Assessment of PV-based business models in urban energy ......Seite 1 von 20 Assessment of PV-based...

10. Internationale Energiewirtschaftstagung an der TU Wien IEWT 2017

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Assessment of PV-based business models in urban energy systems with respect to political and

economic targets: A model-based scenario analysis

Stephan Seim1 (1), Fabian Scheller(1), Mario Götz(2), Hendrik Kondziella(2), Thomas Bruckner (1, 2)

(1) Institute for Infrastructure and Resources Management (IIRM), University of Leipzig (2) Fraunhofer Center for International Management and Knowledge Economy (IMW)

Abstract:

In order to address today’s persistent challenges like climate change and the phase-out of

nuclear energy, the ‘Energiewende’ is profoundly transforming the German energy landscape.

Utilities are forced to further develop their business models by taking into account the growing

share of prosumers, changing political requirements and increasing competition from new

players entering the market. The development of promising utility business models and overall

strategies therefore is a challenging task, which needs to consider the utilities’ structural

conditions (generating capacities, customer base, tariffs) as well as the regulatory

environment. In this context, the economic performance of three innovative photovoltaics-

based business models for municipal utilities will be evaluated. The business models of

photovoltaic (PV) power self-consumption, direct power consumption and direct marketing will

be assessed and compared to the conventional business model of grid-based electricity

consumption. Using the two-step optimization process of the model IRPsim, cost-saving

potentials at the customer level and changes of profits from the perspective of the involved

utilities will be derived.

Keywords: Business model assessment, Utility, Solar energy, Photovoltaic, Energy transition,

Renewable energy, Municipal energy system modeling

1 Motivation

Today’s persistent challenges like climate change, environmental concerns, energy security

as well as a reduction of energy import dependency, have profound implications on the global

energy landscape [1], [2]. In this regard, Europe’s energy sector is subject to continuous

change resulting from technological advancement, a changing political environment and

market-driven trends towards decentralized energy generation [3]. In the context of the

German “Energiewende”, this market change particularly affects German energy utilities facing

a tremendous erosion of their revenues as a result of dwindling power prices and ongoing

trends towards renewable energies and decentralization of the energy system [4], [5]. It “is

clear [..] that business as usual is no longer an option.” (Klose et al. 2010, p.4). The utility

incumbents have yet failed to adapt to and to benefit from this transition [6]. It is argued though

1 Jungautor, Gerhardtstraße 3, 10557 Berlin, 0163-7322291, [email protected]


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that, from a societal perspective, particularly municipal utilities are already decisive drivers and

could be crucial for the success of the energy transition [6], [7], [8]. With their predominant role

as capital-intensive, infrastructure-experienced actors they might be a crucial partner to “scale

up emerging energy products or services.” (Fratzscher 2015, p. 23) [2]. Moreover, while the

current pace of the transition is seen to be insufficient to meet environmental targets [9], a

commercialization of renewable energies could significantly accelerate the system’s

decarbonization [10].

In particular, regional and municipal utilities are predestined to take an active role in shaping

the energy transition, due to their decentralization, their customer relation and embeddedness

in local politics and administration [2], [11]. Moreover, strengthening the energy systems on a

communal level has the potential to increase both regional value and system stability [12], [13].

Despite significant efforts of utilities to define their future role, the main hindrances to

innovation yet prevail: uncertainties within unpredictable policy frameworks, lack of profitability

of projects, insufficient budgets for innovation, and the possibility of expensive mistakes [14],

[15].

“What is the most effective strategic direction for the energy provider of the future? It is a simple

question with no simple answer. The answer depends on regulatory and market environments,

technological capabilities, the size and nature of a utility's consumer base, its internal appetite

for change and its current business portfolio" (Guthridge et al. 2013, p. 38) [16].

Reflecting upon the uncertainty of future prospects, there is a reasonable number of

publications investigating utilities’ options for business model innovation and adaption to the

changing market environment: [6], [17], [18], [19], [20], [21]; to name but a few. Responding to

the acute need to address such task, this research aims to complement the existing up to date

research by shedding light on utilities’ potential business model innovation by means of

thorough qualitative and quantitative analysis of selected business models with regard to

multilevel system objectives.

“Though simulation will never be able to predict the future, it is a way of doing low-risk

experiments, without endangering an organization” (Osterwalder et al. 2005, p. 16) [22].

The focus is therefore on the comparison and thorough assessment of existing innovative

business models with regard to political and economic aspects. Implications will be drawn from

the resulting analysis, along with recommendations as how to strengthen the role of regional

utilities in the energy transition and ensure a sustainable development of the energy sector.

2 Business model characterization

2.1 Business model innovation in the energy sector

Academia and practitioners agree on the disruptive quality of decentralized autarky solutions

for the future energy system [23], [24], [25], [26], [27], [28], [29]. While anticipated profits are

small in decentralized business models due to high transaction costs, the threat of revenue

erosion to utilities represents an obligation to engage in this market [4]. Until recently, tough,

utilities have been rather passive in the PV market [23], neither considering decentralized PV

as an opportunity, nor a threat [6]. However, Richter (2013) particularly stresses the crucial

strategic importance of distributed PV for the future energy system. As technology costs for


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PV are anticipated to further decline and energy prices to potentially increase, many innovative

business models may become profitable in the near future [27]. For an intense expansion and

commercialization of decentralized PV, it is thus a question of the right timing and business

model that will be crucial [18].

2.2 Candidate business models

All business models introduced can be characterized by energy and financial flows, as

illustrated in Figure 1. These schemes will be further elaborated in the following chapters.

Figure 1: Business model schemes of electricity and financial flows

In general, the electricity tariffs for end-consumers may consist of three different parts: An

energy rate [€/kWh], a power rate [€/kW x month] and a basic fee per month [€/month].

As indicated in the Reference model of Figure 1, the end-consumer usually consumes grid

electricity (A) and pays the associated energy-dependent rate (1) and the monthly basic fee.

The power-level (P) dependent power rate (2) is uncommon in the residential sector and will

thus not be considered in the present paper. The energy rate consists of various components,

which are depicted for an average household in Table 1.

Depending on the exact characteristics, only some of the above cost components incur for

each unit of electricity consumed in all other business models. The applicable cost components

of each business model are listed in Figure 2, to illustrate their particular saving potential. The

exact derivation of cost components depends on the legal framework and will be elaborated in

the following chapters.

Self-generated electricity (via grid) Grid electricity PaymentSelf-generated electricity

Direct consumption

Self-consumption

Direct marketing

Reference model


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Table 1: End-consumers’ energy rate components (including basic fees), average values as of 2015, given a monthly demand of 3,500 kWh. Amended from [17], figures by [30].

Figure 2: Cost components of all business models in comparison to grid electricity.

2.3 Power self-consumption (SC)

2.3.1 Model Description

The construct of “power self-consumption” (German: Eigenverbrauch, Selbstverbrauch) refers

to a setting of a residential single-family household with a decentralized source of electricity

generation, while the on-site generated electricity allows, at least to some extent, for the

satisfaction of energy needs of the respective house owner. The key driver of this construct is

cost-saving by consuming self-generated electricity compared to grid electricity and feed-in

remuneration in the framework of the Renewable Energy Act (EEG). Due to a decreasing feed-

in tariff, a high domestic consumption rate of generated electricity is desirable [31].

