Danish Wind Power Export and Cost

Full text

CEESA (Coherent Energy and Environmental System Analysis) Research Project
Danish Wind Power
Export and Cost
By
Henrik Lund, Frede Hvelplund, Poul A. Østergaard, Bernd Möller, Brian Vad Mathiesen
Department of Development and Planning, Aalborg University, Aalborg, Denmark
Anders N. Andersen
EMD International, NOVI Research Park, Aalborg, Denmark
Poul Erik Morthorst, Kenneth Karlsson, Peter Meibom and Marie Münster
Risø DTU, National Laboratory for Sustainable Energy, Roskilde, Denmark
Jesper Munksgaard
Pöyry Energy Consulting AS, Copenhagen, Denmark
Peter Karnøe
Department of Organization, Copenhagen Business School, Copenhagen, Denmark
Henrik Wenzel,
Institute of Chemical Engineering, University of Southern Denmark, Odense, Denmark
Hans Henrik Lindboe
Ea Energy Analyses, Copenhagen, Denmark

Danish Wind Power
Export and Cost
© The authors
February 2010
Authors:
Henrik Lund, Frede Hvelplund, Poul Alberg Østergaard, Bernd Möller, Brian Vad Mathiesen, Anders N.
Andersen, Poul Erik Morthorst, Kenneth Karlsson, Peter Meibom and Marie Münster, Jesper
Munksgaard, Peter Karnøe, Henrik Wenzel, Hans Henrik Lindboe
Publisher:
Department of Development and Planning,
Aalborg University
Fibigerstraede 13
DK9220 Aalborg
Denmark
Pdf of this study can be downloaded freely from the following link
www.energyplanning.aau.dk/
ISBN 978-87-91830-40-2
Cover photo:
Kristen Skelton
Acknowledgement
This study is part of the research project Coherent Energy and Environmental System Analysis (CEESA),
partly financed by the Danish Council for Strategic Research. The rest has been financed by the
companies and institutions of the authors.
This study has been initiated and conducted solely on the initiative of the authors and involve no
additional financing or involvement by any political or commercial interests.
2

Content
About the authors of this report 4
Abstract 6
Introduction 7
1. Wind Power and Export
1.1 Why is the CEPOS statement on export not correct?
1.2 What is correct then?
1.3 How can more wind power be integrated in the future?
1.4 Conclusions on wind power and export
9
9
14
19
20
2. The Financing of Danish Wind Power
2.1 Why is the CEPOS statement on financing not correct?
2.2 What is correct then?
2.3 Conclusions on the financing of Danish Wind Power
22
22
23
26
3. Can the Danish experience regarding wind energy´s effects on
employment be transferred to the US? 27
Appendix 1:
Statistical analysis of the correlation between wind power and export
Appendix 2: Statistical analysis of the correlation between changes in wind
power and export
Appendix 3:
Wind power and electricity prices
References
30
32
34
36
3

