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

𝑓𝑙𝑜𝑎𝑑𝐴𝑣𝑒𝑟𝑎𝑔𝑒 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)


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

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