0

10

20

30

Grid electricity Self-consumption

(< 10 kWp)

Self-consumption

(> 10 kWp)

Direct

consumption

(partial EEG levy)

Direct

consumption (full

EEG levy)

Regional Direct

Marketing

Ct

/ k

Wh

VAT

EEG levy

Grid fees

Offshore liability levy

Concession fee

Cogeneration levy

§19 StromNEV levy

Levy for deferrable loads

Electricity tax

Generation costs

PV technology costs

Price component Fees/Taxes incur, if/for Value

[Ct/kWh]

Offshore liability levy

General distribution grid is used

-0.051

Grid fees 6.76

Concession fee 1.66

Cogeneration levy 0.254

§ 19 StromNEV levy 0.237

Levy f. deferrable loads 0.006

VAT Unless small enterprise (§ 19 1 UStG (2015))

Value-added-tax (VAT) of 19% of total costs imposed 4.60*

EEG levy

a) 100% of EEG levy for all grid electricity consumed

b) Partially in case of “Power self-consumption” and “Direct

power consumption”, only if installed capacity > 10 kW

c) Does not incur for self-generated electricity ≤ 10 kW

6.17

(100%)

Electricity tax

Does not incur, if

a) Renewable energy plant used and electricity directly extracted

b) Plant capacity


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From the utility viewpoint, the systems could either be sold or leased to customers for an

attractive price. However, by partly satisfying the end-consumer’s electricity demand, self-

consumption compromises utilities’ conventional business model (‘cannibalisation’-effect) [15].

The electricity and the financial flows of power self-consumption are shown in Figure 1. The

end-consumer can use the self-generated electricity (A) for which he might have to pay the

partial EEG-levy (1). Excess electrical energy will be fed into the grid (B) for a remuneration

(2). The residual demand can be satisfied by grid electricity (C), for which the energy rate

incurs (3). The power rate (P) and basic fee depict monthly payments (4). If the consumer

leases the PV system, a monthly leasing fee incurs (5).

2.3.2 Legal framework

Self-consumption is defined as the consumption of self-produced electricity (1) in the

immediate vicinity of the generation plant, (2) without using the grid, and (3) if the electricity

consumer is at the same time the plant operator (§5 No. 12 EEG 2014) [32].

There are three different forms of power self-consumption models, which can be distinguished

by who is in charge of operating the system, which in turn determines the applicable legal

framework. In the first form, the house owner himself invests in the PV-system (and is at the

same time system operator). As an alternative, a third party like a solution provider can invest

in the PV-system and have it leased by the house owner (second and third form). The important

precondition for the legal case of self-consumption is that the electricity consumer needs to be

the system operator, i.e. needs to bear the economic risk of operating the system. In that case,

only 40% of the EEG levy has to be paid (§ 61 No. 1 EEG 2014) [32] for systems of more than

10 kWp (smaller systems are completely exempt). However, if the plant operator and electricity

consumer are not the same person, the full EEG-levy has to be paid (see model “Direct power

consumption”). See Figure 2 for details.

For the case of purchasing and operating a PV plant, the house owner becomes a taxable

entity as a business. In this paper’s assessment of utility business models, all business models

are treated as regular businesses and are therefore not covered by the regulation for small

businesses (UStG 2015) [33]. This obligates the PV system operator to pay taxes on any

turnover generated, including feed-in remuneration. However, the house owner is eligible for

a pre-tax deduction, saving VAT tax on the PV system itself [34]. In case of small PV systems,

the regulation for small businesses has proven less profitable compared to the conventional

regulation [35].

2.4 Direct power consumption (DC)


The construct of “direct power consumption” (German: Direktverbrauch, Mieterstrom) refers to

a situation similar to “power self-consumption”, with the difference that the plant operator is not

the end-consumer. In practice, this is mostly the case for apartment buildings with several

tenants, where the building owner or an investor wants to supply electricity from a roof PV

system to these tenants, without using the public grid.

In this business model, the utility would be the system owner and the operator, leasing the roof

from the building owner. By this means, building owners (and tenants) are not confronted with


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any investment or leasing costs. From a utility perspective, there are two kinds of legal

relationships in this business model, i.e. building owners and tenants: While building owners

profit from a leasing fee for the roof area, an assumed increase in value and improved image,

tenants can profit from reduced electricity costs. Due to the complex regulatory requirements

in the energy supply, building owners are rarely willing to operate the system themselves,

enabling utilities to step in [31]. As previous surveys found, there are distinct preferences for

direct consumption in residential building types. Particularly new buildings are more attractive

for utilities since their new residents tend to live more consciously and have a higher

willingness to cooperate [36].

The electricity and financial flows are illustrated in Figure 1. The system operator sells the

generated electricity for a fixed, competitive price (1) to the contracted tenants (A1), (A2), (An).

The price (1) will include the partial EEG-levy, which will be transferred (2) to the grid operator.

The excess electricity will be fed into the grid (B), for which the system operator receives a

feed-in remuneration (2). The residual energy demand for tenants will be satisfied by electricity

from the grid (C1), (C2), (Cn), for which conventional electricity costs incur (3). Again, all tenants

might as well be charged (4) for the power level of connection (P1), (P2), (Pn). The utility has to

lease (5) the roof from the building owner. As indicated above, the tenants can freely choose

whether they want to enter into the electricity supply contract with the system owner.


Direct consumption (German: “Direktlieferung”) is defined as the consumption of produced

electricity (1) in immediate spatial proximity of the generation plant, (2) without using the grid,

and (3) if the electricity consumer is not the plant operator.

In contrast to electricity in the power self-supply model, electricity in the framework of direct

consumption was not (partially) exempt from the EEG-levy (§5 No. 12 EEG 2014) [32] for the

incongruence of plant operator and electricity consumer. However, as a reaction to the new

EEG 2016, the Federal Council (German: Bundesrat) has indicated that the model of direct

power consumption should be exempt from the full EEG levy [8]. Likely, the Federal Council’s

recommendation will be considered, so in this paper, a partial EEG levy for the business model

of direct power consumption is assumed. Moreover, any grid related fees and taxes can be

omitted (see Figure 2).

A central element of this business model is the contractual arrangements between the PV

system operator and interested tenants, i.e. electricity consumers, in which the price of

supplied generated electricity per kWh is agreed on. Unlike commercial customers, the

contractual arrangements for tenants can only be fixed for a maximum of two years and –

complying with the liberalized market – each tenant is free to decide whether they want to enter

into the PV electricity contract. Consequently, the metering concept needs to enable tenants’

individual choice of electricity supply contract. To avoid additional billing costs for tenants

entering into the PV contracts, the residual energy demand should be supplied by the new

electricity supplier as well [31].