About the authors of this report
This report is written by a group of energy researchers and experts from Danish universities and
independent consultants. The group represents many years of experience within a wide range of expertise
covering academic studies as well as hands on experience with the operation and management of the
Danish energy system.
Aalborg University (Department of Development and Planning)
Dr.Techn. Henrik Lund, Professor in Energy Planning and Editor-in-Chief of Elsevier international
journal ENERGY, is the main developer of the energy system analysis model EnergyPLAN and author of
the book “Renewable Energy Systems” (Academic Press, Elsevier 2010).
Dr.Techn. Frede Hvelplund, Professor in Energy Planning, has a background in economy and social
anthropology, and many years of experience in the analysis and design of energy policy strategies. In
2008, he was awarded the European Solar Prize.
Ph.D. Poul Alberg Østergaard, Associate Professor in Energy Planning, researches large scale integration
of renewable energy from a technical as well as from an organisational perspective. He also has
experience trading electricity on the Nord Pool Market for small and medium-sized power plants.
Ph.D. Bernd Möller, Associate Professor in Energy Planning and Geospatial Analysis, has key
competence within energy systems analysis and their geographical perspective, and is board member of
Samsø Energy Academy, the Danish Renewable Energy Island of Samsø.
Ph.D. Brian Vad Mathiesen, Assistant professor in Energy Planning, is the main author of the technical
and economic analyses behind the two energy strategies of the Danish Association of Engineers, IDA
Energy Plan 2030 and Future Climate Plan 2050.
Technical University of Denmark (Risø DTU, National Laboratory for Sustainable Energy)
M.Econ. Poul Erik Morthorst is Senior Research Specialist in the Systems Analysis Department at Risoe
National Laboratory for Sustainable Energy, the Technical University of Denmark. He has participated in
a large number of projects related to wind power, takes part in several national and international
committees and is member of the board of the Danish TSO, Energinet.dk.
Ph.D. Peter Meibom, Senior scientist in energy system analysis, is one of the main developers of the
Wilmar Planning tool which is widely used for wind integration studies in Europe. He has co-authored
around 50 international papers about modelling of power systems with large shares of wind power.
Ph.D. Kenneth Karlsson, Senior scientist at DTU Climate Centre, working with scenario analysis and the
interaction between macro-economic and energy system models. He has been involved in the Danish
Association of Engineers’s Future Climate Plan 2050 and is at present working on scenarios for the
Danish Commission on Climate Change.
Ph.D. Marie Münster, Research Assistant at the System Analysis Division, recently completed her Ph.D.
in Energy System Analysis of Waste-to-Energy Technologies with focus on flexible use of waste for
energy in energy systems with high percentages of wind power.
Copenhagen Business School
Ph.D. Peter Karnøe, Professor in Innovation, Technology and Market Architectures at Copenhagen
Business School, is an expert on the creation of the Danish wind turbine industry and is co-editor of the
book “Path Dependence and Path Creation”, Lawrence Earlbaum Press, 2001).
University of Southern Denmark
(Institute of Chemical Engineering, Biotechnology and Environmental Technology)
M.Sc. Henrik Wenzel, Professor in Environmental Engineering, is an expert in environmental assessment
in a system perspective with extensive experience in energy systems. Henrik Wenzel was project leader
of the development of the Danish EDIP methodology for environmental assessment of products and
4

systems for which he received the most significant Danish environmental prize, the DADES prize, and
co-received the great Nordic Nature and Environment prize.
EMD International Ltd. (Department of Energy Systems)
Head of Department Anders N. Andersen, in charge of the development of e.g. the modelling software
package, energyPRO, for combined techno-economic design, analysis and optimisation of cogeneration
and trigeneration projects as well as other types of complex energy projects.
Pöyry Energy Consulting AS
Ph.D. Jesper Munksgaard is a senior consultant at Pöyry with special expertise in wind power, energy
policy and energy markets. He is an economist and has a record of more than twenty years of experience
in the energy sector including an extensive list of publications and presentations on different topics within
wind power.
Ea Energy Analyses
M.Sc. Hans Henrik Lindboe is one of the founders and partners in the consultancy and research
company Ea Energy Analyses. In recent years, Hans Henrik has contributed to analyses of the utility
value of investments in the Nordic transmission grid and the economic conditions of integrating large
amounts of renewable energy in the electricity system. He was previously a systems planner with the TSO
in Eastern Denmark.
5

