New Business Models Through a Sharing Economy in the Energy Sector - Seminar Paper Adrian Degode

E-Energy - Challenges and Opportunities for
Information Systems in the smart grid
– SEMINAR WINTER SEMESTER 2015/2016 –
New business models through a “Sharing Economy”
in the Energy Sector
– SEMINAR PAPER –
Submitted by:
Adrian Degode
Student ID: 3110192
Advisor:
Stefan Reichert

New business models through a “Sharing Economy” in the energy sector?
Table of Contents
1. Introduction................................................................................................................................................................1
1.1 Objective and Outline....................................................................................................................................2
2. The Smart Grid ..........................................................................................................................................................3
2.1 From Power Grid to Smart Grid................................................................................................................3
3. Grid Flexibility...........................................................................................................................................................5
3.1 Flexibility in Energy Production...............................................................................................................6
3.2 Flexibility in Energy Storage......................................................................................................................7
3.3 Flexibility in Energy Consumption..........................................................................................................8
3.4 The Economic Importance of Flexibility for the Grid ...................................................................10
4. New Business Models through a Sharing Economy................................................................................11
4.1 Sharing Economy - A Major Change in Power Industry?.............................................................11
4.2 Business Cases from the Sharing Economy in the Energy Sector............................................12
4.2.1 “Yeloha”..................................................................................................................................................12
4.2.2 “Mosaic”..................................................................................................................................................12
4.2.3 “Vandebron”.........................................................................................................................................12
4.2.4 “Lichtblick”............................................................................................................................................13
4.3 Aggregation of Small Scale Resources as a Business Model.......................................................14
5. Evaluation and Discussion.................................................................................................................................16
Limitations and Future Research.............................................................................................................................19
References..........................................................................................................................................................................20

List of Figures
Figure 1. Hourly loads from ERCOT in 2005 (Denholm, 2011).....................................................................5
Figure 2. Load Shifting (Coda Energy, 2015) ........................................................................................................7
Figure 3. Basic Load Shaping Techniques (Gellings, 1985).............................................................................9
Figure 4. Integrated information and automation systems (Koto et al., 2011)...................................14

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1. Introduction
“You could power the entire United States with about 150 to 200 square kilometers of solar panels,
the entire United States. Take a corner of Utah… there is not much going on there, I have been
there. There’s not even radio stations.” – Elon Musk
Until today, the worldwide primary energy supply has risen constantly. The supply has followed
the demand curve (IEA 2015a, p. 6) and will continue to do so in the future (World Energy Council
2013, p. 38). Through new technologies such as fracking, peak oil has moved to an unknown point
in the future as new oil fields are being discovered constantly. However, the world is not in a
situation to continue to carry the side effects of fossil fuels for another century. Already today,
global warming is a fact that will have serious physical and social consequences throughout the
world as depicted by the NASA (www.climate.nasa.gov) and approved by numerous leading
scientists (AAAS 2009).
Energy production from renewable energy sources can contribute to the solution of this problem.
Considering their low carbon dioxide emissions compared to other types of energy production
(Wagner, 2007) and due to ongoing technological improvement in production (Economist, 2012)
and efficiency of renewables, especially in the area of Photovoltaics (PV) and wind energy, interest
in renewable energy as savior of the climate but also as an economic driver and long-term
investment has risen continuously (IEA 2015b, pp. 368-372; Bloomberg, 2015, pp. 15-16). While
worldwide implementation of PV and wind turbines has grown dramatically in the last years (IEA,
2013, p. 9; IEA, 2014, p. 10) and is accelerating, it is important to realize that new problems with
grid stability have arisen as nations struggle to integrate fluctuating energy from renewable
resources into the grid.
Most grids in western countries were built decades ago and designed to cascade large quantities
of high voltage energy from large power plants to the decentralized end-user. They were not
designed to cope with energy flowing in the reverse direction from decentralized small generators
into the grid. Furthermore, they were not designed to deal with the intermittency of numerous
renewable generation methods such as solar and wind which are predicted to take a leading role
in renewable energy production besides hydropower by 2040 (IEA, 2015b, p. 348) which
constitutes a serious challenge for the future (Denholm, 2011, p. 1817).
To integrate steadily increasing amounts of fluctuating energy sources successfully, grid flexibility
in energy production, storage and especially consumption, will play a major role. New