In the framework of direct power consumption, the plant operator will take on the role of an

electricity supplier in accordance to §5 No. 13 EEG (2014) [32] and §3 No. 18 EnWG (2015)

[37], with resulting guidelines and obligations. As is implemented in the case of decentralized

CHP plants already, the tenants can also form a civil law partnership (German: GbR) and


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operate the PV jointly, supposedly complying with the requirements for power self-supply.

Nevertheless, there are legal uncertainties in the definition of power self-supply of a civil law

partnership solution as well as high contractual and administrative barriers [31], [36].

2.5 Direct power marketing (DM)


The construct of direct power marketing (German: Direktvermarktung) refers to a situation

whereby the generation and the consumption of electricity will take place at different locations,

using the public grid to bridge this distance. Two customer groups are required, while the

excess PV electricity of customer group 1 will be fed into the grid and satisfy the electricity

demand of customer group 2. The utility would take the role of a broker between both parties,

to ensure that all legal requirements are met. Formerly, the same spatial context enabled an

electricity tax discount (§ 9 StromStG). However, as of 2016, this discount can only be granted

if no EEG remuneration is being received at the same time [38] (§ 19 Abs. 1a EEG 2014).

As for the customer with a PV system on his/her roof, the principle of all energy and financial

flows are identical to the business model of self-consumption, elaborated in chapter 2.3.

Instead of feeding excess electricity (B) into the grid, the system operator could also directly

sell the electricity to the second customer group (via the grid), covering parts of their electricity

demand (A1), (A2), (An), and receiving the agreed price for generated electricity (1). The

residual demand of the second customer group would be covered by conventional grid

electricity (C1), (C2), (Cn) associated to conventional electricity tariffs (3), and respective

connection fees (4) in accordance with the power level (P1), (P2), (Pn). Since the system

operator would use the grid to satisfy the electricity demand of the second customer group

(A1), (A2), (An), all grid dependent fees as well as the EEG levy (2) would have to be paid to

the grid operator.

For excess electricity, which is not consumed by the second customer group, the system

operator can receive feed-in remuneration (if eligible) or sell it elsewhere. For any electricity

sold directly, the system operator is eligible to receive a market premium (2), the concept of

which will be explained below.


Direct power marketing (German: “Direktvermarktung”) is defined as the electricity sale (1)

from renewable energy sources to third parties (2) whilst using the grid, (3) unless the electricity

is being consumed in a direct spatial context of the system (§5 No. 9 EEG 2014) [32].

Renewable electricity in this framework is sold to third parties, such as electricity traders, the

electricity exchange or other end-consumers. The electricity supply to other end-consumers,

however, is associated with a number of regulatory obligations [31]. The main distinction to

direct power consumption lies in the grid usage due to different locations, hence all grid

dependent fees incur.

For all new PV systems, which are put into operation after the 01.01.2016, the direct marketing

of electricity is obligatory for all systems ≥ 100 kWp. All other systems (< 100 kWp) are eligible

to either receive a feed-in remuneration for 100% of electricity produced or to directly market

electricity (§ 37 EEG 2014).


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Direct marketing of electricity is commonly established in the electricity spot market [39]. The

financial gap between the spot market price and the hypothetical feed-in tariff can be

compensated by a market premium (§ 19 No. 1 EEG 2014). This market premium also includes

a small management premium of 0.4 Ct/kWh, compensating for additional effort associated

with direct marketing. The system operator of the PV facility will thus avoid any disadvantages

by direct marketing in contrast to a feed-in remuneration [40]. Equation (1) illustrates how the

market premium is determined.

Market premium = Feed-in tariff – Average spot market price (per month) + Management Premium (1)

In order to qualify for a market premium, the electricity sold cannot be labelled as ‘green’ or

renewable electricity, since it has already passed the grid and compensation has been paid (§

19 EEG; § 34 EEG) [41].

Table 2 lists requirements to qualify for this market premium as well as different options for

direct power marketing. In the framework of this paper, only the option of direct power

marketing without label will be further considered.

Table 2: Different options for direct power marketing

Direct power marketing

Without label (as conventional electricity mix)

• ‘Promoted’ direct marketing (§20 EEG 2014)

• Only if remotely controllable (§35; §36 EEG 2014)

• Eligible for Market premium (§19; §34 EEG 2014)

• Not eligible for avoided network tariffs (§18 StromNEV; §35 EEG 2014)

Labelled as “green electricity”

• ‘Other’ direct marketing (§20 EEG 2014)

• Not eligible for market premium (§19 EEG 2014)

• Eligible for avoided network charges (§ 18 StromNEV; § 35 EEG 2014)

Regional direct power marketing (§ 9 StromStG No. 3b)

• Exempt from electricity tax, only if no remuneration (e.g. market premium) received (§19 EEG 2014)

• For PV systems < 2 MW

• If generation and consumption of electricity in spatial context [42]

• Proof of simultaneous generation and consumption [43]

For the business model of direct power marketing, some legal obligations apply, which are

mostly borne by the direct marketer: Reporting obligations to the grid operator, marketing of

excess energy and procurement of residual energy, forecast and scheduling, and others [43],

[31].

Similar to the business model Power Self-Consumption, the PV system purchase will be based

on pre-tax deduction and consequently, the system’s operation will underlie conventional tax

regulations of an entrepreneur. In contrast to feed-in remuneration in the case of Power Self-

Consumption, the market premium received in the case of Direct power marketing is not

subject to VAT taxation [34].

3 Scenario-based energy system modelling

3.1 Assumptions

3.1.1 Scenario definition

Based on content of the World Energy Outlook of 2013 [44], two future scenarios are defined

for the model-based scenario analysis: a green and a fossil scenario, which relate back to the


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‘450 scenario’ and the ‘current policy scenario’ of the above publication. The fossil scenario,

thus, depicts a baseline picture of how the global energy system would evolve if current trends

in energy demand and supply remain unabated. The green scenario, on the other hand,

represents a global energy market scenario that allows for significant chance for a successful

climate change abatement with regard to staying below the global warming target of two

degrees Celsius (2 °C). It thereby depicts a much more transformative scenario with regard to

a decarbonization of the energy system [44].

These two market scenarios will set some of the boundary conditions for the regional energy

system, particularly defining global fuel and CO2-prices and in turn, affecting overall energy

prices. The IEA data will be complemented by German spot market and balancing power price

projections of the Fraunhofer Center Leipzig. Both scenarios will be compared to a ‘Status

Quo’ scenario, using historical data of 2015 as a reference. All scenarios are commonly

characterized by insolation data for Cologne, 2005 and balancing power prices (negative and

positive) of 2015.

The scenarios are individually characterized by German day-ahead spot market [45], [46] and

resulting different retail prices for end-consumers, CO2-emissions of the grid electricity mix

[47], [45], learning factors of PV (see Table 4) and feed-in tariff levels for generated PV

electricity (see Table 3).

In order to determine the electrical load of households, the standard load profile (SLP) in

accordance to the BDEW in quarter-hourly resolution is used [48] and scaled to match the

respective calendar and customer groups. Each public holiday will be treated as Sunday.