Abstract
In a normal wind year, Danish wind turbines generate the equivalent of approx. 20
percent of the Danish electricity demand. This paper argues that only approx. 1 percent
of the wind power production is exported. The rest is used to meet domestic Danish
electricity demands.
The cost of wind power is paid solely by the electricity consumers and the net influence
on consumer prices was as low as 1-3 percent on average in the period 2004-2008. In
2008, the net influence even decreased the average consumer price, although only
slightly.
In Denmark, 20 percent wind power is integrated by using both local resources and
international market mechanisms. This is done in a way which makes it possible for our
neighbouring countries to follow a similar path. Moreover, Denmark has a strategy to
raise this share to 50 percent and the necessary measures are in the process of being
implemented.
Recently, a study made by the Danish think tank CEPOS claimed the opposite, i.e. that
most of the Danish wind power has been exported in recent years. However, this claim
is based on an incorrect interpretation of statistics and a lack of understanding of how
the international electricity markets operate. Consequently, the results of the CEPOS
study are in general not correct. Moreover, the CEPOS study claims that using wind
turbines in Denmark is a very expensive way of reducing CO
2
emissions and that this is
the reason for the high energy taxes for private consumers in Denmark. These claims
are also misleading. The cost of CO
2
reduction by use of wind power in the period
2004-2008 was only 20 EUR/ton. Furthermore, the Danish wind turbines are not paid
for by energy taxes.
Danish wind turbines are given a subsidy via the electricity price which is paid by the
electricity consumers. In the recent years of 2004-2008, such subsidy has increased
consumer prices by 0.54 €¢/kWh on average. On the other hand, however, the same
electricity consumers also benefitted from the wind turbines since the wind power
decreased the electricity market price on Nord Pool. On average during 2004-2008, such
effect decreased the consumer prices by 0.27 €¢/kWh and consequently the net
influence during this period increased consumer prices by only 0.27 €
¢/kWh equal to
only 1-3 percent of the final consumer prices. In 2008, the net influence of wind power
actually decreased the consumer price slightly by approx. 0.05 €
¢/kWh. Consequently,
the influence of Danish wind turbines on the consumer electricity price is negligible.
6

Introduction
In a normal wind year, Danish wind turbines generate the equivalent of approx. 20
percent of the Danish electricity demand. In 2008, the number was 19.3 percent.
In the report “Wind energy – The case of Denmark” September 2009 [1], the Danish
think tank CEPOS claims 1) that most of the Danish wind power has been exported in
recent years, and 2) that wind turbines in Denmark are very costly to Danish taxpayers
and electricity consumers.
The CEPOS report has been used in the US to cast serious doubt on whether other
countries can learn from the Danish case. Among others, the CEPOS report cites
President Obama:
”America produces less than 3 percent of our electricity through renewable sources of energy like wind
and solar — less than 3 percent. In contrast, Denmark produces 20 percent of their electricity through
wind.”
Relating to this statement, the CEPOS report has been quoted
“to refute the claim that Denmark generates 20 percent of its power from wind stating that its high
intermittency not only leads to new challenges to balance the supply and demand of electricity, but also
provides less electricity consumption than assumed.” [2]
Moreover, the CEPOS report has been used to say that due to wind power
“Danish ratepayers are forced to pay the highest utility rates in Europe.” [3]
But - as will be documented in the following – the CEPOS conclusions are in general
not correct and the above statements are misleading.
1.
The CEPOS study claims on page 2 that wind power “has recently (2006) met as little
as 5% of Denmark’s annual electricity consumption with an average over the last five
years of 9.7%”.
The statement is not correct. This paper argues that approx. only 1 percent of Danish
wind power production is exported. The rest is used to meet domestic Danish electricity
demands, thus implying that wind power meets close to 20% of Danish electricity
consumption.
2.
The CEPOS study claims on page 19 that “a significant fraction of the charges and
taxes paid for by Danish domestic consumers is recycled to support ….. the feed-in
tariffs that make it attractive … to invest in wind power”. (see full citation in section
2.1).
This statement is not correct. No taxes are recycled to support the established wind
turbines
1
and the net influence on consumer electricity prices is as low as 1-3 percent on
average in the period 2004-2008. In 2008, the influence even decreased the average
1
Only with regard to research, development and demonstration are taxpayers involved in payments to
wind power as well as other new technologies. The payment for already established wind turbines is made
by power consumers.
7

consumer price slightly. Moreover, the payment to wind power does not make Danish
electricity prices any higher than those in other countries. In fact, Danish electricity
prices (excl. tax and VAT) inclusive of all payments for 20 percent wind power are
among the cheapest in Europe.
8