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technologies will enable the so-called “smart grid”, offering new IT leveraged possibilities of grid
management to address grid flexibility and other challenges of supply and demand (Gelazanskas
and Gamage, 2014, p. 22).
Furthermore, the upcoming energy transition also offers potential for new business models that
move away from the classical one-sided market towards a two-sided market where in the future
consumers actively participate through own production and altered consumption behavior. While
this movement, also known as Sharing Economy (Matofska, 2013), has not affected energy market
structures yet, it will most likely become an important driver soon. Promising new startup
companies, although still in their infancy today, may change the way energy markets work in the
future resulting in higher efficiency of resource usage as well as lower energy prices.
This leads to two main questions:
1. What will determine whether these business models will be successful?
2. Will the sharing economy help to achieve a successful energy transition?
1.1 Objective and Outline
This paper begins with a general introduction to power grids today and their development
towards a smart grid, showing its possibilities within changed environmental conditions.
In the subsequent chapter, various factors that determine the value of flexibility in the in the grid
will be analyzed showing the key elements of stability and reliability within this future grid. More
precisely, three areas will be examined, flexibility in consumption, production and storage. It will
also be shown why flexibility is so important in electrical grids when facing the integration of large
amounts of fluctuating renewable energy while an important source of base load from coal and
nuclear power is phased out.
In chapter IV, this work will introduce several new business models that have evolved in recent
years and are driving the energy transition towards a sharing economy. This is followed by a
feasibility analysis of a business model that aggregates small-scale loads and offers their potential
in the market.
Chapter V will evaluate determinants for the success of these business models and finally discuss
possible impacts on the energy market in the future. This work will end with a short limitation
and outlook for future research implications.

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2. The Smart Grid
In the following, the functionality of traditional power grids will be presented, followed by an
introduction and subsequent definition of the future grid, named “smart grid”.
2.1 From Power Grid to Smart Grid
Traditionally, electric power grids can be designed in radial, looped or meshed fashion (Catalão
2015, p. 289) with radial structures being most common. Traditional grids are designed
unidirectional, meaning that electricity flows from large power plants via high voltage
transmission grids into many different low voltage distribution grids to supply residential loads.
While this system worked well in the last century where coal and nuclear power where
responsible for the majority of production, it is outdated and challenged by new technological,
economic and environmental developments, such as well as the deregulation of electricity
markets western countries today (Bari et al., 2014, p.1). However, various renewable energy
sources (RESs) such as wind turbines, PV solar systems, solar-thermo power, biomass power
plants, hydropower turbines, combined heat and power (CHP) micro turbines and hybrid power
systems are partly already used today and will be an inherent part of the electricity production in
the future (Mohd et al., 2008, p. 1627).
According to Fadel et al. (2015), integrating larger amounts of energy from the aforementioned
ways of production into the existing grid, will transform this grid into “a very large-scale, highly
distributed generation system which incorporates a large number of generators, generally
characterized by different topologies which combine different technologies with various current,
voltage and power levels”. Considering that such large-scale grids moreover connect
internationally to other grids, so-called “super grids” will evolve.
These changes in the electricity production and distribution call for a next generation power
system that, while being more reliable, scalable and manageable than today’s grids, should also
offer better cost-effectiveness, security and interoperability (Gao et al., 2012, p.1). For a next
generation power system that integrates various RESs, automated and intelligent management
will be an unquestionably necessary component, determining its effectiveness and efficiency
(Wang et al., 2011, p. 1). Wang (2011) entitles this next generation power system as “smart grid”.
Although there is no single and generally valid definition of the term smart grid, the way Murphy
et al. (2010) from the Ontario Smart Grid Forum has defined it seems to be most comprehensive
and therefore suitable to point out all the different aspects:

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“A smart grid is a modern electric system. It uses communications, sensors, automation and
computers to improve the flexibility, security, reliability, efficiency, and safety of the
electricity system. It offers consumers increased choice by facilitating opportunities to
control their electricity use and respond to electricity price changes by adjusting their
consumption. A smart grid includes diverse and dispersed energy resources and
accommodates electric vehicle charging. It facilitates connection and integrated operation.
In short, it brings all elements of the electricity system production, delivery and consumption
closer together to improve overall system operation for the benefit of consumers and the
environment”
While today, such a “smart grid” is still on the drawing board, the development of smarter grids
can be clearly observed at all bigger network operators such as PG&E (USA), British Gas (UK), EDF
(France), Eon (Germany), Vattenfall (Sweden) or SGCC (China). The reason for this is that keeping
the grids stable whilst constantly increasing input from renewable energy (RE) as it is the case
today, requires new ways of energy management.
This development is not surprising, considering the fact that without exception, the number of
smart meters and Intelligent Electronic Devices is expected to increase strongly within the next
decade (Navigant Research, 2013; Ets insights, 2013) and will have to be managed in efficient
ways.