3.1.2 End-consumer structure

All scenarios include two customer groups: The first customer group (CG1) are the prosumers,

operating a PV system. The second customer group (CG2) are the reference group, which

solely consume grid electricity, or – in the case of direct marketing – consume CG1’s excess

electricity. Both customer groups have an annual growth rate of 10% p.a. to reflect a customer

growth dynamic. Starting with 250 end-consumers in each group in the year 2015, the

customer groups will have 648 end-consumers by 2025. The following table shows the years

and customer group size.

Table 3: Absolute annual consumer growth [households] and levels of feed-in remuneration [Ct/kWh] (non-weighted). CG – Customer group, FIT – feed-in tariff

Year 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Abs. cons. growth 250 25 27.5 30.3 33.3 36.6 40.3 44.3 48.7 53.6 59.0 CG1 250 275 303 333 366 403 443 487 536 589.5 648.4

Total consumers (CG1 + CG2)

500 550 605 666 732 805 886 974 1072 1179 1297

FIT (Green) 12.4 12.3 12.0 11.7 11.5 11.2 10.9 10.6 10.3 10.0 9.7

FIT (Fossil) 12.4 12.3 12.2 12.0 11.9 11.8 11.6 11.5 11.3 11.2 11.1

3.1.3 Electricity tariffs of end-consumers

Flat and variable tariffs of 2015

The grid electricity flat tariff in the 2015 scenario is given by historical data. For every time step

in 2015, the customer will pay 28.81 Ct/kWh (cf. Table 1).


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To derive a variable tariff for 2015, the cost component ‘Sales & Marketing’ was deconstructed

into the spot market price and the utility margin. The spot market prices of 2015 were extracted

from [46]. Given the average spot market price in 2015 of 3.16 Ct/kWh, the remaining 3.96

Ct/kWh of the ‘Sales and Marketing’ cost component is assumed to be the utility margin. The

variable tariff thus consists of the spot market price of this point in time and the fixed margin of

3.96 Ct/kWh.

Flat and variable tariffs of 2025

To determine the flat and variable tariffs in two scenarios of 2025, all components will be kept

constant except for the spot market prices. This is largely consistent with [49] and in the range

of projections by [50], [45]. As mentioned in chapter 3.1.1, the electricity spot market price

projections for the two scenarios have been provided as hourly values by [45]. The values were

linearized into quarter-hourly values.

Feed-in remuneration in 2025

The feed-in remuneration is fixed for 20 years, while the time of initial operation determines

the respective level of feed-in remuneration. A growing customer base (10% p.a.) results in

new customers starting their initial operation at different years with respective feed-in tariffs.

These different feed-in tariffs will be harmonized among the whole customer group by taking

the weighted average of respective year-dependent feed-in tariff and year-dependent

customers starting initial PV system operation.

Two values of projected PV-based feed-in remuneration in 2035 are extracted from [51], while

the values for the year 2025 were linearly interpolated, yielding to a feed-in remuneration level

of 11.1 Ct/kWh in the fossil scenario and 9.7 Ct/kWh in the green scenario, given in Table 3.

The weighted average for the year 2025 based on the above considerations amounts to 11.4

Ct/kWh for the green and 11.9 Ct/kWh for the fossil scenario.

3.1.4 Technology characteristics

Characteristics of small-scale PV systems

The assumptions about technological characteristics of PV systems are based on [52], and

summarized in Table 4. The assumptions predominantly refer to mono crystalline PV systems.

The average PV system size of apartment buildings has been derived as a conservative proxy

to mean values of projects which have been realized already: [53], [54], [55], [56], [57].

Table 4: Assumptions of technological characteristics of PV systems Value Unit

Lifetime 25 years Average degradation 0.1 %/year

Electricity yield in Germany 150 kWh/m²∙year Average end-consumers system price in Germany [58] 1300 €/kWp

Share of installation costs 15 % Share of O&M Costs 1.7 %

Module efficiency 18 % Average PV system sizes (individual household) 22 m² Average PV system sizes (Apartment buildings) 100 m²

Module area requirements [59] 6.4 m²/kWp Annual learning factor (Fossil 2025 Scenario) -1.6 %/year Annual learning factor (Green 2025 Scenario) -3.6 %/year


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3.2 Municipal energy system model – IRPsim

IRPsim is a bottom-up techno-economic optimization model with a municipal scope, whose

central purpose is the evaluation of new business models in a constantly changing market

environment from the perspective of different actors. In this context, a flexible and modular

structure allows the configuration and optimization of business models in the context of various

energy systems. The specific modules are described by actors, technologies, energy flows,

power measurements, dependencies, tariffs as well as the market and the environment. A

detailed description can be found in [60]. The implementation has been carried based on

GAMS/CPLEX.

Optimization approach

In the center of the techno-economic model is the systematic of mixed-integer optimization.

The structure of the model is characterized by linking functional sets, like sectors, system

components, power metering points as well as market actors that are all coupled with

interdependencies of energy flows, power metering and tariffs. The objective function of the

optimization maximizes the total profit of individual actors’ variable financial flows, while the

operational planning of system components is optimized by a dispatch model.

In the framework of this paper, the model works with a two-step optimization systematic. The

model firstly optimizes from an aggregated customer perspective, determining the residual

energy demand and excess energy supply with all components the customers have regulative

access to. In the subsequent step, the model optimizes all other energy and financial flows

from the company’s perspective, considering all residual energy demand and supply. This two-

step optimization process results in a multi-perspective optimization and attempts to reflect

realistic market conditions. From a conceptual point of view, the idea of a multi-level entity-

oriented optimization approach (which is similar to the two-step approach selected here) has

been presented by the authors in earlier studies [61], [62].

Accounting approach

IRPsim determines the net present value (NPV) of payment series of individual customer

groups as well as business divisions, by the sum of variable and fixed cash flows.

In order to take into account time-dependent investments of a potentially growing customer

group with regard to the annual price degression of PV, the model uses an exceptional

accounting approach. In contrast to the procedure in a simple energy related project

evaluation, not only one investment must be considered at the point of evaluation, but also

further investments at later timeframes. Technological progress will eventually cause prices to

fall. To address this, the model uses a modified annuity approach. Thereby, the technology’s

annuity reflects the price development of the asset as well as the expected constant discount

rate per year. As opposed to the classic annuity method, there will not be a constant annuity

with respect to the single years of technology lifetime but rather – depending on the price

development – a growing or sinking annual amount of depreciation. The approach is described

in detail in [60].


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4 Results

In Figure 3, the annual household costs are depicted for all business models in comparison to

the reference model (Ref.). As can be seen, all models offer a significant cost-saving potential,

while the model of power self-consumption (SC.) seems to be the most cost-saving model,

while all chosen business models reveal cost-saving opportunities for end-consumers.

Deviating costs for the status quo between the green and fossil scenario (cf. (a) Figure 3) trace

back to IRPsim’s accounting approach, reflecting faster declining PV technology costs in the

green scenario, which lead to higher depreciation losses for households. The pattern of future

household costs remains similar to that of the status quo, while as a result of discounting, all

values are significantly decreased from today’s perspective. Self-consumption will maintain an

attractive business model to save annual electricity costs.