1. Wind Power and Export
The CEPOS study claims on page 2 that wind power “has recently (2006) met as little
as 5% of Denmark’s annual electricity consumption with an average over the last five
yeas of 9.7%”.
1.1 Why is the CEPOS statement on export not correct?
We have been able to replicate the calculations of CEPOS by using the same data,
namely hourly production data, which can be downloaded from the website of the
Danish TSO Energinet.dk: www.energinet.dk. By using these data, one can see hour by
hour consumptions and productions divided into 1) wind power, 2) large power plants
(Extraction and condensing plants) and 3) small CHP plants in the two separate supply
areas of Denmark, i.e. east and west.
If one presumes that all export by default is wind power (until the export exceeds the
wind power production), we can replicate the same numbers as the CEPOS study, i.e.
the 5 percent of electricity consumption in 2006 mentioned above. This implies that
CEPOS statement of 5 percent wind power in 2006 must build on an assumption that
export, when present, is by default wind power. For the most recent year, 2008, the
number will, on the same assumption, be 12 percent. However, if one presumes that all
export by default is large and small power stations, the same number is 17 percent in
2006 equal to the total wind power production of that year. In this respect, export of
wind is only as little as 0.01 percent of the demand. The same pattern shows for 2008.
Consequently, the whole claim of the CEPOS study originates from the presumption
that all export by default is wind power.
However, this assumption is not correct, and it builds on an erroneous interpretation of
statistics and a lack of understanding of the Nordic electricity market.
The CEPOS study’s main argument for making the presumption that all export by
default is wind power is that the Danish export of electricity is generally higher during
hours of high wind production than during hours of low wind production. The CEPOS
study shows (on pages 15 and 16) diagrams of such correlation for western Denmark
2007 and eastern Denmark 2006 and concludes the following:
“.. the coincidence of so much wind output with net outflows makes the case for
claiming that there is a large component of wind energy in the outflow, indisputable”.
Based on this argument, the CEPOS study then implicitly presumes that all export by
default is wind power (until the export exceeds the wind power production). However,
the assumption is not correct. As will be shown in the following, one cannot conclude
that this means that all export by default is wind power. On the contrary, almost all
wind power is consumed in Denmark.
We have reconstructed a diagram in Fig. 1 plotting wind power production on the x-axis
and export on the y-axis using data from 2008 for western Denmark. As one can see,
there is a tendency that the higher the wind power production, the higher the export.
9

WindpowerandExport
‐2000
‐1500
‐1000
‐500
0
500
1000
1500
2000
2500
0 500 1000 1500 2000 2500 3000 3500 4000
WindPower[MW]
Export[MW]
Fig 1: Correlation between hourly Wind Power and Export in western Denmark 2008
LargePowerPlantsandExportin2008
‐2000
‐1500
‐1000
‐500
0
500
1000
1500
2000
2500
0 500 1000 1500 2000 2500 3000 3500 4000
LargePowerPlants[MW]
Export[MW]
Fig 2: Correlation between hourly power from Large Power Plants and Export in western
Denmark 2008
However, this is not unique for wind power. This is general for all types of production
units in the Danish electricity system. We have made the same analysis for the Large
CHP and Power plants with the result illustrated in Fig. 2. As one can see, there is no
real difference between the plot of wind power vs. export and the plot of Large CHP vs.
export. Accordingly, one could use more or less the same argument for large power
10

