1

Solar Energy’s Potential to Enlighten

Germany’s Electricity Price

Term Paper, spring 2011

Energy Economics an Policy

Nicolas Trinks

ETH Zürich

What happens if German households maximize their potential PV

capacity? What is the potential and how does this affect the costs for

electricity generation?

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Solar Energy’s Potential to Enlighten Germany’s Electricity Market ........................... 1

0. Introduction ............................................................................................................. 3

1. The Technology of Solar Energy ............................................................................ 4

1.1 A long history with an uncertain outcome .......................................................... 4

1.2 High Flexibility at High Costs for Low Impact – Who is interested? .................. 5

1.3 Shedding Light on the Costs of PV ................................................................... 7

2. Germany’s Electricity Market .................................................................................. 9

2.1 Less Fuels, More Electricity .............................................................................. 9

2.2 PV and Households, a Good Match ................................................................ 10

3. The Potential of Solar Energy in Germany ........................................................... 11

3.1 Peak Loads – PV’s Future .............................................................................. 11

3.2 Too Many Rooftops for too Little Peak Loads ................................................. 13

4. Enlightening the Electricity Costs ......................................................................... 14

4.1 What Would It Look like Today?...................................................................... 14

4.2 Growing Over Time – PV on Its Way to Supply Peak Loads ........................... 16

4.3 25 Years of Receiving after One Investment ................................................... 17

5. Conclusion ............................................................................................................ 19

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0. Introduction

Solar energy is one of the renewable energy technologies that we like to imagine as

one of the future main sources of our electricity. According to Nozik (2004), it is even

the most appropriate solution to provide the energy supply needed in the coming

decades because of its theoretical and practical potential. But despite the constant

development and the emergence of new technologies in this area, its high prices and

altering political conditions evoke different perspectives.

Some governments, especially in Germany, have already implemented incentives

which yielded in a generation of about 0.1 % of world’s electricity supply in 2010

according to IEA’s technology roadmap 2010. The same author proposes 11 % of

total energy consumption provided by solar energy in 2050. The realization of such

projects would require immense dimensions in terms of financing and collaboration in

R&D and coordination on an international level.

In order to give an example for the potential of solar energy with an economic point of

view, we analyze its feasibility and its impact on the electricity market in Germany.

Remark: if not explicitly stated otherwise, the presented numbers are taken from

Deutsches Statistisches Bundesamt (DESTATIS).

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1. The Technology of Solar Energy

1.1 A long history with an uncertain outcome

Solar Energy, synonymously named Photovoltaic (PV), is actually an old technology

which first served to make our satellites operate in space. Its high cost and relatively

low efficiency made it unattractive for large-scale use for decades. But with

increasing R&D and production, the prices went down as it is shown in fig.1. Here,

the double logarithmic scale indicates an average learning rate of about 20 %, which

is “an often-used best estimate future cost reduction potential for a variety of (energy)

technologies” (Zwaan 2003, 27). According to the WEA (2000) this rate is expected

to continue over the years to come, from a technological point of view.

20 % Learning Curve for Si-based PV

Fig.1: Double logarithmic scale of price vs. cumulative production (Zwaan, 2003)

In the same time, the efficiency went up; a process which is supposed to continue

especially for emerging technologies. The expected efficiencies for the already well-

established technologies are shown in tab.1

R&D is expected to maximize efficiency

Technologie 2010-2015 2015-2020 2020-2030

sc-Si 21 23 25

mc-Si 17 19 21

a-Si/a-Si-μ-Si 10 12 15

CIS/CIGS 14 15 18

CdTe 12 14 15

Tab.1: expected efficiencies for current standard PV technologies

(IEA, Energy Roadmap 2010)

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The efficiency tells about how much of the incident light energy is converted into

electricity. The Shockley-Queisser limit assumes a theoretical maximum of about

31 % for the current standard technologies.

Currently c-Si, which is the general expression for single crystalline (sc-Si) and multi-

crystalline (mc-Si) modules, represents 85-90 % of the global market. They are also

known as first-generation PV. The second-generation PV, thin films like a-Si, µ-Si

and blends of other semiconductors e.g. Cadmium and Copper, account for 10-15 %.