Figure 3: Annual household costs in the Status Quo (2015), in the green and fossil scenario (2025) with an annual consumption of 3500 kWh. Future values discounted (4% p.a.).

Figure 3 and Figure 4 illustrate the results of the quantitative evaluation of innovative PV

business models with particular focus on the cost-saving potential from the household

perspective and the change in profits from the perspective of the affected utilities. The potential

cost savings of Figure 3 relate to the potential change in utility profits of Figure 4.

Figure 4: Annual profit potential of business models per household for the Status Quo (2015), green and fossil scenario (2025) with an annual consumption of 3500 kWh/a. Future values discounted (4% p.a.). See Figure 5 for explanations.

-875 €

-1.008 €

-802 €-886 €

-965 €

Ref. SC. DC. DM.

-1.000

-750

-500

-250

0

1 € 2 € 3 € 4 € 5 € 6 € 7 € 8 € 9 € 10

€

11

€

12

€

13

€Potential cost savings (fossil) Potential cost savings (green)

Annual household costs (fossil) Annual household costs (green)

-751 €

-549 €-638 €

-719 €-743 €

-546 €-637 €

-713 €

Ref. SC. DC. DM.

-1.000

-750

-500

-250

0

76 €48 €

132 €

81 €99 €

98 €

154 €

115 €94 €

187 €

115 €

Ref. SC. DC. DM.

0

100

200

300

1 € 2 € 3 € 4 € 5 € 6 € 7 € 8 € 9 € 10

€

11

€

12

€

13

€Potential extra profit (green) Min. profit (green)

Realistic profit level

90 €

50 €65 € 65 €

87 €

48 € 64 € 63 €

60 €

158 €

78 €59 €

152 €

75 €

Ref. SC. DC. DM.

0

100

200

300

Min. profit (fossil) Potential extra profit (fossil)

Future scenarios 2025 Status Quo 2015

c

d f

e g

h i

€/J

ahr

€/J

ahr

Future scenarios 2025 Status Quo 2015

€/J

ahr

€/J

ahr

a

b


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Figure 6 illustrates the most important quantitative

and qualitative evaluation aspects, some of which

will be elaborated upon in this chapter. The

inclusion of these multiple system targets seeks to

take account of the multi-dimensional and

profound nature of the energy transition [63], [64].

A more detailed evaluation of all aspects is given

in [35].

Figure 6: Morphological box as aggregation of most important aspects in the business model evaluation

Power Self-Consumption (SC)

From a utility perspective, the power self-consumption is associated with a substantial

reduction in annual profit. Assuming a profit margin of 6% on the sale or leasing of PV systems,

the expected profit will drop for about 29% in 2015 (cf. (c), Figure 4) and 32 - 33% in future

scenarios (cf. (g), Figure 4) in comparison to the reference model (cf. (b), (f), Figure 4). The

model is associated with high transaction costs, which are confronted with fairly low margins

due to low market entry barriers [65], [66], [67]. Emphasis should therefore be put on

minimizing transaction costs by process standardization, which could be achieved by

outsourcing required processes [68]. White-label providers already offer such services,

handling all processes involved and sharing margins with the utility [69]. Despite these losses,

the model may open the door for additional profits by closer customer interaction, which

Results from quantitative analysis

Results from qualitative analysis

Reference Scenario Power Self-Consumption Regional Direct Marketing Direct Power Consumption

Acceptance

High level of local ownership and

diversity of actors

Increasing level of local ownership and diversity of actors

Moderate level of local ownership and diversity of actors

Low level of local ownership and

diversity of actors

No local ownership and diversity of

actors

Customer retentionVery close customer

relationshipsClose customer

relationshipsCertain degree of

customer interactionLittle customer relationships

No customer relationships

Participation

High level of participation in the energy transition

Increasing level of participation in the energy transition

Moderate level of participation in the energy transition

Low level of participation in the energy transition

No participation in the energy transition

Grid-related return

Distribution of infrastructure costs among all consum.

Distribution of infrastructure among

most cons.

Distribution of infrastructure among

many cons.

Inefficient pricing of infrastructure

Self-enforcing dynamic to

decreasing solidarity

Climate ProtectionHigh CO2-reduction

potentialSignificant CO2-

reduction potentialModerate CO2-

reduction potentialLittle CO2-reduction

potentialNo CO2-reduction

potential

System Stabilization

Sufficient stab. elements, very

smooth grid inter.

Many stabilization elements, smooth

grid interaction

Some stabilization elements, moderate

grid fluctuations

Few stab. elements, distinct fluctuations in grid interaction

No stabilization elements, volatile

fluctations

Autarky High level of autarkyIncreasing level of

autarkyModerate level of

autarkyLow level of autarky No autarky

Utility's profit decreases,

reasonable compet.

Utility's profit decreases, high

competition

Poor Very Poor

Affordability

Consumer can independently save

costs

Consumer can save costs, depending on

utility

Consumer costs stay on current level

Consumers' costs increase

Consumers' costs increase, high level

of dependence

System targetVery Good Good Moderate

Profitability

Utility can increase profit with little

competition

Utility can increase profit but faces

competition

Utility maintains profit and consumer

base

Figure 5: Explanation to Figure 4


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potentially enables cross-selling. In any case, the utility risks to completely lose revenue if they

remain idle, since competitors might take over [70].

From an end-consumer perspective, power self-consumption does indeed exhibit significant

saving potential in comparison to the reference model (Figure 3). Moreover, it enables end-

consumers to participate in the energy transition, take control over electricity costs and foster

environmental protection (Figure 6).

From a system perspective, the model puts considerable pressure on the grid infrastructure in

terms of avoided grid-related return and power fluctuations into and out of the municipal grid.

The system pressure could be compensated by decentralized electrical storages, which will

become increasingly attractive in the future (Figure 6).

Direct Power Consumption (DC)

In the business model of direct power consumption, generated PV electricity is commonly

priced a few cents per kWh below the grid electricity price [31]. Tenants are assumed to pay

2 cents less for the PV electricity than they pay for grid electricity, leading to the above profit

expectations of 154 – 187€ in the status quo (2015) (cf. (d), Figure 4) situation and 152 – 158€

for future scenarios (2025) (cf. (h), Figure 4). This represents a profit increase of 16 – 42% in

the status quo (2015) and a doubling of profit in future scenarios (2025) (217 – 227%, cf. (f),

(h), Figure 4). The main drivers of the improved profit situation are falling technology costs,

which are borne by the utility; and slightly increasing electricity prices, leading to a higher profit

margin. However, these expected profits have to be adjusted for a roof leasing fee as well as

administration costs. Furthermore, the model assumes that all tenants will enter into a contract

with the utility. This is an opportunity to distinctly improve customer relationships, but tenants’

will to cooperate remains uncertain. Stagnating or decreasing grid electricity prices will also

negatively affect the profit. Above all, the business model has been evaluated assuming a

partial EEG levy on generated electricity, which is currently uncertain.

