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
22 Prosume Foundation Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
23 Pylon Network Partial Partial No No Partial Partial Yes Yes Aggregated
value
Yes Cooperation
24 Share &Charge Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
25 Solar Bankers Partial Partial No - Partial Partial Yes Yes Yes
26 Solar IoT Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
27 SonnenCommunity Yes Yes Yes, using a self-
learning software
platform
Yes Yes, using a self-
learning software
platform
Yes Yes Yes Yes Yes Collaboration
28 Sun Exchange Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
29 SunContract Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
30 Tarus Project Partial Partial No No No Partial Yes Yes No Yes Cooperation
31 Toomuch.energy Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
32 Verv VLUX Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
33 Volt Market Partial Partial No No Partial Partial Yes Yes No Yes Cooperation
34 WePower Partial Partial No No Partial Partial Yes Yes Aggregated
value
Yes Cooperation
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
10
entities or service providers. From our observation, activities that are
carried out in these ecosystems are not coordinated with collabora-
tion in mind. Thus, it might be fair to give a "partial" status to this
feature in all the cases that are analyzed, except for the Sonnen-
Community, which has clear evidence of coordinated activities that
tend toward working together.
3Common plan, joint planning, and implementation.In all but one of
the cases considered, there is no evidence of a common plan as well as
joint planning and implementation designed by mutual consent or
agreement among the actors in these ecosystems. However, as an
exception, joint planning and implementation can be seen only in the
SonnenCommunity. For this ecosystem, joint planning and imple-
mentation are achieved using a self-learning software platform [63].
Planning and implementation, in almost all cases, are performed in a
quasi-independent manner, without the involvement of other par-
ticipants. Individuals such as prosumers, investors, and consumers
can engage in their planning and implementation activities without
consulting other actors in the ecosystem. Therefore, the status of this
feature for all the other cases can be described as “No.”
4Mutual engagement in joint creation.Mutual engagement in joint
creation means that parties come together to engage one another to
jointly create a product, or a service, or increase the value of a product
or service. In the considered cases, there is evidence of mutual
engagement in most cases to help achieve the objectives of the various
actors. However, in the case of the SonnenCommunity, it is
completely different. In this particular case, the community uses a
self-learning software platform to engage members in a way that al-
lows the community to act as a VPP, selling renewable energy to the
grid to create value. In this particular case, mutual engagement is
visible, although through a software application. In most cases, the
evidence is partially visible in the sense that value creation is
observed. However, the process of creating value is not born out of
any form of mutual engagement. Nevertheless, the types of products
and services that are found can be the result of individual efforts that
produce the results, without any underlying mutual engagement. It
can therefore be inferred that value, in most cases, is created in a
quasi-independent manner, without a common plan, agreement, or
purpose. Thus, we consider that in most of these cases, mutual
engagement for joint creation is "partial".
5Sharing risks, resources, responsibilities, and rewards.There is ev-
idence of partial sharing of resources, risks, and rewards. For instance,
in the case of WePower, small energy producers who use WePower
services and who cannot reach the 1 MWh certificate, which is the
minimum requirement to trade in the energy market, are grouped as a
single entity to sell their energy to the market. The constituents of this
entity share the benefits proportionally among themselves. However,
no explicit mention is made of sharing of risks and responsibilities.
Similarly, the Pylon Network offers tools to simplify shared owner-
ship processes through transparent, safe, and real-time monitoring of
assets. This includes the distribution of profits or costs associated with
the co-owned assets. Details about risk sharing are not explicitly
mentioned in these cases. Moreover, it is observed that there is a
common goal, namely, to aggregate energy and sells it to the grid.
However, this goal does not result from a mutual plan based on a
common objective with clearly defined roles or responsibilities for
each member. Although the sharing of rewards and resources is
explicitly mentioned in the Pylon Networks, the sharing of risks and
responsibility is not mentioned. Because of this, we consider that
sharing risks, resources, rewards, and responsibilities in these eco-
systems is usually "partial."
6Having an image of collective identity.Evidence of the notion of joint
image or identity is found in almost all the cases considered. Although
there is no explicit mention of a joint or collective identity, we
acknowledge that all these platforms have some identity. At the time
of joining the community, members are conversant with the names
and identities of these ecosystems and nevertheless chose to join
them. Since members signed up for these platforms knowing what
they are, what they stand for and how they worked, our opinion is
that identity is implied. Therefore, in all cases considered, this feature
is considered present.