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3. Grid Flexibility
As mentioned before, the bottleneck of today’s grids and at the same time the challenge that has
to be met by grid operators, is the inflexibility in integrating new distributed energy resources
(DERs) into the power system (Jaradat et al., 2015, p. 593). According to Akorede et al. (2010),
DERs refers to “electric power generation resources that are directly connected to medium
voltage or low voltage distribution systems, rather than to the bulk power transmission systems.”
These may include generation units such as fuel cells, photovoltaics etc. on the one hand, and
energy storage technologies such as batteries or flywheels on the other hand.
According to Denholm and Hand (2011), being able to respond to load fluctuations as well as to
provide operating reserves at the same time, requires different kinds of power plants working
simultaneously: Baseload, which means constant production, Intermediate load, meeting the daily
average demand curve and finally Peaking load, which covers short peaks in electrical demand
mainly during summertime. An example for a summer-peak-load structure and its variations can
be seen below in figure 1 depicting a large grid (ERCOT) from Texas (USA), showing its load
variation.
Besides managing daily, weekly and seasonal demand, grid operators must be able to dispatch
additionally needed power to “rebalance, restore and position the bulk-power system to maintain
reliability through normal load variations as well as contingencies and disturbances” (NERC,
2009, p. 6). Whereas contingencies normally refer to unforeseeable events with major impacts
such as power plant blackouts, frequency regulation and load-forecasting errors also need to be
addressed (Denholm, 2011, p. 1818). This responsive ability of grid operators is also known as
operating reserve. In subsequent chapters, it will be demonstrated which different kinds of
flexibility in power grids can be achieved and why they are important, starting with flexibility in
energy production.
Figure 1. Hourly loads from ERCOT in 2005 (Denholm, 2011)

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3.1 Flexibility in Energy Production
Energy production through wind and solar is subject to weather conditions, which cannot be
100% predicted. In contrast, conventional types of generators usually have the ability to reduce
their output to some degree and work load following by cutting down the amount of fuel, which
is termed system flexibility (Denholm, 2011, p. 1819).
Especially for grid scenarios with high system penetration of variable generation (VG), which is a
likely scenario for the majority of grids in the future, the ability of the aggregated set of generators
to respond to variations and uncertainty in the net load plays an important role. Denholm and
Hand (2011) demonstrated that a power system with little or no system flexibility would,
economically seen, end up in high energy-curtailment. Therefore, it would be advisable that power
generators are able to cycle down their production e.g. of a large power plant down to zero within
a short period. Hence, in times of strong variable generation that covers complete demand, no
energy would be curtailed in consequence of inflexible generators. However, two problems apply:
First, according to Denholm (2011), a flexibility factor of 100% cannot be achieved in today’s grids
and second, renewable production is not available at all times but intermittent. Considering this,
flexibility in the production might not be the cheapest and easiest way to achieve increased grid
stabilization but also rather other mechanisms like load shifting or demand response should be
put into focus for the future, as they can provide operating reserves in a more cost effective and
flexible way; this topic will be discussed in chapter 3.3.
Another important factor to consider is the transmission and distribution of the energy as grids
are often connected to other neighboring grids. These connections can promote rebalancing larger
variations in demand by importing and exporting electricity from and to surrounding grids,
adding economic efficiency and flexibility to the system. Depending on the development of
decentralized energy production in the future, the potential of connecting grids to improve load
balance may hold potential to be exploited, especially in the light of new Information and
Communication Technologies (ICT) that can help to make power management easier for large-
scale grids in the future.
In 2012, the average loss through transmission and distribution in the OECD countries was 6.39%
of all transmitted electricity on average (WDI, 2015). Economically seen, this makes transport of
large amounts of energy over longer distances less attractive opposed to alternative possibilities
such as higher system flexibility (if possible at all), ways of storing energy locally or Demand Side
Management (DSM). This is of course subject to economic variables. The next chapter will
therefore show the advantages of possible energy storage techniques in combination with high
penetration of VG in the grid and the resulting flexibility.

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3.2 Flexibility in Energy Storage
As mentioned before, Solar and wind generation are subject to environmental conditions, which
in turn depend on the geographic location of the grid. The probability of no curtailment at all, even
within a 100% flexible system could be achieved, is still very low. This is simply due to limited
supply and demand coincidence (Denholm, 2011, p. 1825). Regarding this problem, storage
techniques should be considered as part of the solution for this problem.
By load shifting, i.e. by moving the otherwise unused and therefore curtailed energy to times of
high net-load, curtailment of renewable energy could be decreased drastically. A depictive
explanation of load shifting is shown below in figure 2.
The degree of efficiency of this process will depend on the shifting technique applied. This can
include various techniques for long-term storage such as pumped-hydro storage, electrical
batteries or energy stored in compressed air but also for short-term storage such as super
capacitors or Flywheels (Mohd et al., 2008, pp. 1629-1630).
Besides preventing energy curtailment, storage can furthermore contribute to other aspects such
as voltage and frequency support, which are a big issue for grid operators in today’s age of
renewable energy integration (Mohd et al., 2008, p. 1628). Although storage solutions help to
reduce energy curtailment of VG, especially when it comes to large energy- and power capacity
shifts, it is, despite the fact that storage prices have dropped dramatically in recent years (Nykvist
and Nilsson, 2015), still very expensive to implement. Another negative by-product of storage is
the round-trip-efficiency loss of the respective storage unit, as technologies are not fully advanced
yet. To achieve high grid penetration of variable generation without wasting energy, large
amounts of storage would be needed that, at present, do not make economic sense (Denholm,
2011, p. 1825). It must however be mentioned here that as prices for storage drop and technology
becomes more efficient, storage will play an increasingly important role in future grids. This
Figure 2. Load Shifting (Coda Energy, 2015)