Organic Photovoltaic (OPV) is about to enter the market for built-in applications as

several companies have announced to launch production by using roll-to-roll

methods. Low costs are expected for modules providing 10 % efficiency; 8 %

efficiency has been achieved recently by the Heliatek GmbH, for instance. This

technology and Dye Sensitized Solar Cells (DSSC) are the third-generation PV.

In order to decide among those technologies a trade-off decision between cost and

efficiency has to be made. It also involves considering the energy payback time

required for its specific use. C-Si needs obviously more energy in production than

thin films or a-Si as they need more or purer Silicium. OPVs, on the other hand, need

little energy as their active layers contain organic polymers or oligomers whose

syntheses do not require high temperatures or energy intensive steps. Depending on

the technology, Fthenakis (2006) assumes 1.0-2.7 years until the energy used during

the whole life cycle is gained back by the module. The life cycle starts with the

acquisition of the raw materials and ends with the disposal of the modules.

1.2 High Flexibility at High Costs for Low Impact – Who is interested?

The diversity in technology matches the diversity in applications – Photovoltaic is a

very flexible energy source. They can work in off- or on-grid systems, on residential

or commercial buildings as well as on large-scale electricity production facilities. Even

applications on accessories like bags and sunshades are being introduced to the

market, mainly using third-generation PV.

So far, on-grid systems are much more frequent than off-grid systems. The latter,

which accounts for 8 % in 2010, is typically used in less-developed countries where

no grid-connection is provided. By contrast, on-grid systems experienced an

immense growth with an average annual growth rate of 40 % within the last decade

which was spurred by governmental incentives mainly in Germany, Spain, Japan and

the US. Fig. 2 and 3 show this evolution and thus the dependency of PV on political

instruments.

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On-grid Extension in Subsidizing Countries

Fig.2: Global cumulative installed capacity (IEA, Energy Roadmap2010)

80 % of World’s PV Comes from 4 Countries

Fig.3: Development of world’s PV capacity according to their origin

(IEA, Energy Roadmap 2010)

The character of PV determines its application. Off-grid systems for instance make

more sense in remote areas where power lines are not economical. In big city

centers, the higher population density and therefore the limited space for modules

reduce PV’s potential whereas smaller towns and villages offer a big potential for

extensions. Further, very high efficiency c-Si modules do not make sense in

applications, where no high irradiation occurs. OPV modules would be more suitable

as they also work with scattered light.

The IEA gives one possible scenario for the future development of PV from a global

point of view, taking an adequate and efficient spreading over the different sectors

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into account. The scenario is presented in fig.4. Although losing some shares,

residential use (< 20 kW) is expected to keep its first position. This makes sense, as

Zwaan (2003) found that the hours during which solar panels generate electricity

matches the hours when electricity prices are highest – especially in summer, when

air conditioning runs. Commercial use (< 1 MW) is similar to residential use and only

differs in size due to the bigger size of commercial buildings. But Large-scale PV

applications (> 1 MW) will play a major role as well. They are supposed to materialize

in the world’s sunniest regions like the deserts of Sonora, Sahara, Negev, Thar, Gobi

and Sandy which the IEA’s Photovoltaic Power Systems Programme (PVPS)

proposes in its “Energy from the Desert” project. Off-grid applications, as mentioned

above, will have to be extended in remote areas and in developing countries.

Confidently Aiming at 11 % Solar Energy

Fig.4: IEA’s project for the development of world’s PV Solar Energy with reference to

the different sectors (IEA, Energy Roadmap 2010)

1.3 Shedding Light on the Costs of PV

The feasibility of a technology is one thing, the competitiveness from an economic

point of view and the possible alternatives are another. As Fig. 2 and 3 allude, PV is

currently not competitive and needs political incentives.