7Having common or compatible goals.It is further observed in almost
all the studied cases that sellers, buyers, investors, and service pro-
viders have “quasi-common”goals. These goals are found in two
layers. The first observed layer is a sustainability goal. This goal is
common among sellers whose primary objective is to generate,
consume, and trade excess renewable energy, although this goal is not
jointly conceived. Buyers, in most cases, also have a similar sustain-
ability goal, which is to purchase and consume energy from renew-
able sources rather than fossil fuel-based sources. The goal of third-
party actors, in the same sense, is to invest in renewable energy by
creating a marketplace where sustainable energy and related services
can be exchanged. These activities of third-party actors will conse-
quently promote "sustainable consumption," hence an implicit goal.
The second layer goal is an economic one. The goal of sellers, in this
sense, is to maximize revenue from their sales. The goal of buyers, on
the other hand, is to minimize the cost of their purchases. The goal of
third-party actors is to maximize revenue and minimize costs. In
addition, it can also be argued that prospective actors in these eco-
systems may often have prior knowledge of the aims, objectives, and
possibly goals of these ecosystems before joining. Accepting the terms
and conditions at the time of joining may constitute an implied
acceptance and alignment of the goals. In a hypothetical sense, all
these goals can be considered compatible, although implicit or tacit in
their design. Since the focus of this aspect of the study is centred on
identifying “common goals,”it may be reasonable to infer the exis-
tence of some form of common “sustainability”and “economic”goals,
although it can be argued that these goals were not jointly defined.
Therefore, it may be reasonable to generalize the conclusion about
“common goals”as being “present.”
8Value co-creation.This notion implies the involvement of the
customer and local stakeholders in the process of collectively creating
new products or services [7]. In the context of collaboration, it is
usually not easy to clearly identify the amount of "added value" that
each member has contributed. Subsequently, it is not easy to devise
general schemes to distribute revenues and liabilities [7]. There are
other complementary factors that influence the behaviour of a
network and thus its ability to generate value. These factors include
the scheme of incentives, trust relationships and management pro-
cesses, ethical code, collaboration culture, contracts, and collabora-
tion agreements. These are key elements in a value co-creation
environment. In almost all cases studied, these key value-creation
elements or factors are not explicitly discussed. For instance, in the
“Prosume”ecosystem, it is mentioned that “consumers will choose
their energy provider according to their needs, possibilities, and
ethics”. Ethics, as mentioned in this sense, is not about value
co-creation. Also, an ecosystem like “EnergiMine”mentioned in-
centives in its white paper, but this relates to behaviour change and
not necessarily value creation. Although many of the factors that in-
fluence the behaviour of a network towards value creation, as stated
in [7], are mentioned sporadically in several cases, they have no
special connotation to value creation. Three exceptional cases were
found. These are the “Pylon Network”SonnenCommunity and
“WePower”. These cases make explicit mention of aggregated value,
which can be synonymous with value co-creation. Except for these
three cases, all other cases can be considered as not co-creating value.
9Division of labour.Division of labour, according to [64], is the pro-
cess of dividing a task or job into smaller, interconnected sub-tasks,
thereby generating efficiency gains due to the positive effects of
specialization. The available evidence from the studied cases suggests
that each member plays specific and specialized roles to achieve in-
dividual objectives. For instance, prosumers play their respective
roles as producers, while consumers also play their respective roles as
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
11
consumers. Investors and service providers also play their respective
roles accordingly. Although these actors are found to be playing their
natural roles as independent business entities, it can further be argued
that these roles are “implicit roles”in the sense that each actor is
likely to have foreknowledge of their expected role before joining a
community. Furthermore, these roles are highly specialized, and the
ecosystem is able to achieve its objectives by aggregating the out-
comes of each actor's role. As a result, it may be commendable to infer
that there are some forms of “division of labour”in these cases.
However, they are more implicit and implied. The conclusion for this
element is therefore in the affirmative.
4.4. Addressing RQ-2: what technological enablers and trends underlie the
establishment, operation, and service provision of these ecosystems?