From an end-consumer perspective, the model offers slightly reduced and stable electricity

prices. Moreover, the model introduces the opportunity for tenants to participate in and benefit

from the energy transition despite their lack of property ownership. This might improve a feeling

local identity and acceptance of system transformation (Figure 6).

From a system perspective, however, the business model does put pressure on the

infrastructure by fluctuating grid interaction as well as by inefficient re-financing. In comparison

to the model of power self-consumption, the pressure on grid-infrastructure is less distinct due

to balancing effects associated with a smaller scale PV capacity per household.

Direct power consumption could also ultimately be complemented with a decentralized

storage, significantly releasing pressure on the grid infrastructure. Moreover, further

technologies are potential add-ons, such as heat-pumps or CHP plants for the building.

Direct Power Marketing (DM)

Similar to the model of direct power consumption, a price of 2 cents below grid electricity price

is assumed for PV generated excess electricity of customer group 1 (CG 1). The utility gains

as merger between both CG’s, which is 115€ for the status quo (2015) (cf. (e), Figure 4) and

around 75 - 78€ for future scenarios (2025) (cf. (i), Figure 4). In comparison to the reference

case, this represents a decrease of 13% in profit, for the status quo and future scenarios. If an


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additional electricity tax discount was granted in the case of regional direct marketing, the utility

could gain 128€ in the status quo, and 84 – 87 € in future scenarios (2025). Similar to previous

models, administrative costs are not taken into account yet. Besides, it remains unclear

whether 2 cents are sufficiently incentivizing for two CG’s. On a lower level, the model enables

profit stabilization for the utility and retains customers, which can already be perceived

positively with regard to utilities’ current revenue erosion.

From an end-consumer perspective, the model of direct power marketing exhibits a slight cost

reduction. Depending on whether the utility offers a constant electricity rate or passes on grid-

based electricity price fluctuations, electricity can also be stabilized for end-consumers. It is

another simple way to enhance consumer participation in the energy transition, fostering

acceptance and identification potential, however, with limited perceived impact (Figure 6).

Since the model can only be offered in combination with the two previous models, the pressure

on the grid infrastructure observed is similar to that in Power Self-Consumption. On the other

hand, given an independent evaluation of Direct Power Marketing, the model is associated

with a complete coverage of the infrastructure costs. Moreover, the model incentivizes load

shift behavior using cheap PV electricity once available.

5 Summary and conclusion

The aim of this paper was to characterize and evaluate the potential of innovative PV business

models for municipal utilities with regard to multiple perspectives. The study seeks to stress

the importance of business model innovation in the energy sector and offers important

recommendations as to which business model may be favorable. While as all models revealed

diverse impacts, the model of Direct Power Consumption seems to provide the most significant

benefit to all actors. This particularly relates to the economic aspects (if regulations remain as

assumed) as well as the social and ecologic aspects. All other business models reveal

ambivalent attributes and limited profit potential, but nevertheless comprise significant strategic

relevance. While as the model of Power Self-Consumption demonstrates very positive impacts

on end-consumers’ affordability of electricity supply, it lacks profit potential for the utility.

Despite substantial pressure on the grid infrastructure, it is associated with favorable social

impacts. Even though the model of direct marketing offers less significant economic potential,

it can be regarded as an easy-to-implement business model ensuring beneficial customer

relationships.

In the current transformation towards a decentralized energy system, the important question

for utilities is not only how to increase profits but rather how to limit economic losses. In view

of the latter argument, the PV business models introduced could make an important

contribution to securing utilities’ market access in decentralized PV solutions, improve

customer relationships and enable future cross-selling of related products and services.

Utilities are thus advised to evaluate business models carefully and reflect on their role in the

future energy system, in order to ultimately enhance a successful energy transition.


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Literatur

[1] Klose, Frank; Kofluk, Michael; Lehrke, Stephan; Rubner, Harald (2010): Toward a Distributed-Power World: Renewables and Smart Grids Will Reshape the Energy Sector.

[2] Fratzscher, Susanne (2015): The Future of Utilities: Extinction or Re-Invention? A Transatlantic Perspective. In Heinrich Böll Stiftung.

[3] Haag, Wolfgang; Lang, Volker (2010): "Volksbewegung Energie" - auf dem Weg in die partizipative Energiewirtschaft? In Dow Jones Energy Weekly (6), pp. 9–10.

[4] Richter, Mario (2012): Utilities’ business models for renewable energy. A review. In Renewable and Sustainable Energy Reviews 16 (5), pp. 2483–2493. DOI: 10.1016/j.rser.2012.01.072.

[5] Schlandt, Jakob (2015): Utilities and the energy transition. Clean Energy Wire (CLEW).

[6] Richter, Mario (2013): German utilities and distributed PV. How to overcome barriers to business model innovation. In Renewable Energy 55, pp. 456–466. DOI: 10.1016/j.renene.2012.12.052.

[7] Edelmann, Helmut (2012): Stadtwerke: Gestalter der Energiewende. In Stadtwerkestudie.

[8] Bundesrat (2016): Stellungnahme des Bundesrates zum EEG 2016. Drucksache 310/16: Bundesanzeiger Verlag GmbH (ISSN 0720-2946).

[9] Quaschning, Volker (2016): Sektorkopplung durch die Energiewende. Anforderungen an den Ausbau erneuerbarer Energien zum Erreichen der Pariser Klimaschutzziele unter Berücksichtigung der Sektorkopplung. Edited by University of Applied Sciences (htw) Berlin.

[10] Wainstein, Martin E.; Bumpus, Adam G. (2016): Business Models as Drivers of the Low Carbon Power System Transition. A Multi-Level Perspective. In Journal of Cleaner Production. DOI: 10.1016/j.jclepro.2016.02.095.

[11] Doleski, Oliver D. (2016): Utility 4.0. Transformation vom Versorgungs- zum digitalen Energiedienstleistungsunternehmen. 1. Aufl. 2016. Wiesbaden, s.l.: Springer Fachmedien Wiesbaden (essentials). Available online at http://dx.doi.org/10.1007/978-3-658-11551-7.

[12] Müller, Matthias Otto; Stämpfli, Adrian; Dold, Ursula; Hammer, Thomas (2011): Energy autarky. A conceptual framework for sustainable regional development. In Energy Policy 39 (10), pp. 5800–5810. DOI: 10.1016/j.enpol.2011.04.019.

[13] Spletter-Weiß, Ingrid; Fischedick, Martin (2013): Energiewende kommunal gestalten - und finanzieren. Passende Finanzierungskonzepte und eine Bewertung von EE-Projekten aus Bankensicht. In Der Neue Kämmerer 2013, 2013 (3), p. 12.

[14] Edelmann, Helmut (2014): Nachhaltige Geschäftsmodelle für Stadtwerke und EVU. In Stadtwerkestudie.

[15] Edelmann, Helmut; Fidan, Metin (2016): Digitale Geschäftsmodelle. Digitalisierung in der Energiewirtschaft - Stadtwerkestudie Juni 2016. Edited by EY. Ernst & Young GmbH.