Typically, the performance of PV is given in kWh/kWp. “Watt peak” (Wp) indicates the

nominal power of PV devices under laboratory conditions such as a cell temperature

of 25 °C, an irradiation intensity of 1000 W/m2 and an airmass of 1.5. In Germany,

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values of 800-1200 kWh/kWp are frequently measured for c-Si PV. In the desert of

Sahara, for instance, values of 2270 kWh/kWp are measured. Usually, prices of

modules are given in € or USD / Wp which allows to compare different technologies

on a nominal basis. But it only tells about the potential efficiency and therefore one

cannot infer a price for electricity from this data. Setting a general price for Solar

electricity is basically not possible. There are too many factors which yield into

different prices depending on the region, date of purchase (of the PV module),

technology and sector. The IEA (2010), for instance, assumes for the year 2008

generation costs of USD 36-72 cents/kWh for residential use, USD 30-60 cents/kWh

for commercial use and USD 24-48 cents/kWh for the utility sector, depending on the

irradiation (between 2000-1000 kWh/kWp).1

C-Si module prices in Germany were 1.61 €/Wp in March 2011 (a price drop of about

50 % since January 2009). The price per kWh further depends on the PV module’s

lifetime and the interest rate as emphasized in fig.5.

Fig.5: Cost for electr icity (y-axis [c/kWh]) generated by Solar modules in dependence

on interest rate(x-axis [%])

Current PV modules last for 25 years and need about 1.5 % operations and

maintenance costs (O&M), data which fig.5 is based on, and we assume 1 kWh/a per

Wp installed. The IEA uses an interest rate of 10 % which would yield in about 70

cent/kWh (€).

Basically, the aim for any energy technology is to achieve grid parity, which means a

price that equals the price at which private end-consumers purchase their electricity.

In March 2011, German private end-consumers paid 23.7 cents per kWh. An interest

rate of 5,3 % would be necessary to achieve grid parity under those conditions or a

price of 0.54 €/Wp. Considering the 40 % global growth rate of the global PV

1 These values are based on an interest rate of 10 %, a technical lifetime of 25 years and operations

and maintenance costs of 1 %.

6

16

26

36

46

56

66

76

10 9 8 7 6 5 4 3 2 1 0

Interest rate matters

cent/kWh

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capacity, the learning rate of 20 % and 2008’s capacity of 15 MWp, Solar electricity

will be competitive in Germany with today’s grid prices at the beginning of 2018. As

electricity prices are raising and modules become more efficient and more durable,

an earlier date could be expected – especially if a reduced interest rate is applied.

Almost the whole cost for electricity generated by PV has to be done at one time

because the operational costs barely cause capital expenditure. This is a very

specific characteristic of Solar energy.

2. Germany’s Electricity Market

In order to be able to estimate the potential for Solar energy in Germany, we first

have to look at the evolution of the market.

2.1 Less Fuels, More Electricity

Germany’s energy consumption (primary energy consumption) has been relatively

stable for almost two decades although its GDP has risen by an adjusted average

rate of 1.5 % per year (Fig.6).

Germany Grows Energy-Conscious

Fig.6: Germany’s nominal GDP(BIP) and nominal primary energy consumption (PEV)

1991-2008

(DESTATIS, Energie auf einen Blick 2009)

The primary energy consumption amounts to almost 4 000 TWh in 2008, 44 % of the

costs for this amount of energy are due to electricity. The overall electricity

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generation has risen by 18 % since 1991 to a level of 637.6 TWh in 2008. It has

become more expansive by 56.2 % between 1990 and 2009 (for households).

The electricity price for German end-consumers consists of an increasing amount of

taxes. The actual cost for generation, distribution and license amounts to 15.7 cents

of the 23.7 cents per kWh mentioned above (66 %).

Over time, the resources used for generating electricity have changed as shown in

fig.7.

Shifting to CO2-free Technologies

Fig.7: Germany’s mix for electr icity generation in TWh (left) and in % (right) in 1991

and 2008 (DESTATIS, Energie auf einen Blick 2009)

While nuclear energy remains at a constant level, coal and oil have been partly

replaced by gas and renewable energy sources for generating electricity. The latter

amounts to 10.3 % of the total energy production in 2010, or 16 % of the provided

electricity in 2009. Solar energy remains rather insignificant with a share of roughly

1 % of the total electricity generation in 2008.

2.2 PV and Households, a Good Match

According to the IEA, 60 % of the Solar energy comes from residential applications,

from a global point of view. We therefore have a look at the energy situation of

German households: Electricity is the main energy consumer in Germany (44 % of

the energy costs come from electricity) and the share of the population’s income

spent on energy for their households has risen by 80 %, which is significantly more

than the consumer price index’ increase of 17 %.