The outcome of this research question is summarized in Table 6.To
help answer RQ-2, we studied each case to identify the key technologies
being deployed in these ecosystems. Nine key technologies are observed,
as briefly explained below:
Artificial Intelligence/Machine Learning.This element of the
study focused on how artificial intelligence and machine learning tech-
nologies are being used in the studied energy ecosystems. Two sub-
sections are considered under this section. These are:
1. The integration of smart devices, IoT devices, smart meters, as
well as intelligent agents.
Smart devices, IoT devices and smart meters.
Under this item, we identified 29 out of 34 cases that integrate
smart meters or IoT devices into their operation. Some examples
include cases such as Electrify. Asia, which uses the Powerpod in its
networks. Powerpod is simply an IoT gateway for reading and
relaying real-time energy data to a central management system of
the Electrify. Asia network, allowing an algorithm to match and
process settlements. A second example is the Pylon network, which
relies on a generic smart meter. The device is called the Klenergy
METRON, and is described by the network as any digital meter,
sub-meter, or electric vehicle charger that can record energy data
on the Pylon Network's blockchain. A third example is the gridbox
from gridx, which serves as a gateway to its Xenon platform, which
is the interface to all connected Distributed Energy Resources
(DERs) and is used for data collection and management of DERs.
The Verv vlux network also introduced its core IoT product called
the Verv Home Hub, which is a patented, self-installed energy hub
that samples a home's electricity consumption approximately 5
million times faster than a smart meter. It uses machine learning
algorithms to derive a real-time profile for key household appli-
ances, providing homeowners with a view of their electrical ap-
pliances' current status [60].
Intelligent Agents.
As an example of the use of software agents, Energy Web Foun-
dation - Decentralized Autonomous Area Agent (D3A) is an intel-
ligent software agent that performs grid communication and
control functions for physical assets. D3A allows any energy-
consuming or energy-producing device to interact with other de-
vices in a trustless blockchain environment, helping to optimize
operational decisions locally and based on user preferences and
system conditions [65]. Another intelligent agent application is
found in the case of Gridþ. In this example, whenever a customer
signs up for Gridþ, he will purchase a Smart Agent and buy BOLT
(a cryptocurrency) from the Grid þweb console. The Grid þsmart
agent, once registered, will allow customers to transfer BOLT to-
kens to the Smart Agent to pay for electricity in real time. An
automatic payment option can be set up so that it can be refilled
automatically if a Smart Agent runs out of BOLT. The Smart Agent
will make digital signatures from a secure hardware enclave and
act autonomously while still registered with Gridþand owned by
the customer [66].
2.Blockchain Technology.
In [68], a blockchain is described as a distributed and immutable ledger
that facilitates the recording of transactions and the tracking of assets
within a business network. An asset can be either tangible (such as a
house, automobile, money, or land) or intangible (intellectual property,
patents, copyrights, branding etc.). In a blockchain network, almost
anything of value may be recorded and sold, lowering risk and expense
for all involved. In the context of renewable energy communities,
blockchain can give consumers greater control over their energy sources.
Additionally, an immutable ledger provides secure and real-time updates
of energy usage data and monitors trading between sellers and buyers.
The transparency of public blockchains further reduces the chances of
monetary or data exploitation [69]. Concerning the type of distributed
ledger technology that is mainly used, it is found that all 34 cases studied
used the public blockchain except one (the Enosi platform) that used a
private blockchain. In this case, the private blockchain allows most
computations to be validated by it rather than by the public chain.
Another case (Energo Labs) also uses the Qtum blockchain. The use of
blockchain technology in these emerging energy ecosystems is quite
extensive and the following facets are worth mentioning:
Distributed Applications (DApps).
Ethereum, launched in 2015, is an open-source, blockchain-based
decentralized software platform that can simultaneously integrate
a cryptocurrency. Ethereum helps deploy Smart Contracts and
DApps to be developed and executed without fraud, control, or
interference from third parties. Ethereum offers both a platform
and a programming language that runs on a blockchain and allows
developers to build and publish distributed applications. 29 out of
the 34 studied cases use the Ethereum platform to deploy their
distributed applications. The use of other blockchain variants, such
as Hyperledger Fabric, Qtum, and Skyledger blockchain, is also
found in cases such as Lition, Energo Labs, and solar bankers,
respectively.