[16] Guthridge, Gregory S.; Burns, Ann V.; Colle, Serge (2013): The New Energy Consumer Handbook. In Accenture. Available online at https://www.accenture.com/

[17] Hillenbrand, Melanie; Scheller, Fabian; Schleich, Joachim (2016): Increasing power self-sufficiency of German households – Implications for energy companies’ business models. In 14. Symposium Energieinnovation Graz/Austria 2016, 2/10/2016.

[18] Nillesen, Paul; Pollitt, Michael; Witteler, Eva (2014): New Utility Business Model: A Global View. In : Distributed Generation and its Implications for the Utility Industry: Elsevier, pp. 33–47.


Seite 17 von 20

[19] Engelke, René; Graebig, Markus (2013): Der Status Quo innovativer Geschäftsmodelle bei Energieversorgern. In Energiewirtschaftliche Tagesfragen 63 (11), pp. 2–4, checked on 10/27/2015.

[20] Pätäri, Satu; Sinkkonen, Kirsi (2014): Energy Service Companies and Energy Performance Contracting. Is there a need to renew the business model? Insights from a Delphi study. In Journal of Cleaner Production 66, pp. 264–271. DOI: 10.1016/j.jclepro.2013.10.017.

[21] Schwieters, Norbert et al. (2014): The road ahead: Gaining momentum from energy transformation. In PWC.

[22] Osterwalder, Alexander; Pigneur, Yves; Tucci, Christopher L. (2005): Clarifying Business Models: Origins, Present, and Future of the Concept. In Communications of the Association for Information Systems 16 (1).

[23] Schoettl, Jean-Marc; Lehmann-Ortega, Laurence (2011): Photovoltaic business models: threat or opportunity for utilities? In Robert Wuebker, Rolf Wüstenhagen (Eds.): The handbook of research on energy entrepreneurship. Cheltenham, UK, Northampton, MA: Edward Elgar, pp. 145–171.

[24] Edelmann, Helmut (2015): Gewohnte Wege verlassen. Innovation in der Energiewirtschaft. In Stadtwerkestudie.

[25] Confais, Eric; Fages, Emmanuel; van den Berg, Ward (2015): Solar PV. could be similar to the shale gas disruption for the utilities industry. In Roland Berger - Think Act.

[26] Frantzis, L.; Graham, S.; Katofsky, R.; Sawyer, H.; (Keine Angabe) (2008): Photovoltaics Business Models. National Renewable Energy Laboratory - US Department of Energy. Available online at http://www.nrel.gov/docs/fy08osti/42304.pdf, checked on 12/6/2015.

[27] Schillig, Ivo (2013): Die Energiewende und ihre Implikationen für Energieversorgungsunternehmen. Dissertation. University of St. Gallen, St. Gallen.

[28] Bower, J. L.; Christensen, C. M. (1995): Disruptive technologies. Catching the wave. In Long Range Planning 28 (2), p. 155. DOI: 10.1016/0024-6301(95)91075-1.

[29] Sioshansi, Fereidoon P.; Weinberg, Carl (2014): Lessons from Other Industries Facing Disruptive Technology. In : Distributed Generation and its Implications for the Utility Industry: Elsevier, pp. 141–162.

[30] BDEW (2015): Strompreisanalyse März 2015. Edited by Bundesverband der Energie- und Wasserwirtschaft e.V. (BDEW).

[31] Grundner, Christian; Baez Morandi, María Jesús; Wörlen, Christine (2014): Investorenleitfaden Photovoltaik. Marktübersicht und Praxishilfe zu PV-Geschäftsmodellen in Deutschland. Berlin.

[32] Federal Ministry of Justice and Consumer Protection (2014): Erneuerbare-Energien-Gesetz 2014. EEG 2014.

[33] UStG (2015): Federal Ministry of Justice and Consumer Protection - Umsatzsteuergesetz (UStG). UStG, revised 2015

[34] BLfS (Ed.) (2015): Hilfe zu Photovoltaikanlagen. Bayerisches Landesamt für Steuern (BLfS). Available online at http://www.finanzamt.bayern.de/Informationen/Steuerinfos/Weitere_Themen/Photovoltaikanlagen/Hilfe_fuer_Photovoltaikanlagen_2015.pdf, checked on 8/18/2016.

[35] Seim, Stephan (2016): Assessing municipal business models in the energy sector with respect to political & utility-related targets: a model-based multilevel scenario analysis. Master's thesis. University of Leipzig, Leipzig. Institute for Infrastructure and Resources Management.


Seite 18 von 20

[36] Hillenbrand, Melanie (2015): Increasing power self-sufficiency of German households - Implications for energy companies' business models. Master's thesis. Universität Leipzig, Leipzig. Institute for Infrastructure and Resources Management.

[37] Federal Ministry of Justice and Consumer Protection (2015): Energiewirtschaftsgesetz 2015. Available online at https://dejure.org/gesetze/EnWG, checked on 3/15/2016.

[38] Herms, Manuela; Richter, Christoph (2016): Strommarktgesetz in Kraft! - EEG-Förderung weg? Doppelförderungsverbot rückwirkend zum 01.01.2016 in Kraft getreten. Edited by MASLATON Rechtsanwaltsgesellschaft mbH.

[39] Battaglia, Manuel; Meyer, Markus (2014): EEG 2014 - Was ändert sich zum 1.8.2014 für die Photovoltaik? Edited by Bundesverband Solarwirtschaft e.V. (BSW Solar).

[40] Next Kraftwerke (Ed.) (2014a): Direktvermarktung von Strom - was ist das? Available online at https://www.next-kraftwerke.de/wissen/direktvermarktung, checked on 4/2/2016.

[41] Hölder, Daniel (2014): Geschäftsmodelle zur (regionalen) Direktvermarktung von EEG-Strom. Ein Bericht aus der Praxis. Edited by Clean Energy Sourcing (Clens). Available online at http://www.clens.eu/fileadmin/Daten/Mediathek/Termine/141017_EWeRK_Gruenstrom vermarktung_Hoelder_v1.pdf, checked on 4/4/2016.

[42] Fuchs, Thomas (2004): Federal Fiscal Court (BFH), Decision of 20. 4. 2004 – VII R 44/03 (German). Available online at http://lexetius.com/2004,1641, checked on 3/21/2016.

[43] Next Kraftwerke (Ed.) (2014): Regionale Direktvermarktung - was ist das? Available online at https://www.next-kraftwerke.de/wissen/direktvermarktung/regionale-direktvermarktung, checked on 4/2/2016.

[44] IEA (2013): World energy outlook 2013. Paris: International Energy Agency (World Energy Outlook).

[45] Fraunhofer IMW (Ed.) (2016): Scenario-dependent electricity spot market price projections for Germany, 2025; specific CO2-emissions of grid electricity mix in 2025.

[46] EPEX SPOT (Ed.) (2016): EPEX SPOT SE: Day-Ahead Auction. DE/AT (Phelix). Available online at https://www.epexspot.com/en/market-data/dayaheadauction/auction-table/2015-01-01/DE/24, checked on 7/16/2016.