While households use less fossil energy carriers like coal, oil or gas by choosing

cheaper firewood and wood-pellets in order to heat up their rooms, their consumption

of electricity has risen by 8 % between 2000 and 2007. Households consume about

28 % of the total electricity in Germany. The increased electricity consumption of

households is expected to continue as the number of households and their technical

equipment increase. The number of households has risen by almost 14 % since 1991

0 50 100 150 200

brown coal

nuclear

hard coal

gas

wind

hydro

mineral oil

other

1991

2008

0 20 40

mineral oil

gas

hard coal

nuclear

brown coal

renewable

1991

2008

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to a level of 40.2 Million in 2010; a level of 41 Million is expected for the upcoming

two decades. This development is mainly due to the growing number of one-or two-

person households which obviously use more energy per capita than three-or four-

person households, for instance. It is worth noting that the enhanced consumption is

not significantly influenced by the growth of the population that has only grown by 2.9

% between 1990 and 2009.

3. The Potential of Solar Energy in Germany

3.1 Peak Loads – PV’s Future

The increasing demand of households for electricity and its prices combined with the

match of hours during which Solar modules generate most of their electricity and high

electricity prices indicate a considerable potential for residential PV. The higher

prices during those hours of peak load are due to the increased demand and the

necessity to generate additional electricity. The supply of this short additional

electricity causes higher marginal costs. Fig.8 emphasizes the fact that prices for

generating peak loads are higher than those for the base loads. It shows the

development of average annual prices (in €/MWh) at the European Energy Exchange

(EEX) Leipzig for peak loads (Spitzenlaststrom, light blue) and base loads

(Grundlaststrom, dark blue) between 2000 and 2009. During this period, peak loads

were by an average of 25 % more expensive than base loads (median is 24 %).

Peak Loads cost 25 % more than Base Loads

Fig.8: Evolution of prices of peak and base loads at the EEX in Leipzig from 2000 -2009

(DESTATIS)

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On the other hand, this characteristic of Solar energy, the dependency on

intermittent irradiation, limits its competitiveness against many technologies because

it is basically not appropriate for the base or intermediate load generation. Peak

loads are usually provided by low capital intensive and dispatchable sources like

hydropower and gas turbines (gas-or oil-fired) as well as steam turbines. Large coal

based plants do not make sense, basically for the same reason as nuclear power

plants inquire. They are far too capital intensive to be used for peak loads

economically. Fig.9, showing the shares of the different energy sources in MW during

a day (in December 2003), proves the concept of using capital intensive plants like

nuclear energy (Kernenergie, grey), brown coal (Braunkohle, white) and hard coal

(Steinkohle, purple) for the base loads. Here, the merit order applies. It states that the

least expensive plants are the ones which supply the electricity for base loads. At

increased demand those plants are included which cause the fewest additional. The

consequence for Solar energy is, it cannot provide more than about 15 % of the total

capacity, assuming the peak loads account for 10 000 MW (10 GW). 10 GW equals

87.6 TWh/a which would require 87.6 GWp installed PV capacity.2 In summer, the

profile of Fig.9 would like different, the whole level would be at a lower MW number

and the peak load would occur during a shorter period of hours

15 % for Peak Loads

Fig.9: Mix for electr icity generation in 2003 during 24h (Frauenhofer Institut, 2005)

At this point, it becomes obvious that we need technologies that save energy

generated by PV. This way, Solar electricity could produce much more energy than

needed during peak loads and supply it later on which would make higher PV

2 Assumptions: 1 kW = 8,76 MWh/a; 1 MWh/kWp

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capacities possible. There are already existing solutions but their diversity and

technological immaturity would intrude too much complexity and uncertainty into this

study.

3.2 Too Many Rooftops for Too Little Peak Loads

Now that we have seen the role Solar energy can play in the market, we turn to its

physical potential.