plants as for wind power. In both cases, however, the argument would be wrong. As
shall be shown, the causal relation behind export is more complex and involves
understanding market mechanisms and cost implications of the various power suppliers
on the Nordic grid.
Appendix 1 shows similar diagrams for all production units in the Danish system
divided into 1) Wind turbines, 2) Large power plants and 3) Small CHP plants. The
diagrams show the tendency that high export more frequently takes place during hours
of high wind production than during hours of low wind production. However, the same
is the case for production on both Large and Small CHP’s. For wind power, the
correlation coefficient R is as low as 0.62 and R
2
is only 0.39. Such a correlation is very
poor and cannot justify any conclusion about causal relation. Therefore, none of these
diagrams say anything about the causal relation, i.e. which units cause the export. It is
not possible, based on any of these diagrams, to conclude (as CEPOS does) that all
export by default is caused by wind power.
In order to look for the causal relation, we have also analysed whether changes in export
from one hour to another are derived from wind power more than from other production
units. Such analysis has been made by calculating all hourly changes in wind production
and export during 2008. The results were then plotted x,y in a diagram as shown in
Appendix 2. Moreover, we have made the same diagram for large power plants.
Normally one would require a correlation coefficient resulting in R
2
around 0.9 or above
to conclude that there is a strong correlation between the changes, and even then one
cannot directly interpret correlation as causal relation. In this case, the correlation
coefficient between changes in wind power and import/export is as low as 0.30 (R
2
=
0.09) which is extremely weak. On the other hand, the correlation coefficient between
changes in large power plants and import/export is R=0.65, which is still very weak, but
stronger than the wind vs. export correlation. Therefore, such analysis does not in any
way suggest that changes in import/export are generated by changes in wind power.
Consequently, none of these diagrams showing only correlations over time can be used
to establish a causal relation between wind power and export. On the contrary, they
indicate that wind power in general does not influence export any differently than other
production units.
Moreover, as a general comment, the use of hourly statistics for trying to determine the
impact of wind power on other production units inherently gives a faulty time
perspective. Due to the impact of hydro power with storage capacity it is necessary to
look at longer time spans if one wishes to determine which plants have been affected by
the wind. Another approach can be by looking at marginal costs which will be
elaborated on below.
To establish a causal relation, one has to examine WHY the Danish energy system ends
up exporting or importing electricity. Such causal relation has to do with the
functionality of international (Nordic) electricity markets and how the independent
power generators respond to price incentives. Most export is generated in power plants
for the simple reason that it is financially attractive for the Danish power producers to
generate power and sell it on the international power market. Such export is highly
11

influenced by the fact that Denmark has a lot of CHP rendering fossil-based power
plants competitive to foreign power plants mainly due to the financial advantage of
district heating and the consequential lower marginal cost of operation per kWh of
power.
The following two examples illustrate why the causal relation can only be established
by observing the electricity markets.
Fig. 3 compares two different hours of production in 2008: one hour in January with
significant export taking place and one in March with no export taking place. In both
situations, the production from wind turbines is approx. 1000 MW and the total Danish
consumption is around 3200 MW. The large difference is evident in the production at
the large CHP and power stations. On March 10
th
, the production at these was approx.
1000 MW while on January 5
th
, the production was more than 1900 MW. Moreover, the
production on the small distributed CHP plants was a little higher in March than in
January.
It is obvious that wind power in this situation can hardly explain WHY Denmark chose
to export in January and not in March.
Nevertheless, the CEPOS study calculates as if all export in the January situation is
based on wind power while all the electricity produced at the power plants is used in
Denmark.
5 January 2008, hour 19
(Nord Pool system Price = 386 DKK/MWh)
0
500
1000
1500
2000
2500
3000
3500
4000
4500
Production and consumption
MW
Import
export
consumpt.
large
small
wind
10 March 2008, hour 19
(Nord Pool system Price = 234 DKK/MWh)
0
500
1000
1500
2000
2500
3000
3500
4000
4500
Production and consumption
MW
Impor t
export
consumpt.
large
small
wind
Fig. 3: Consumption and production in two 2008 situations with the same wind power
production but different export figures.
However, if we look at Fig. 3 and examine the contribution of the different generators,
it is clear that large power stations generated much more electricity in the January
situation than in the March situation. In both situations, wind power production was
about 1000 MW as mentioned. Therefore, we infer that the reason for the difference
between the two hours is the financial incentive for mainly the large power stations to
produce (or not produce). The price on the Nord Pool international electricity market
12