Trading Tokens (cryptocurrency).
Of the 34 cases that are considered, 29 use cryptocurrencies as
tokens for trade. These cryptocurrencies differ from ecosystem to
ecosystem, and their values also vary. They are used as the main
medium of exchange in these ecosystems instead of fiat currency in
the real world. Many cryptocurrencies are supported on decen-
tralized networks based on blockchain technology. One defining
feature of cryptocurrencies is that they are generally not issued by
any central authority, such as banks, making them theoretically
immune to government interference or manipulation. For instance,
in some cases, like "WePower," cryptocurrencies are used to
tokenize energy. Tokenization of energy is a contracting scheme
that is established between an energy producer and an energy
buyer.
Smart Contracts.
Smart contracts (SC) are simply programs stored on a blockchain
that run when predetermined conditions are met. SCs are computer
protocols that facilitate, verify, or enforce the execution of a con-
tract, thus making the need for a contract clause unnecessary. SCs
often imitate the logic of contract clauses. SCs can support the
exchange of money, property, shares, or anything of value in a
transparent and conflict-free manner, avoiding the services of a
middleman. Normally, a process would require payment to a
middleman, a government agency, a bank, a lawyer, or a notary,
and then a processing time before receiving goods or services.
However, with smart contract technology, all these processes can
be automated. In the studied energy ecosystems, information about
transactions and arbitrations between sellers and buyers is
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
12
Table 6. Summary of technological enablers for energy ecosystems.
Index Cases Enabling Technology References
Artificial Intelligence/Machine
Learning
Blockchain Technology ICT Architecture
IoT devices/
Smart meters
Intelligent
agents
Distributed
Application
(DApps)
Type of trading tokens/
cryptocurrency
Distributed ledger
technology
Smart
contracts
Blockchain as a
service platform
(BaaS)
Cloud-based
platform
P2P Network
topology
1 BittWatt Yes No Ethereum BWT Public Blockchain Yes Yes No Yes [29]
2 Electrify Network Yes No Ethereum Eden Token Public Blockchain Yes Yes Yes Ye [30]
3 Electrify.Asia Powerpod No Ethereum ELEC Token Public Blockchain Yes No No Yes [31]
4 ElectronConnect Yes No Ethereum - Public Blockchain Yes Yes No Yes [32]
5 EnergiMine Yes No Ethereum ETK Public Blockchain Yes Yes No Yes [33]
6 Energo Labs Yes [EME 1.0] No Qtum blockchain Qtum, Qtum blockchain Yes Yes No Yes [34]
7 Energy Web Foundation No Yes (D3A) Ethereum Tobalaba Public Blockchain Yes Yes Yes Yes [35,65]
8 EnergyNet Yes No Ethereum Fiat Currency, any
crypto
Public Blockchain Yes Yes Yes Yes [36]
9 Enosi Foundation Yes No Ethereum Joul Public Blockchain
Private
Blockchain
Yes Yes No Yes [37,67]
10 EtainPower Yes No Ethereum EPR Token Public Blockchain Yes Yes Yes [38]
11 Greeneum No No Ethereum Green tokens Public Blockchain Yes Yes No Yes [39]
12 GridþYes Yes: Grid þ
Smart agent
Ethereum BOLT Public Blockchain Yes Yes No Future
implementation
[40]
13 GridX gridBox Ethereum Public Blockchain Yes [41]
14 Hive Power Yes No Ethereum HVT Public Blockchain Yes Yes No Yes [42]
15 Jouliette (Spectral) Yes No Ethereum Jouliette Public Blockchain Yes - No Yes [43]
16 KWHCoin Yes No - KWHCoin Public Blockchain Yes Yes No No [44]
17 Lition Yes No Hyperledger Fabric,
Ethereum
Lition tokens Public Blockchain Yes Yes no Yes [45]
18 LO3 Energy/Brooklyn
Microgrid
Yes No Ethereum XRG Public Blockchain Yes Yes No Yes [46]
19 NAD Grid No Ethereum Eden Token Public Blockchain Yes Yes - Yes [47]
20 Peer 2 Peer Energy
Protocol (P2PEP)
Yes PED Token Public Blockchain Yes Yes No Yes [48]
21 Power Ledger No No Ethereum POWR Tokens &
Sparkz
Public Blockchain Yes Yes No Yes [49]