Coming back to the residential application of PV, we have to consider the availability

of rooftop area in order to find out its potential. A study by Witzmann (2010) presents

an estimation for its potential. He first defines three different categories of housing

estates in Bavaria: countryside, village and suburb. This study includes farms, which

have a considerable impact on the results of the countryside category. Further,

Witzmann’s study makes numerous assumptions and takes different kinds of rooftops

and the share for Solar thermal systems, into account. The latter reduces PV’s

potential by 34 %. Using an average performance of 150 W/m2, tab.2 presents the

following potentials for each category found by the study:

Housing estate category

Countryside Village Suburb

Average PV potential per house connection

in kWp

25,8

13,9

5,7

Tab.2: Average PV potential per house connection for each category (Witzmann, 2010)

Finally, using the data found in analyzing the situation in Bavaria, Witzmann projects

a potential of 161 GWp for PV applications on rooftops in the whole of Germany,

taking into account his specific, well justified assumptions. Fig.10 shows the potential

for each federal state in GWp. Other references propose comparable potentials, 53-

116 GWp (Kaltschmidt, 1993) and 130 GWp (Quaschning, 2000). Estimating 161

GWp would mean that 10 % (about 17 GWp) of the total potential were materialized

in 2010, assuming that all the Solar energy currently produced comes from PV

applications on rooftops.

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Roofs could provide 25 % of Germany’s electricity

Fig.10:Potential in GWp for each federal state (Witzmann, 2010)

Referring to the 87.6 GWp that is necessary to answer the electricity demand at peak

loads, currently the only feasible application for PV, the potential found by Witzmann

exceeds the necessary capacity by more than 80 %.

4. Enlightening the Costs for Electricity

We have seen that Solar electricity has a higher potential than it can be used at the

moment. In the following, the 87.6 GWp covering the peak loads in 2010 is the power

that is meant to be applied in the scenario for Germany’s electricity market.

4.1 What Would It Look like Today?

Now, we want to see how the realization of the peak loads generated by PV affects

the electricity market. For having a simple first idea, I present an “instant conversion”

which means we look at the theoretical impact the 87.6 GWp has on Germany’s

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electricity market. Without taxes, German’s electricity price for end-consumers would

amount to 15.7 c/kWh, including generation, distribution and license. But this value

still contains the profit of energy providers. A publication by the IEA presents “reliable

information on key factors affecting the economics of electricity generation” (IEA,

Executive Summary, 2004). Based on a 10 % discount rate, it concludes the

following costs for the electricity generation from data of 130 power plants, shown in

tab.3.

Technology cost3 in cent/kWh Cost + transport

Coal 2.5-4.3 (3.4) 6.9

Gas 2.8-4.5 (3.6) 7.1

Nuclear 2.1-3.6 (2.9) 6.4

Wind 3.2-10.4 (6.8) 10.3

Hydro 4.6-7.1 (5.9) 9.4 Tab.3: Costs for electricity generation (IEA, Executive Summary 2004)

The red numbers are the average values that I’m going to refer to. The costs

including the transportation and distribution costs are based on 3.5 c/kWh which is

what German households had to pay in 2009. The values of the right column are now

referred to as the cost for electricity. In this context, the term grid parity gets a

different meaning with regard to the costs for electricity generated by PV. At a 10 %

discount rate (or interest rate), costs amount to 70 c/kWh and would be 73.5 c/kWh if

the distribution and transportation costs were included. This is about ten times more

than what is usual for peak loads which are on an average of 25 % more expensive

than the costs for the base loads like coal and nuclear energy. The costs for

electricity are shown in tab.4. There are three scenarios, both based on the shares

for resources from fig.7:

Share of peak lodas c/kWh

CO2 Reduction 17.1

Cost Reduction 17.0

2008 7.2 Tab.4: calculated costs for peak loads generated by PV with 10 % interest rate

“2008” gives the cost for tab.3 combined with fig.74. “CO2 Reduction” maximizes the

amount of renewable sources (wind, hydro) whereas “Cost Reduction” respects the

merit order; both consist of 15 % PV generated electricity. The difference between

the scenario with peak loads generated by PV and the actual mix for generation is

immense whereas the difference between the last two is minimal which means the

scenario producing less CO2 should be preferred. As seen earlier, interest rate has a

considerable influence on energy prices. Therefore, the “CO2 Reduction” scenario is

presented using a 5 % interest rate for PV only, assuming national institutions

support such investments as the kfw (Kreditanstalt für Wiederaufbau) does, for

3 The publication gives the costs in USD, an exchange rate of 1 € = 1.4 USD is applied.

4 Cost for oil generated electricity are assumed to be the same as for gas and “others“ amount to

estimated costs of 8 c/kWh

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instance5. At 5 %, the cost for electricity would amount to 22.1 c/kWh plus 3.5 c/kWh

(transportation and distribution costs).