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assumption is also substantiated by the fact that big players of the market such as Tesla have taken
up the topic already.
However, as intermittent renewable resources and high storage unit costs exists and state a
problem, storage techniques and production flexibility might not be able to face the upcoming
challenge of large amounts of renewable integration. To fill this gap, possibilities arising from the
demand side, meaning flexible energy consumption, must be considered and exploited as they
pose a large, if not the largest, opportunity of all.
3.3 Flexibility in Energy Consumption
When facing the future challenges of our energy system, an important role will have to be played
by managing the demand side, also known as Demand Side Management (DSM) (Denholm, 2011,
p. 1827; Pfluger et al., 2011, p. 88; Gelazanskas and Gamage, 2014, p. 23; Barooha et al., 2015, p.
2700).
While the classical approach to balancing the grid is to follow the demand and hence supply the
exact amount of energy that is demanded, the new approach states that demand should rather be
controlled through consumer participation in the system (Gelazanskas and Gamage, 2014, p. 23).
This is, among other things, exactly what the smart grid idea tries to achieve, making “customer
participation in the overall grid energy management” possible (Bari et al., 2014, p.2).
DSM consists of two main categories: “Demand Response” (DR) and “Energy Efficiency and
Conservation Programs” (Davito et al., 2010, p. 38). While “Energy Conservation programs”
means to encourage people to use less power, “Energy Efficiency Programs” intend to hold utility
constant while improving energy efficiency; both are primarily driven by politics and the
government. For consumption flexibility however, DR activities are in the focus.
Chiu et al. (2009) defines DR as
“Changes in electric usage by end-use customers from their normal consumption patterns in
response to changes in the price of electricity over time, or to incentive payments designed to
induce lower electricity use at times of high wholesale market prices or when system
reliability is “jeopardized”.
In other words, DR includes all changes in timing, current amount of demand or entire power
consumption that were deliberately performed (Albadi, 2007, p. 1). It is worth mentioning that
peak demand contributes to the bulk of system cost because generation as well as Transmission
and Distribution must be designed in such a way as to meet the maximum load peaks, even if it is
only for 30 minutes within a year (Gelazanskas and Gamage, 2014, p. 23). Therefore, already in

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1985, Gellings (1985) introduced typical load shaping techniques that can be used to address this
issue: Peak clipping, Valley filling, Load shifting, Strategic conservation, Strategic load growth and
Flexible load shape. A graphical explanation can be seen below in Figure 3.
Therefore, by means of new ICT available today, through DSM and the above-depicted DSM
activities, it is possible to alter the shape of the demand curve to converge as far as possible with
supply (Gelazanskas and Gamage, 2014, p. 23). By either increasing average load or decreasing
peak load, this would lead to an increase in the system load factor, which reflects system efficiency,
and thus contribute to lower emissions of greenhouse gases.
According to Watkins (1915), the system load factor is defined as
𝑓𝑙𝑜𝑎𝑑
𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑙𝑜𝑎𝑑
𝑀𝑎𝑥𝑖𝑚𝑢𝑚 𝑙𝑜𝑎𝑑 𝑖𝑛 𝑔𝑖𝑣𝑒𝑛 𝑡𝑖𝑚𝑒 𝑝𝑒𝑟𝑖𝑜𝑑
As demand Side response will most likely play a major role in future, it is important to understand
the different opportunities presented by it. Therefore, according to Albadi (2007), DR programs
can be subdivided into Incentive Based Programs (IBP) and Price Based Programs (PBP).
Incentive based programs are divided into classical (direct control or interruptible programs) and
Market based programs (Demand Bidding, Emergency DR, Capacity Market, Ancillary services
market). Generally said, they “pay participating customers to reduce their loads at times
requested by the program sponsor, triggered by either a grid reliability problem or high electricity
prices” (QDR, 2006, p. 5).
Price based DR however is based on dynamic pricing methods such as Time of Use (TOU), Critical
Peak Pricing (CPP) or even Real Time Pricing (RTP), which is the most difficult method to
implement. By using pricing mechanisms with flexible prices however, providers could follow the
classical approach of a Demand and Supply equilibrium (Siano, 2014, p. 462). Certainly, to
implement real-time pricing for the decentralized end user was not possible in the past due to
technical limitations. By means of new ICT however, slowly but surely this step comes closer to
be realized, as the number of installed smart meters is increases (Navigant Research, 2014). Such
Figure 3. Basic Load Shaping Techniques (Gellings, 1985)