22 Prosume Foundation Yes No Ethereum PEF Token Public Blockchain Yes Yes No Yes [50]
23 Pylon Network Klenergy
Metron
No Ethereum Pylon-Coin Public Blockchain Yes Yes No Yes [51]
24 Share &Charge Yes No Ethereum No Public Blockchain Yes Yes No Yes [52]
25 Solar Bankers Yes No SkyLedger Skycoin Public Blockchain Yes Yes No Yes [53]
26 Solar IoT Yes No Ethereum SolCredit Public Blockchain Yes Yes No Yes [54]
27 SonnenCommunity Yes Self-learning
software
Not mentioned N/A Not mentioned N/A N/A Not
mentioned
Yes [55]
28 Sun Exchange Yes No Ethereum SUNEX Public Blockchain Yes Yes No No [45]
29 SunContract No No Ethereum SNC Public Blockchain Yes Yes No Yes [57]
30 Tarus Project Yes No Ethereum TORUS Public Blockchain Yes Yes No Yes [58]
31 Toomuch.energy Yes No Ethereum - Public Blockchain Yes Yes No Yes [59]
(continued on next page)
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
13
achieved using smart contracts. All the cases considered use this
technology.
3. Other ICT Software Architectures.
Cloud-based platforms.
Three cases are found to use cloud-based platforms. These are (a)
Energy Web Foundation, (b) Verv VLUX, and (c) Electrify Network.
For instance, Verv VLUX uses a decentralized cloud storage service
to host the platform and related applications. Furthermore, the Verv
Household Hub is designed to connect to the cloud via a Wi-Fi
network and provide users with a central hub to control other
cloud-connected household smart appliances [60]. Again, consid-
ering the Electrify Network, the platform sought to combine the
reliability and robustness of the microgrids with intelligent,
multi-tasking smart meters. This is made easier by software that
runs in the cloud and makes all transactions and exchanges smooth,
safe, and easy [30].
P2P network technology.
In all the cases considered, the platforms utilize the P2P network
topology except in two cases, which are KWHCoin and Sun
Exchange.
Blockchain as a Service Platform (BaaS).
BaaS is a relatively new development in the growing field of block-
chain technology. For BaaS, a third-party service provider is
responsible for setting up all the necessary blockchain technology
and corresponding infrastructure for a fee. Once created, the pro-
vider continues to handle the complex back-end operations on behalf
of the client. In almost all cases considered, third-party service pro-
viders are responsible for the blockchain infrastructure as a service
offered to energy sellers and buyers.
4.5. Addressing RQ-3: how do the characteristics and functions of virtual
power plants (VPPs) compare to renewable energy communities/
ecosystems?
A VPP, according to [5], is a virtual entity with numerous stake-
holders and decentralized multi-site heterogeneous technologies
composed of dispatchable and non-dispatchable distributed energy
sources and energy storage systems as well as electric cars and control-
lable loads. The use of information and communication technologies
enables VPPs to act as the equivalent of a single power plant with the
ability to manage and coordinate its operations, ensuring power and
information flow among its stakeholders to reduce generation costs,
maximize profits, and improve participation in demand response pro-
grams as well as trade within electricity markets. By juxtaposing the VPP
concepts with RECs it can be found that both ecosystems are similar in a
way. For instance, prosumers in RECs can aggregate their surplus or
unused energy from the community and sell it to the grid. This enables
RECs to also behave like VPPs.
VPPs can therefore be described as having the following features:
1. Is composed of multiple stakeholders/actors.
2. Is comprised of decentralized multi-site heterogeneous technol-
ogy/systems.
3. Is formed by aggregating distributed energy resources.
4. Is supported by ICT.
5. Is characterized by the simultaneous flow of information and
energy.