[47] Statista GmbH (Ed.) (2017): CO2-Emissionsfaktor für den Strommix in Deutschland bis 2015 | Statistik. Available online at https://de.statista.com/statistik/daten/studie/38897/ umfrage/co2-emissionsfaktor-fuer-den-strommix-in-deutschland-seit-1990/, checked on 1/12/2017.

[48] NEW Netz GmbH: Lastprofile. NEW Netz GmbH. Available online at https://www.new-netz-gmbh.de/stromnetz/netzzugang/lastprofile/, checked on 7/9/2016.

[49] BMWi (Ed.) (2014): Entwicklung der Energiemärkte - Energiereferenzprognose. Prognos AG; Energiewirtschaftliches Institut an der Universität zu Köln (EWI); Gesellschaft für Wirtschaftliche Strukturforschung mbH (gws) (Projekt Nr. 57/12).

[50] Öko-Institut (2015): Die Entwicklung der EEG-Kosten bis 2035. Wie der Erneuerbaren-Ausbau entlang der langfristigen Ziele der Energiewende wirkt. Edited by Agora Energiewende. Available online at https://www.agora-energiewende.de/fileadmin/Projekte/2015/EEG-Kosten-bis-2035/Agora_EEG_Kosten_2035_web_05052015.pdf, checked on 7/16/2016.

[51] Agora Energiewende (Ed.) (2016): Online EEG-Rechner. Available online at https://www.agora-energiewende.de/de/themen/-agothem-/Produkt/produkt/130/Online+EEG-Rechner/, updated on 7/6/2015, checked on 8/15/2016.

[52] Wirth, Harry (2016): Aktuelle Fakten zur Photovoltaik in Deutschland. Edited by Fraunhofer ISE. Freiburg.


Seite 19 von 20

[53] BEA (Ed.) (2016): Mieterstrom aus Erneuerbaren Energien: BEA Kiezstrom aus Photovoltaik. With assistance of Oliver Zernahle. Berliner Energieagentur (BEA).

[54] hessenEnergie (Ed.) (2016): Wirtschaftlichkeit von Mieterstrom aus Kraft-Wärme-Kopplung und Photovoltaik bei unterschiedlichen Betriebskonzepten. With assistance of Meixner, Horst. hessenEnergie Gesellschaft für rationelle Energienutzung mbH.

[55] Berliner Stadtwerke GmbH (Ed.) (2016): Berliner Stadtwerke GmbH. Mieterstromprojekte. Available online at http://www.energieverein.org/docs/201604/03_20160411_Andreas_Irmer_Stadtwerke_Berlin.pdf, checked on 8/19/2016.

[56] GERTEC GmbH (Ed.) (2015): Mieterstrom als Geschäftsfeld für die Wohnungswirtschaft? Eine Haltungsfrage. Überlegungen zum Aufbau eines möglichen neuen Geschäftsfeldes für die Wohnungswirtschaft. With assistance of Andreas Hübner. Available online

[57] Ullrich, Sven (2014): Solarstrom für Mieter. Riesenpotenzial für Städte. In Erneuerbare Energien, 2014. Available online at http://www.erneuerbareenergien.de/solarstrom-fuer-mieter/150/3882/78586/2, checked on 8/19/2016.

[58] Mayer, Johannes N. (2015): Zukünftige Kosten der Photovoltaik bis 2050. Langfristszenarien zu Marktentwicklung, Systempreisen und Stromgestehungskosten. Edited by Fraunhofer ISE.

[59] Rech, Bernd; Elsner, Peter (Eds.) (2016): Photovoltaik. Technologiesteckbrief zur Analyse "Flexibilitätskonzepte für die Stromversorgung 2050". Nationale Akademie der Wissenschaften Leopoldina acatech - Deutsche Akademie der Technikwissenschaften Union der deutschen Akademien der Wissenschaften (Energiesysteme der Zukunft).

[60] Scheller, Fabian; Burgenmeister, Balthasar; Wellnitz, Patrick; Kondziella, Hendrik; Bruckner, Thomas (2016): Geschäftsmodellanalyse kommunaler Energieversorger im liberalisierten Energiemarkt - Problemformulierung und Modellentwicklung. 14. Symposium Energieinnovation Graz/Austria.

[61] Morrison, R.; Wittmann, T.; Bruckner, T. (2004): Energy Sustainability through Representative Large-Scale Simulation: The Logical and Physical Design of xeona. In Proc. of the Inter-national Conference on Sustainability Engineering and Science (ICSES), Auckland, New Zealand 2004, 7/6/2004. Available online at http://www.nzsses.org.nz/conference/ConfManuscripts.cfm.

[62] Morrison, R.; Wittmann, T.; Heise, J.; Bruckner, T. (2005): Policy-oriented Energy System Modeling with 'xeona'. In Proc. of ECOS 2005 (18th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems): Shaping our Future Energy Systems, Trondheim, Norway, 6/20/2005, pp. 659–667

[63] Geels, Frank W. (2011): The multi-level perspective on sustainability transitions. Responses to seven criticisms. In Environmental Innovation and Societal Transitions 1 (1), pp. 24–40. DOI: 10.1016/j.eist.2011.02.002.

[64] GRI (2013): G4 Sustainability Reporting Guidelines. Reporting Principles and Standard Disclosures. Edited by Global Reporting Initiative (GRI).

[65] Meyer-Delpho, Florian (2013): Greenergetic GmbH: Online-Shopping für Fotovoltaikanlagen. Edited by GoingPublic Media AG. Available online at http://www.vc-magazin.de/allgemein/greenergetic-gmbh-online-shopping-fuer-fotovoltaikanlagen/, checked on 9/12/2016.

[66] Solarpraxis AG (Ed.) (2014): 15. Forum Solarpraxis, Programme. Available online at http://neue-energiewelt.de/archiv/konferenzen/konferenz-archiv/15-forum-solarpraxis/programm/index.html, checked on 9/12/2016.


Seite 20 von 20

[67] Fuhs, Michael (2015): Greenergetic sieht steiles Wachstum für Vertrieb über Stadtwerke. In pv magazine, 2015. Available online at http://www.pv-magazine.de/nachrichten/details/beitrag/greenergetic-sieht-steiles-wachstum-fr-vertrieb-ber-stadtwerke_100021196/, checked on 9/12/2016.

[68] Trianel GmbH (Ed.) (2015): TRIANELetter 1. Quartal 2015. Available online at https://www.trianel.com/media/trianel.com/Info/Downloads/TRIANELetter/TRIANELetter_Q1_2015.pdf, checked on 9/12/2016.

[69] Thomas, Torsten (2014): Masse mit Klasse. In Sonne Wind & Wärme (05). Available online at http://www.sonnewindwaerme.de/sites/default/files/sww_0514_026-027_markt_greenergetic_0.pdf, checked on 9/12/2016.

[70] Focht, Peter (2016): Stadtwerke machen sich auf Digitalisierungsweg. Digitalisierung ja - aber wo bleibt das Geschäftsmodell? Vor diesem Dilemma stehen auch viele Stadtwerke. In Energie & Management, 2016 (10).

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