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a change in pricing moreover would not only give an advantage to system providers or direct
participants of demand response programs such as RTP, but would also result in a more elastic
demand and thus price, which would be lower than prices with fixed tariffs (Albadi, 2007, p. 3).
Initial programs for demand response with integrating electric vehicles which will be a major
opportunity in future, have already been started e.g. by “enercity” in Hannover, Germany
(Enercity, 2014)
3.4 The Economic Importance of Flexibility for the Grid
By all participants for the first time signing the climate treaty of December 12, 2015 in Paris, which
aims to maintain global temperature rise below 1.5°C, a historic step and a solid foundation
towards a more climate friendly world in the future has been taken (Federal German Government
2015). This goal is supposed to be reached by all countries by achieving a near zero carbon balance
in the second half of the century and therefore will very likely give a strong boost for renewable
energy implementation as environment-friendly technology.
Furthermore, it is likely that several countries will start phasing out power production by coal as
soon as renewable production becomes more efficient and profitable. In fact, solar panel prices
e.g. are decreasing more and more every year (Greentech Media, 2013; NREL, 2014). Considering
a nuclear and coal power phase out, future grids in the future must be able to offer high flexibility
in all of the aforementioned areas with a major focus on consumption and storage as the share of
energy being produced from renewables increases every year (LBBW, 2015, p. 14).
Disregarding the costs of global warming, two major economic arguments for flexibility in the grid
can be named. First, curtailment of energy, as equated with the opportunity costs of otherwise
selling this electricity. An example: 20% of the produced variable energy in a grid is curtailed due
to lack of supply and demand coincidence in connection with renewable production.
Implementing large amounts of storage with Round-Trip Efficiency of 80% (an average battery),
the energy provider would only bear 4% of revenue loss opposed to 20% without any kind of
flexibility. By combining flexibility in production, storage and consumption, these costs could be
reduced even further.
The second major argument for flexibility is maintaining grid stability, which is why Transmission
System Operators (TSOs) exist. A survey by the Berkley National Lab showed that the estimated
cost of power outage in the United States alone is estimated at $80 Billion every year (LaCommare
and Eto, 2004). This clearly shows the economic impact of grid stability for a nation. Adding
flexibility to the grid could therefore significantly improve the management of power quality
(power range, frequency and voltage). As, due to increasing amounts of intermittent renewable
energy, flexibility in the production becomes less important every year, the focus for the future

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should be more on flexibility in consumption and storage of energy. Thus, by using DSM and
storage techniques, efficiency and stability of grids could be significantly improved with the
outcome of reduced chance of power outages.
4. New Business Models through a Sharing Economy
This chapter will introduce the new phenomena of the “Sharing Economy” (SE). The term “Sharing
Economy” will be defined and its impacts on the electricity market today and in the future will be
discussed. Moreover, several new companies that have arisen from the SE and operate in the
energy market will be introduced. In a next step, the feasibility of a new business model that offers
small aggregated loads in the market will be assessed.
4.1 Sharing Economy - A Major Change in Power Industry?
Until today, mostly large companies participated in the energy market via DR programs. By
including small-industrial and residential customers in the DR-equation, which is now
increasingly becoming possible through ICT, completely new opportunities arise in this area,
raising DR to the status of a mainstay in future smart grids.
In recent years, the phenomena “Sharing Economy” has changed the whole markets. While the
most popular examples are companies like Airbnb or Uber, more and more areas come up with
new business models and ideas that apply the “sharing” idea. The electricity markets have not yet
had such a revolution, but already today, new promising startups like “Yeloha” or “Mosaic” from
the USA but also “Vandebron” from the Netherlands or “Lichtblick” from Germany are taking the
SE-lead in the energy market. More are expected to come. However, how to define the term
“Sharing Economy”? Not many definitions exist yet. The most applicable one however was given
by Benita Matofska (2013): “The Sharing Economy is a socio-economic ecosystem built around
the sharing of human and physical resources. It includes the shared creation, production,
distribution, trade and consumption of goods and services by different people and organizations.”
According to Jeremiah Owyang (2013), founder of Crowd Companies, there are three major
market drivers for the SE also known as Collaborative Consumption: Social-, economic- and
technological drivers. While Social drivers could be an increasing population density, the concept
sustainability, or the desire for community, economic drivers could be the monetization of excess
inventory, strained resources or the desire for previously inaccessible luxury. However, above all
others the technological drivers in the first place, made the SE at all possible through social
networking, mobile technologies, and digital payment systems.