was only 234 DKK/MWh on March 10
th
and substantially higher on January 5
th
, namely
386 DKK/MWh. Consequently, the power stations make a profit on exporting in
January but not in March.
Fig. 4 is even more effective at illustrating the ‘causality’ of energy production causing
export from wind power and power plants.
Western Denmark June 14th, 2008
0
500
1000
1500
2000
2500
3000
1 3 5 7 9 11 13 15 17 19 21 23
hour
MW
large plants
Small CHP
Wind
Demand
Fig. 4: Actual Danish electricity demand and production on June 14
th
, 2008.
As one can see, there was no export during the hours 1 to 11 and after 13 on June 14
th
,
2008. There was a small amount of export during the hours between 11 and 13. In the
CEPOS study, this export is by default said to come from wind turbines. However, Fig.
4 shows that there is no evidence to support that.
As one can see, the coal-fired large CHP and condensing mode plants increase their
production in the same period and the system ends up exporting. However, if the large
plants had not increased production, there would be no export. The reason for the large
plants’s production increase during such hours is the financial attractiveness to do so
(the income from the Nord Pool electricity market exceeds the marginal production
costs). The fact that this is a summer situation makes this even clearer as changes in
electricity production are not caused by needs to produce additional heat on the CHP
units.
Looking at the exact Nord Pool Prices of that day, one can see the price increases during
exactly the same hours in which the large power plants increase production and peaks
between 11 and 13 o’clock. Consequently, with the current price mechanism in the
Nord Pool market, it is financially rational for the individual power producers to
increase the production, and the aggregate effect of the increased production is that the
‘system’ starts exporting.
The point is that even though there is a weak correlation over time between wind power
and export, this does not establish a causal relation. The reasons for export have to be
found by observing the market mechanisms of international electricity markets and, as
13

we shall see, such observation shows a causal relation between export and large power
plants but next to no causal relation between export and wind power.
1.2 What is correct then?
First, we do agree with the CEPOS study that the balancing of an electricity system
requires access to balancing and regulating reserves in order to make the system
function, and that Denmark is well-connected to neighbouring countries with
transmission lines. However, as already stated and supported above, we do not agree on
the implicit presumption in the CEPOS study that this means that all export by default is
wind power. Such presumption is not correct.
Denmark is part of an international collaboration in which a large number of European
countries help one another in securing the balancing task e.g. within the supply of
primary automatic reserves. Denmark draws upon the assistance of other countries and
helps them in return. That includes the balancing of wind power in Denmark as well as
in Denmark’s neighbouring countries. One of these countries is Germany, and the
northern region of Germany, Schleswig-Holstein, has more or less the same proportions
of wind power as Denmark.
We do agree with the CEPOS study that when we increase the number of wind turbines
in Denmark, we need more regulating power. However, it is not correct to say - as the
CEPOS study implicitly claims - that this regulating power by default is coming from
Norway and Sweden. Denmark shares a well-functioning regulating power market with
Finland, Norway and Sweden which has the necessary capacity to provide all the up-
and downward regulating power we need in order to operate the system. It is most cost
efficient to handle the regulation in the Nordic power system via a common regulating
power market, analogous to the distribution of primary (frequency) reserves among
countries. However, Danish regulating power resources are used whenever it is most
cost efficient, given the particular mix of energy production technologies in the system
at any point in time and given the present rules for price making in the market.
Moreover, all the costs of operating this regulating power market are included in the
electricity price. When regulation based on Norwegian or Swedish hydro power with
storage capacity is often more cost effective than local Danish regulating resources, the
hydro power will be prioritised in the merit order. Given the present institutional set-up,
this solution is good business for all countries involved, but it says nothing about the
possibility to regulate by use of solely local resources.
What can be said for a fact, and what would be fair to say about the present technology
mix in the Danish energy system, is illustrated here for the year 2008. In 2008, wind
turbines in Denmark produced 6,978 GWh equal to 19.3 percent of the electricity
demand (36,105 GWh).
During a few hours, the wind power production exceeded the demand and the excess
production was exported. However, this happened in only 43 hours and the total excess
production being exported was as low as 5 GWh, equal to less than 0.1 percent of the
wind power production (or less than 0.02 percent of the demand).
14

In other hours, there were either no export at all or the wind production exceeded the
export. In such hours, the share of wind production which exceeded the export would
have to be used domestically – no other outlet for this wind power exists. In 2008, this
domestically used production was as high as 4,398 GWh equal to 63 percent of the wind
power production (or approx. 12 percent of the demand). It should be noted that this
number only includes the share that exceeds the export.
Consequently, one can say for a fact that a minimum of 0.1 percent of the Danish wind
power production in 2008 was exported and a minimum of 63 percent was used in
Denmark.
With regard to the remaining 36.9 percent, one cannot conclude anything from a purely
technical, physical or statistical point of view as illustrated before. In all the remaining
hours, the production was a combination of wind power and electricity production from
large-scale CHP and power plants and small distributed CHP plants, and it is not
possible from a technical, physical or statistical point of view to determine which parts
of this production were exported and which were used domestically. Such question
cannot be answered solely by looking at the correlation over time.
If one should identify whether export in such hours came from one type of production
or another, one would have to establish a causal relation, i.e. explain why and from
which units export is generated. Such causal relation can be established by observing
the international electricity markets on which the import/export is determined.
Denmark is part of the Nordic electricity market Nord Pool on which the electricity
production and price are found as illustrated in Fig. 5.
Fig. 5: Price setting in a marginal cost electricity spot market.
15