6. Can function like a single power plant
In this section of the study, the objective is to establish or ascertain
how each of the 34 cases compares to a VPP. The focus here is on their
characteristics and functions. As described above, items one (1) to five
(5) represent the characteristics of a VPP while item six (6) focuses on its
functions. To help explore these cases, the characteristics of the VPP are
described above, thus, items 1–5 are framed into sub-research questions.
Table 6 (continued )
Index Cases Enabling Technology References
Artificial Intelligence/Machine
Learning
Blockchain Technology ICT Architecture
IoT devices/
Smart meters
Intelligent
agents
Distributed
Application
(DApps)
Type of trading tokens/
cryptocurrency
Distributed ledger
technology
Smart
contracts
Blockchain as a
service platform
(BaaS)
Cloud-based
platform
P2P Network
topology
32 Verv VLUX Yes No Ethereum VLUX Token Public Blockchain Yes Yes Yes Yes [60]
33 Volt Market Yes No Ethereum RECs Public Blockchain Yes No Yes [61]
34 WePower No No Ethereum WPR Token Public Blockchain Yes Yes No Yes [62]
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
14
After a careful analysis, it is found that the answers to these sub-
questions are generally in the affirmative, thus a “Yes”for all the cases.
Further explanation is, however, given below:
Sub-RQ-A: Are these ecosystems composed of multiple stakeholders?
Yes. In all considered cases, these ecosystems are also found to be
comprised of multiple stakeholders or actors. These stakeholders include
prosumers, consumers, service providers, investors, communities, non-
profit organizations, platforms, ecosystems, and many others.
Sub-RQ-B: Are these ecosystems comprised of decentralized multi-site
heterogeneous technology?
Yes. Distributed energy resources in these ecosystems are decen-
tralized and located at multiple sites. There is evidence of het-
erogeneous technology use. RQ-2 provides an additional
explanation of the types of technologies that are currently being
used.
Sub-RQ-C: Are these ecosystems formed by aggregating distributed
energy resources?
Yes. Some cases demonstrate the aggregation of distributed en-
ergy resources, although not many of them.
Sub-RQ-D: Are these ecosystems supported by ICT?
Yes. The studied ecosystems thrived with the support of computer
networks. This is seen in all the cases studied. Community mem-
bers are connected using an online portal.
Sub-RQ-D: Are these ecosystems characterized by a simultaneous flow
of information and energy?
Yes. There is information flow between community members and
power flow from suppliers to consumers. All of this happens
simultaneously.
In the context of the function, item 6 is also framed into a sub-
research question as follows:
Sub-RQ-E: Do these ecosystems function like a virtual power plant,
thus acting like a single power plant?
The outcome of this sub-research question is provided in Table 7
below.
5. Summary and conclusion of research findings
5.1. The existence of the potential to act like VPPs
The study reveals that most of these cases have access to diverse and
vast numbers of DERs that are found to be connected in these networks.
Incidentally, these DERs constitute a key asset for all VPPs. This, there-
fore, suggests that most of these ecosystems have access to the primary
assets that could enable them to perform functions that may be similar to
those of VPPs. Yet, in several of the studied cases, the ecosystems did not
integrate features that could afford them the capacity to aggregate con-
nected DERs. The focus of these ecosystems is predominantly on P2P
exchanges.
5.2. Limited use of collaboration and related concepts
Another significant finding is that most cases operate at the level of
cooperation rather than collaboration. In such cases, it can be suggested
that collaboration could be a plausible mechanism that would allow ac-
tors in these ecosystems to come together, devise a common goal, and
engage in collective actions that could result in the aggregation of out-
puts from connected DERs so that they could perform some function
similar to a VPP. Knowledge, concepts, principles, and mechanisms from
the domain of collaborative networks could be useful to adopt. Future
research direction could focus on this area.
5.3. Limited use of intelligent agents
The types of enabling technologies that are found, appear to be
driving the energy industry towards energy cloud 4.0 [9]. Some of the
key highlights of these enabling technologies include the integration of
AI, smart IoT devices, smart software agents, blockchain technology and
related smart contracts, cryptocurrencies, and cloud-based applications
such as platforms-as-a-service, etc. The direction of these ecosystems is
towards greater sustainability, flexibility, autonomy, individualization,
digitalization, and virtualization [9]. It is realized that these de-
velopments may introduce some complexities in terms of choices,
decision-making, and preferences that may seem overwhelming and
cumbersome for human users to single-headedly adopt and use. The need
for some form of autonomous and complementary decision-making
assistance to help navigate this myriad of options for optimized choices
and decisions could be useful. However, the study reveals that all but two
cases did not consider the integration of software agents into their eco-
systems, although this concept has been shown to have good prospects in
the implementation of complementary decision-making entities.