Share of peak lodas c/kWh

CO2 Reduction “5 % i.r. PV” 9.4 Tab.5: calculated costs for peak loads generated by PV with 5 % interest rate

4.2 Growing Over Time – PV on Its Way to Supply Peak Loads

The cost of 9.4 c/kWh for electricity generation and distribution is 30 % higher than

the calculated cost for 2008. But taking into account the price of 15.7 c/kWh indicates

the margin with which the suppliers act on the market. This brings us to the next

model. The model shows the potential development of PV in Germany and the

impact over time for households having PV modules on their roofs.

First, we want to see how long it takes to achieve the aim of peak loads entirely

generated by PV (15 % of total electricity supply) while the total demand increases by

1 %6 per annum and PV’s growth is 40 %/a. The result is 5.02 years which means, if

Germany had continued installing PV modules at the current global growth rate in

2010, the aim would have been achieved in the beginning of 2016.

Now, we turn to the changes in costs of electricity, choosing 22.1 c/kWh for PV.

7.2 c/kWh is the average cost of the residual technologies, with reference to tab.4. A

learning rate (LR) of 20 % and a life time of 25 years for the PV modules are

considered.

Fig.11 shows the development, using nominal values for reasons of clarity.

Shift to “sunny” Peak Loads happens softly

Fig.11: Evolution of costs and portion of peak loads generated by PV

5 kfw offers interest rates starting at 3.19 % per annum;

http://www.kfw.de/kfw/de/Inlandsfoerderung/Programmuebersicht/Erneuerbare_Energien_-_Standard/index.jsp 6 1 % is about the average annual increase referring to the 18 % increase between 1991 and 2008,

this percentage also reflects the increase in households demand.

17

The black line indicates the point when the aim is achieved – when 100 % of the

peak loads are generated by PV. At that point, costs for PV have dropped according

to the learning rate to 13 c/kWh. Interestingly, the costs for electricity would only

increase by 6 % to 8 c/kWh, in case the learning rate applies, but by about 32 % to

10 c/kWh if costs for PV remain at the current level. This model does not consider

increases in costs for the residual technologies. The effect would be obviously

positive for the competitiveness of electricity generated by Solar energy.

4.3 25 Years of Receiving after One Investment

As I talk about Solar energy provided by residential applications, the incentives for

the households to invest in PV modules remain to be discussed. The investments

according to the preceding model, starting with costs of 1.61 €/Wp in 2011,

considering the learning rate would amount to the following values in the

corresponding years:

year Billion €

2011 10.9

2012 13.8

2013 17.4

2014 21.9

2015 27.6

2016 0.6 Tab.6: Investments for realization of the project

Today, the German government pays about 31 c/kWh as a feed in tariff and 19

c/kWh for using one’s own Solar generated electricity. But as the government

alludes, it has no interest in investing considerably more money for renewable energy

resources in the future. In the following, I shed light on what private investors can

expect from owning a Solar modules on their roofs. Being pessimistic, no subsidies

are considered, except the reduced interest rate of 5 %.

The advantages of owning a PV system, are that they basically don’t have to pay for

their electricity and they are paid for the amount that they do not consume

themselves because their houses are grid-connected and they supply the surplus to

the market. Possible risks are, for instance, the risk of damage and the absence of

expected profit and thus a risk of capital. And unlike other investments, the PV

system cannot be sold after its life time, or at least for a disproportionately low price

like selling it to be recycled. The only value of this investment lies in generating

electricity which can be sold.

The following model assumes a constant price of 23.7 c/kWh, a discount rate of 5 %

per annum, as usually 1 MWh/kWp and an increase in the households own

consumption of 1 % per annum. The calculation was done on the basis of

Witzmann’s study referring to the three different categories (countryside, village,

suburb). The average household’s consumption was 3690 kWh/a for the “village”

category and 20 % more for “countryside” and 20 % less for “suburb”. “Total profit”

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means profit plus savings. For clarity, savings, (total) profit and (total) profit-

investment are given as cumulative values in order to indicate the year when the

household’s profits gain over the initial investment. An important assumption is that

households are paid 23.7 c/kWh for the electricity that they supply, which means they

do not have to pay taxes or fees to the power companies. The former is more realistic

as the government is expected to not pay feed in tariffs and could express its interest

in less polluting energy sources by renouncing taxes.