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4.2 Business Cases from the Sharing Economy in the Energy Sector
To see the difference between classical power companies and those from the sharing economy,
several companies that originated from the SE will be presented.
4.2.1 “Yeloha”
Yeloha is a young startup from Boston (USA) that offers a Peer-2-Peer solar sharing network.
Yeloha is at the heart of the sharing economy as it is “the Airbnb for solar energy” (Whitford,
2015). There are two possibilities for consumers: First, a participant has a rooftop that is suitable
for installing solar panels, and therefore can offer their rooftop to other people who do not have
this possibility. These People are “sun hosts” as opposed to the “sun partners” who subscribe to
one or more solar panels. While the latter do not have to pay anything and can use around 30% of
the produced energy for free, the sun partners have to pay a subscription fee to “rent” the panels.
The excess energy is fed into the grid. The Sun Partner gets “Energy Credits” for energy that is sold
into the Grid. These credits are then used to reduce his electricity bill from his utility. The
company's revenue stream is from these subscriptions. Yeloha offers a value proposition by
lowering cost for all participants, a very convenient online platform, a community element that
you get in touch with and finally a lifestyle component that helps the environment.
4.2.2 “Mosaic”
Mosaic is a company based in Oakland (USA), offering a Peer-2-Peer business model (BM) based
on the principle of collaborative crowdfunding which gave it the reputation as “the Kickstarter for
solar” (Fehrenbacher, 2012) before. Mosaic helps each and every person to be part of the energy
transition by enabling them to participate in larger solar projects already starting from very small
amounts like $25 of investment, offering stable Return on Investment rates that can be either
reinvested in new projects or withdrawn onto ones bank account. Investing in projects of mosaic
can be done very conveniently via their website. Mosaics revenue sources are on the one hand
origination fees paid by the solar partners on the loans they get and on the other hand, small fees
which the investors have to pay. Mosaic therefore offers convenience, a value proposition for the
investor and a lifestyle component in terms of contributing to the environment and to other
people by helping them financing their solar projects.
4.2.3 “Vandebron”
Vandebron, based in the Netherlands, offers a Peer-2-Peer online platform that allows consumers
to avoid the traditional energy provider and directly buy renewable energy from selected
decentralized power producers. Vandebron itself does not own any facilities but only facilitates

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the administrative connection between consumers and producers. This includes solar, wind,
water and bio energy. Their aim is 100% transparency, selling real renewable energy instead of
energy from fossil fuels that is declared as “green” by trading emission certificates. Vandebron
helps both, consumers and producers to save- and respectively earn more money than by
cooperating with traditional providers. A social and reputational component is available in terms
of getting to know the producer in detail via an online story or even personally and of course by
promoting the implementation of more renewable energy. The business model is a monthly
subscription fee per connection for every user. Therefore, by reducing individual energy
consumption, Vandebron can allocate more users to each utility and thus produce more revenue.
Additionally, to add some convenience, Vandebron also offers gas delivery to its customers, as
buying from different utilities is impractical for the end customer. Essential for this business
model are liberalized energy markets.
4.2.4 “Lichtblick”
Lichtblick is the first German company to step away from the unidirectional Business towards a
SE. Although Lichtblick is not a new company, as it has already existed for 10 years as a classical
power delivery company for renewable energy, they have recently started a new business model
called “Swarm energy” which transforms the consumer into a prosumer. On the consumer level,
Lichtblick leverages its large electricity customer base and “Lichtblicker” community (as they are
called) by encouraging them to invest in photovoltaics and a storage unit or even bi-directional
electric vehicles. On the utility level, Lichtblick uses its proprietary complex IT-Platform named
“Swarm Conductor” that connects all the individual storage units into a large virtual bi-directional
power plant. By leveraging their license as a utility, Lichtblick can then participate in the larger
Energy market, in particular on the EEX (European electricity exchange) in Leipzig, which is
reserved to contracts above one MW, to offer “stability services” to the grid by either absorbing
or selling energy from or to the grid when prices are highest.
In a complex billing model, the consumer receives free energy into his storage or sells his excess
renewable energy to Lichtblick and thus participates in the larger energy market, which would
otherwise be closed to him. Furthermore, the consumer participates in Lichtblicks revenue
stream, which helps to finance their storage unit. Lichtblicks aim for the future is that every user
can connect to his personalized Interface via an App and share or sell their energy to the market
or to individual community participants. However, this is not possible today due to antiquated
legislation. Indeed, this energy could be shared and sold in Airbnb manner in the future, if the
energy stock market becomes more liberalized. Participating in Lichtblicks network offers several
things to the customer: Clearly, a value proposition in terms of reducing cost is given. As the
company and customers help to create a greener energy market, they also stand for sustainability.