5.4. Cross-platform trading and interoperability between cryptocurrencies
Another noteworthy observation is the lack of evidence of cross-
platform trading and interoperability between cryptocurrencies.
Furthermore, unlike fiat currency, which can be converted from one
currency to another, evidence of interoperability between the various
cryptocurrencies is also lacking. With such limitations, the actors in these
ecosystems are restricted in terms of choices and access to diversity in
terms of affiliation, diverse energy sources, and related services.
6. Conclusion and future work
The objectives of this work are in three folds. These are (a) to char-
acterize the interaction that exists between the actors in the studied
ecosystems. (b) To extricate the technological enablers that are driving
the existence and proliferation of these ecosystems and (c) to compare
the characteristics and functions of a VPP to those of the renewable en-
ergy ecosystem cases. The result for the first objective is shown in
Table 5. The table reveals that in almost all the considered cases, the
interactions between the actors could be described as cooperation, except
in one case. The result for the second objective is also summarized in
Table 6. It can be observed from the table that the dominant techno-
logical enablers include IoT devices, smart meters, intelligent software
agents, peer-to-peer networks, and distributed ledger/blockchain tech-
nology (including smart contracts, Blockchain as a Platform service, and
cryptocurrencies). Other technologies that are found include Platform as
a Service and Software as a Service. The result for the third objective is
also shown in Table 7. It reveals that, in terms of characteristics, these
two concepts are similar. This is because they are both found to be
composed of multiple stakeholders or actors. They are comprised of
decentralized multi-site heterogeneous technologies, systems, or assets
and are formed by aggregating distributed energy resources. They are
also found to be supported by ICT and are characterized by the simul-
taneous flow of information and energy. Although it has been shown that
the characteristics of these energy ecosystems are similar to those of a
VPP, they do not function in the same way.
In terms of their functions, the majority of energy ecosystem cases did
not focus on energy resource aggregation, which is a key function that
can enable these ecosystems to aggregate different energy generation
units, which could result in the creation of some capacity that could
enable them to act like a single power plant or a VPP. Since this func-
tionality is generally absent, the majority of these ecosystems could not
perform functions that could make them act like VPPs. However, there
are four (4) cases that are found to possess the aggregation of the
K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
15
Table 7. The outcome of sub-RQ-E.
Index Cases Do the ecosystems function like a virtual power plant, thus acting like a single power plant?
1 BittWatt No.
Reason: Does not appear to focus on the aggregation of Distributed Energy Resources (DERs), which is a key function that can enable these
ecosystems to aggregate different energy generation units, which could result in the creation of some capacity that could enable them to act
like a single power plant or a VPP
2 Electrify Network No.
Reason: Does not appear to focus on the aggregation of DERs.
3 Electrify.Asia No.
Reason: The focus is on the development and deployment of the “PowerPod”IoT device and P2P energy trading using the synergy and
marketplace 2.0 applications
4 ElectronConnect No,
Reason: Focused on energy trading activities mainly
5 EnergiMine Partial.
Reason: Currently working with Elexon, a UK-based company to allow future aggregation of energy storage devices that can be traded on the
platform to help balance the grid. Grid balancing is also one of the features of technical VPPs. Partial because this is yet to be implemented
6 Energo Labs No.
Reason: Does not appear to focus on the aggregation of DERs
7 Energy Web Foundation No.
Reason: Does not appear to focus on the aggregation of DERs
8 EnergyNet No.
Reason: Does not appear to focus on the aggregation of DERs
9 Enosi Foundation No.
Reason: The vertical hierarchical architecture of the Enosi network where consumers can only access the energy market through a Neo Retailer
and subsequently a licensed retail supplier appears to limit the possibility of aggregating DERs to enable them to behave like VPPs.