If the savings, which means the money that the household does not have to spend

on electricity, are considered, the household makes profit after 4 years in all three

categories (because it is a linear model). Tab.7 serves as an example, showing the

financial value of owning a PV system in the “countryside” category. In this case, a

household earns (being paid for surplus+not paying its own electricity) about 5800 €

each year, after investing 41 500 €.

Saving and Earning Money with PV system on the roof

countryside year 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

capacity [kWp] 25,8

investment [€] 41538 E generation

[kWh] 25800 E generation

[MWh] 25,8 own

consumption [kWh] 4428 4472 4517 4562 4608 4654 4700 4747 4795 4843 4891

residue [kWh] 21372 21328 21283 21238 21192 21146 21100 21053 21005 20957 20909 savings [€] 1049 2059 3030 3964 4862 5727 6558 7357 8127 8866 9578 profit [€] 5065 9879 14454 18802 22934 26861 30593 34139 37508 40710 43752

total profit [€] 6115 18053 35537 58303 86100 118687 155838 197334 242968 292544 345874 profit-

investment [€] -36473 -31659 -27084 -22736 -18604 -14677 -10945 -7399 -4030 -828 2214 total profit-

investment [€] -35423 -23485 -6001 16765 44562 77149 114300 155796 201430 251006 304336 Tab.7: Calculations of a household’s investment in a PV system for the “countryside”

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5. Conclusion

Today, the only potential for Solar energy lies in providing electricity for peak loads,

which amount to 15 % of the generated electricity, because of the immaturity of

cheap energy saving technologies. PV applications on German roofs on the other

hand have a high potential, allowing 25 % of the total electricity being generated by

PV.

“Sunny” peak loads would not necessarily yield in higher electricity prices. Having

peak loads coming from households and not directly from one of the four main power

companies (E.on, RWE, EnBW, Vattenfall) could possibly avoid higher prices: the

costs of Solar electricity affect only slightly the total costs as we have seen in fig.11.

We also have seen the margin of the prices (15.7 c/kWh) which gives space for

introducing more expensive electricity than the current electricity which is generated

at 7.2 c/kWh. Further, if less electricity is supplied directly by the main power

companies, the decreased demand could result in lower prices as well.

And even with receiving of 23.7 c/kWh without any other subsidy but 5 % interest rate

and tax-free selling, the households make profit after 4 years. An investment of about

92 Billion € over 5 years would be necessary to materialize this project.

Enhanced CO2 emissions caused by the increasing electricity demand of households

could be buffered by such a short-term solution. Other renewable resources, like off-

shore wind parks, would require extensions of the circuit lines and take far longer

than the 5 years assumed for this project. The positive environmental impact of

greener energy solutions could avoid future environment-related damage costs which

could be economically more profitable than cheap energy prices (Zwaan, 2003).

20

References

A. Nozik, presentation, 2004.

IEA, Technology Roadmap. 2010. Solar photovoltaic energy.

DESTATIS:

Bundesministerium für Umwelt. 2010. Erneuerbare Energien in Zahlen: national und

internationale Entwicklung.

DESTATIS. 2009. Energie auf einen Blick.

Bundesministerium für Umwelt. 2010. Energie in Deutschland.

Bundesministerium für Umwelt. 2011. Erneuerbare Energien 2010.

Witzmann, Rolf. 2010. Abschätzung des Photovoltaik-Potentials auf Dachflächen in

Deutschland. 11. Symposium Energieinnovation Graz/Austria.

IEA. 2004. Executive Summary.

Frauenhofer Institut. 2005. Gutachten zur CO2 Minderung im Stromsektor durch den

Einsatz erneuerbarer Energien.

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Systems Programme.

van der Zwaan, Bob. 2003. Prospects for PV: a learning curve analysis. Solar Energy

74 (2003): 19-31.

21

Appendix – 4.2 Fig.11