Wind power and other categories of electricity generation are offered at the short term
marginal cost of producing electricity on the given unit. For wind turbines this is close
to zero whereas power plants with a fuel use have marginal costs substantially higher.
This creates a notable implication for the power market. By shifting the supply curve to
the right, wind power in fact typically reduces the spot market price in a given hour.
This is for the benefit of consumers but at the expense of the more expensive power
units.
Fig. 6 shows the merit order of marginal production at the Nordic Nord Pool Market.
0
20
40
60
80
100
120
0
50 100 150 200 250 300 350 400 450
TWh/year
EUR/MWh
Hydro (average year)
Nuclear
CHP
Coal
condensing
Peak
capacity
Demand
ETS cost
Wind
Gas
condensing
Fig 6: Merit order of marginal production at the Nordic Nord Pool Market. Source: Pöyry A/S.
Wind power has the lowest marginal production costs in the Nordic power system.
Danish export is possible because Denmark has interconnectors and access to the
international market as illustrated in Fig. 7. Export takes place when the price outside
Denmark is higher than the short-term marginal cost of the Danish units that may
increase production. From a market perspective, it is generally the most expensive
production in Denmark which is exported, as any cheaper production would already
have replaced more expensive production operating to cover the Danish demand. In the
Danish case, these production costs are influenced by CHP production.
16

Fig. 7: Denmark (in box) is situated between continental Europe and the Scandinavian
peninsula. Western Denmark is connected to Germany, Sweden and Norway while eastern
Denmark is connected to Sweden and Germany only. The map also indicates the price areas of
the Nord Pool electricity market area (EUR/MWh). Source:[4]
How export is generated can be explained by observing the example shown in Tables 1
and 2.
In Table 1, there are no interconnectors and hence no export. In such case, the
production in Price area 1 (E.g. western Denmark) will be 2,000 MWh and the price
will be 200 DKK/MWh. Production and price in Price area 2 (e.g. southern Norway)
will be uncorrelated with production and price in area 1. However, in Table 2 there are
interconnectors and thus the possibility of import/export. In this case, the market will
find a situation in which a final price of 350 DKK/MWh is established in area 2 and 275
DKK/MWh in area 1. Thus, it will pay for power plants 2 and 3 to start producing so
that Price area 1 can export to Price area 2.
This example clearly illustrates the market principle that the export is produced on the
unit with the highest bidding price, i.e. the unit with the highest marginal production
costs which in the Danish system is not the wind turbines.
Using a market principle leads to the conclusion that in most cases the units with the
lowest marginal production costs (i.e. wind) are sufficient for domestic demand (i.e. in
Denmark), while the units with the highest short-term marginal production costs (i.e.
thermal units) are in general the ones which enable the export of electricity. Such
17