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Being part of a large community of “Lichtblickern”, most certainly offers a feeling of community
and furthermore good reputation in terms of participating into something good for the
environment. In terms of convenience however, the business model is not competitive yet as it
needs a lot of effort to establish a complete solution. Besides that, Lichtblick offers everything that
is needed for a successful participation in the Collaborative Consumption market.
4.3 Aggregation of Small Scale Resources as a Business Model
As in the future, flexibility in the consumption will play a major role, the assessment of the
feasibility of a business model (BM) that aggregates small-scale resources of energy from many
different participants could be interesting. Therefore, such a BM would aim to afterwards offering
the aggregated energy to the market. Distributed energy resources (DERs) would be in the center
of attention for such a model. Depending on the definition of DERs, Demand Response can also be
counted as a DER as it is distributed and can be seen as a source of generation that is moreover
highly flexible and dispatchable.
Small Scale Resources can be defined as controllable loads such as Space Heating/Cooling devices,
water-heating systems, Electric Vehicle (EV) charging and, very relevant in the future, storage
systems such as Tesla’s Powerwall from the USA or SOLARWATT’S “My Reserve” from Germany.
A business model that aggregates such comparable small loads would highly depend on ICT, as
the aggregation of large amounts of small sources equivalently requires aggregation of large
amounts of information (Koto et al., 2011, p.1). Such a model would require a smart grid like
environment that transfers data via e.g. Wireless Sensor Networks within Home Area Networks
and Neighborhood Area Networks (Fadel et al., 2015). A possible technical overview how an
aggregation could take place is shown in Figure 4 below.
Figure 4. Integrated information and automation systems (Koto et al., 2011)

15 / 26
Thereby, the company that would start such a business model would take the position of the
“Aggregator” providing an IT infrastructure that would process all the different data from every
single Home Automation System within the Network. The Aggregator then would have to be
directly connected to the grid operator in terms of data transfer to help balance the grid as a
service or to offer the accumulated energy in the market.
A business model like the one depicted would in fact work, if seen from a technical side. It would
be a combination of sharing economy in terms of more efficient usage of resources and advanced
DR applications in terms of small loads behaving as virtual storage (Siano, 2014, p. 468).
Furthermore, such a business model would also hold if regarded from the beneficial view, as it
would offer sustainability, enjoyment, reputation and economic efficiency for the participants.
According to Hamari et al. (2015), these four elements can be seen as necessities for a successful
business model in the Collaborative Consumption. However, such a business would require an
already developed infrastructure on End-Customer-Level, comparable to the today planed and
developed smart homes.
Yet, four reasons apply, why such a model is still on the drawing board level today:
1. Technological requirements for such a business model, that would have to be applied in a
greater scope to be profitable, are yet not available today.
2. The cost of setting up the required infrastructure on a Customer-Level as well as on an
Aggregator-Level, including the procurement of a big data IT platform that can manage such a
system, are out of proportion to possible revenues that could be derived from such a BM today.
3. Besides the economic aspects, privacy and security concerns of such a BM will also play a great
role on the consumer side. A BM is only as good as the demand for its service, if the people do
not want to participate for any privacy or security reason it is determined to fail.
4. Regarding argument three, to meet privacy and security goals of today, large investments
would have to be done that make such a BM even more unattractive from the economic side
of view. In addition, it would be unclear if the information that would have to be gathered were
to be arranged with privacy legislation of most of the western world today.
However, it is important to mention that a preliminary stage of such a business model is already
being realized today in Germany by Lichtblick as depicted in chapter 4.2.4. Even though in this
case only one device, the storage, is remotely managed and monitored, it is conceivable that by
further development of ICT and also the society towards the Internet of Things, more and more
digital controllable devices, Electronic Vehicles being next, will become part of everyone’s life.
This development will allow more complex business models, from a technical and from a
consumers’ point of view, in the future.

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5. Evaluation and Discussion
“The stuff that matters in life is no longer stuff. It’s other people. It’s relationships. It’s experience.”
This inspirational quote by Brian Chesky (2013), co-founder and CEO at Airbnb, hits the core of
the sharing economy and can be applied to all business models arising from it. New energy
companies such as those discussed, all offer more than just a product. Most of the time, they
combine convenience with ideology, economic efficiency and a social aspect which distinguishes
them from the everyday energy company i.e. they do not offer one product but a whole
“ecosystem”.
Furthermore, as the sharing economy among other things stands for sustainability, all of the
aforementioned companies ideologically, clearly position themselves as contributing to a greener
world, pushing the energy transition forward. This happens either directly, e.g. by increasing the
amount of energy production through crowd funding like Mosaic does, indirectly, by e.g.
promoting independent installation of wind turbines on own premises as in the Vandebron case,
or by making the utilization of produced energy more efficient e.g. by promoting storage units as
offered by Lichtblick.
As already mentioned in chapter 3.1, flexibility in production is either not possible with
sustainable energy or, in the case of coal, gas and nuclear power plants, too slow and costly to be
used in an ongoing real-time process that will be necessary in the future as high penetration of VG
constitutes a likely case. Therefore, SE business models in the energy market will most likely be
in the field of flexibility using storage or in the field managing the consumption of energy. The
latter however, at least today, is not a real option for companies but may be in the future, as
depicted in chapter 3.4. At the beginning of this paper, two questions were introduced:
1. What will determine whether these business models will be successful?
2. Will the sharing economy help to achieve a successful energy transition?
Referring to question one, a number of determinants come to mind, which are based on four
principles:
1. As shown by Jeremiah Owyang (2015), convenience, closely followed by the price, is
leading the list of most important arguments for using the shared economy. Thus,
companies operating in the sharing economy energy market should value their customer’s
time and patience, by offering especially user-friendly products in combination with a
clearly favorable price point as incentive, if they want to prevail. Furthermore, People long
for “community” in our fast-paced world today. Adding a social aspect will help SE