10 EtainPower No.
Reason: Focusses on renewable energy project financing and not the aggregation of DERs
11 Greeneum No.
Reasons: Does not have the capacity to aggregate DERs.
12 GridþNo.
Reason: Act mainly as an energy trading platform with a focus on the deployment of the Grid þSmart agents. No emphasis is placed on the
aggregation of DERs
13 GridX No.
Reason: Does not appear to focus on the aggregation of DERs
14 Hive Power Yes.
Reason: Based on the notion of “Self-Consumption Communities”(SCC) the community can sell excess solar power to the national grid e.g.,
during summer days and receive financial remuneration. This action replicates the behaviour of a VPP
15 Jouliette (Spectral) Partial.
Reason: The “Spectral Energy Control System”enables the seamless integration and control of energy storage devices, wind farms, PV plants,
heat pumps, generators, and a wide range of other energy systems. This feature of the ecosystem can enable it to function as a VPP although
this is not explicitly stated as a function of the ecosystem.
16 KWHCoin No.
Reason: Current focus is to promote the KWHCoin as a digital currency for energy trading
17 Lition No.
Reason: Does not appear to focus on the aggregation of DERs.
18 LO3 Energy/Brooklyn Microgrid Partial.
Reason: Have the capacity to support the local community in emergencies when the grid fails.
-Has the potential to act as a single power source in future development
19 NAD Grid No.
Reason: Act mainly as an energy trading platform
20 Peer-2-Peer Energy Protocol
(P2PEP)
No.
Reason: Does not appear to focus on the aggregation of DERs
21 Power Ledger No.
Reason: The platform appears to focus on data collection, market management and/or pricing mechanisms
22 Prosume Foundation Yes.
Reason: One of the features of the platform is to facilitate the integration of Power-Plants and Micro-Grid management on the ESCO (Energy
Sharing Company) model. This feature can enable the ecosystem to act like a VPP.
23 Pylon Network No.
Reason: The platform does not seem to support the aggregation of DERs to form the similitude of VPP although it is mentioned that stand-alone
producers can sell surplus energy to the grid, there is no indication that this is achieved through aggregation of DERs.
24 Share &Charge No.
Reasons: The current focus is on EV charging. Does not have the capacity to aggregate DERs
25 Solar Bankers No.
Reason: Does not appear to focus on the aggregation of DERs.
36 Solar IoT No.
Reason: Does not appear to focus on the aggregation of DERs
27 SonnenCommunity Yes
Reason: The Sonnen Virtual Power Plant achieves this through its digitally networked swarm of home storage systems. If the electricity
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K.O. Adu-Kankam, L.M. Camarinha-Matos Heliyon 8 (2023) e12617
16
generation unit's functionality, and therefore these ecosystems could act
like a single power plant or a VPP. These cases included Hive Power,
Prosume Foundation, SonnonCommunity, and WePower. Other cases,
such as EnergiMine and Jouliette (Spectral), are also found to show po-
tential to function as a VPP.
The significance of this study can be seen from three perspectives.
These are (a) the study reveals a research gap in terms of how actors of
these ecosystems interact. The research opportunity in this direction
includes the consideration of collaborative behaviours among members
of these ecosystems. (b) The study has also helped to unveil the level of
penetration of digital technology and digitalization within these energy
ecosystems and finally, (c) It has helped to uncover the limitations of
these renewable energy ecosystems and how these limitations could be
overcome to enable them to perform other sustainability function com-
parable to VPPs.
In subsequent studies, we would like to know how the performance of
these energy ecosystems could be improved if the interaction between
members is reconfigured to allow them to collaborate rather than
cooperate. Considering the claimed benefits of collaboration, as sug-
gested by Camarinha-Matos and Afsarmanesh in [23], it is hoped that
these ecosystems could yield better outcomes if the interactions between
members are encouraged to take a collaborative form.
Declarations
Author contribution statement
All authors listed have significantly contributed to the development
and the writing of this article.
Funding statement
This work was supported by Project CESME (Collaborative &Evolv-
able Smart Manufacturing Ecosystem) and the Portuguese FCT program
UIDB/00066/2020.
Data availability statement
No data was used for the research described in the article.
Declaration of interests statement
The authors declare no conflict of interest.
Additional information
No additional information is available for this paper.
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