17 / 26
businesses to first gather and then bind people to their products and services, which is
why this aspect must not be left out of consideration. All in all a “product ecosystem”.
2. Legislation, i.e. the will of the governments to invest in green energy in terms of subsidies
or tax reliefs to push renewables forward will determine whether such businesses will be
successful in future. In the USA for example such a subsidy is the “Solar Investment Tax
Credit” (ITC) which reimburses 30% of the investment of a solar system and was recently
extended to the end of 2020 (US Department of Energy 2015). After this period, the “cost
of solar” which has been dropping rapidly for years, will be a crucial determinant as to
whether companies in the SE Energy sector can survive without subsidies or whether new
government support will be needed to reach the goals agreed in Paris. Another area where
the government plays an important role is the liberalization of the energy markets
(lowering entry barriers), as all SE-business models actively participating in the energy
market depend on the possibility to be able to use the grid for their purposes without
discrimination and at a fair tariff, thus enabling them to develop long term business
models.
3. ICT cost reduction will be crucial to paving the path towards new and more complex
business models such as the aggregation of small energy resources (depicted in chapter
4.3) as today the core of every SE business and simultaneously the biggest investment
position is a convenient IT platform and infrastructure.
4. Personal privacy and system security. While the average energy business does not interfere
with personal privacy at home on a large scale yet, future models in a smart grid
environment such as advanced demand side management and smart homes most
certainly will. Therefore, privacy protection and privacy awareness will play a
considerable role in the success of these models and will need to be backed up by relevant
legislation. Besides privacy argument, “system security” should not be underestimated as
such IT-intensive environments may offer new ways for cyber-criminal activities.
The constantly decreasing production price of solar panels, wind turbines and storage elements
coupled with the increase in their efficiency will eventually lead to an increased interest in new
business models. As soon as it is affordable, understandable and offers an economic case to the
small man, it is likely to lead to mass implementation of DERs.
Referring to question two:
It is difficult to say what the role of the sharing economy will be in terms of its effects on grid
stability and therefore on a successful energy transition. Business models such as Lichtblicks
“Swarm Energy” and the like, which have a storage unit in the center of attention, at least today,
primarily intend to drive revenue by providing balancing energy to the utilities. Other companies

18 / 26
like Yeloha or Mosaic however, drive revenue only from the implementation of new renewable
production, which increases the amount of variable generation that intermittently feeds power
into the grid, and further promotes grid instability as a side effect. Grid stability is not their
business but that of Transmission System Operators (TSO’s) whose job it is to guarantee reliable
grids. In the future, this could lead to new fees for companies destabilizing the grid on the one
hand or rewards for those stabilizing it on the other hand.
The aforementioned SE business models all rely on a centralized grid and its stability as a solid
backbone. The relationship between the sharing economy and traditional centralized production
was therefore appropriately summed up in one sentence by Matthew Crosby from the Rocky
Mountain Institute:
“A Peer-2-Peer sharing economy for DERs doesn’t obviate centralized power resources and the
grid—it complements the grid to provide consumers with a more optimized set of choices and
reliability” (Crosby, 2014).

19 / 26
Limitations and Future Research
As the sharing economy in terms of energy market based business models is still in its infancy, it
is not possible to give binding statements about the exact consequences of this new development
for this industry and the grid stability today. Furthermore, different variables like government
support, cost reduction of ICT, decreasing production cost and increasing efficiency of PV and
wind-turbines and the attitude of humans towards clean technology, will determine if new
companies from the SE will become “big players” in the energy market, impacting their branch
like Airbnb as a showcase model did, or not.
This work has depicted the importance of flexibility in grids and presented several new business
models for the energy market in the sharing economy. However, it is limited in terms of examining
the impacts of these business models on the energy markets. Furthermore, no empirical research
has been done due to time and resource limitations, which is why additional empirical research is
needed to test the implications from this work. Therefore, future research could investigate the
economic impacts of energy companies from the sharing economy on the energy market in terms
of grid stability and efficiency, on the development of incumbent energy companies or on the trend
of average energy prices in the future, preferably from an empirical perspective.

20 / 26
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