principle is valid to the point at which the present stock of thermal plants cannot be
decreased further due to the technical operation of the system.
Table 1: Example of a spot trade in a certain hour tomorrow. No connection between the two price areas.
The shaded area indicates the marginal price of the hour and, thus, the marginal supplier unit.
Table 2: Example of a spot trade in a certain hour tomorrow. 1000 MW connection between the two price
areas.
In reference to this analysis, the technical need for power plant production is expressed
in terms of two requirements. It is emphasized that the requirements for operation of the
electricity system are both complex and under constant development. The requirements
presented here serve as illustrative examples:
NordPool Spot
Simple example of spot trade in a certain hour tomorrow
connection between the two price areas
Price area 1 Price area 2
Amount Bidding price Amount Bidding price
[MWh] [DKK/MWh]
[MWh] [DKK/MWh]
ing offer: 2000
Priceindep.
2500
Priceindep.
le offers: Wind turbines 1500 0Power plant 5 500 50
Power plant 1 500
No
Buy
Sa
200Power plant 6 500 100
Power plant 2 500 250Power plant 7 500 350
Power plant 3 500 275Power plant 8 500 400
Power plant 4 500 325Power plant 9 500
435
Power plant 10 500 450
t price of the
our 200 435
Spo
h
NordPool Spot
Simple example of spot trade in a certain hour tomorrow
connection between the two price areas
Price area 1 Price area 2
Amount Bidding price Amount Bidding price
[MWh] [DKK/MWh]
[MWh] [DKK/MWh]
ing offer: 2000
Priceindep.
2500
Priceindep.
le offers: Wind turbines 1500 0Power plant 5 500 50
Power plant 1 500
No
Buy
Sa
200Power plant 6 500 100
Power plant 2 500 250Power plant 7 500 350
Power plant 3 500 275Power plant 8 500 400
Power plant 4 500 325Power plant 9 500
435
Power plant 10 500 450
t price of the
our 200 435
Spo
h
NordPool Spot
Simple example of spot trade in a certain hour tomorrow
00 MW interconnector between the two price areas
Price area 1 Price area 2
Amount Bidding price Amount Bidding price
[MWh] [DKK/MWh]
[MWh] [DKK/MWh]
ing offer: 2000
Priceindep.
2500
Priceindep.
ale offers: Wind turbines 1500 0Power plant 5 500 50
Power plant 1 500 200Power plant 6 500 100
Power plant 2 500 250Power plant 7 500
10
Buy
S
350
Power plant 3 500
275Power plant 8 500 400
Power plant 4 500 325Power plant 9 500 435
Power plant 10 500 450
pot price of the
275 350
S
hour
NordPool Spot
Simple example of spot trade in a certain hour tomorrow
00 MW interconnector between the two price areas
Price area 1 Price area 2
Amount Bidding price Amount Bidding price
[MWh] [DKK/MWh]
[MWh] [DKK/MWh]
ing offer: 2000
Priceindep.
2500
Priceindep.
ale offers: Wind turbines 1500 0Power plant 5 500 50
Power plant 1 500 200Power plant 6 500 100
Power plant 2 500 250Power plant 7 500
10
Buy
S
350
Power plant 3 500
275Power plant 8 500 400
Power plant 4 500 325Power plant 9 500 435
Power plant 10 500 450
pot price of the
275 350
S
hour
18

- The large power units currently in the energy system cannot go below a certain
technical minimum. In 2008, there were hours during which the large units in
western Denmark were operated at only 415 MW and in eastern Denmark only
181 MW. Consequently, it could be argued that the system technically can be
operated with such minimum production, and that everything above this is due
to economic and market based optimisation.
- The grid requires a certain minimum ratio between power production on large
central plants and wind power in order to remain stable. In 2008, hours can be
found during which the grids were operated, for the western and eastern
Denmark respectively, with a wind power of 3.53 and 3.03 times the production
on the large power units. Consequently, it can be argued that the system can
operate with such minimum shares of production on the large units, meaning
that they can reduce production to this level without compromising the system
stability.
By using the above principles, one can identify hours during which the wind power plus
a production on large units of a minimum of 415 MW and a minimum of 1/3.53 of the
wind power exceed the demand. Such excess production can then be defined as wind
power being exported while the rest is export due to the decision to increase production
on the power plants for financial reasons.
By using such principles, the wind power export in 2008 was 61 GWh equal to less than
1 percent of the wind power production (or less than 0.2 percent of the demand).
However, one modification should be mentioned. In some cases the marginal
production on large CHP power plants in Denmark is very low and can even be
negative, if saved start-up costs are included. However, in the present system such hours
are rare and the export of wind power production with this approach is with high
certainty not much more than 1 percent.
1.3 How can more wind power be integrated in the future?
As described above, today, Denmark demonstrates how to supply approx. 20 percent of
its electricity demand by wind power. However, there are plans to increase this number
substantially in the future. Denmark has a long-term objective of stopping the use of
fossil fuels and expanding the share of wind power to 50 percent or even more. So what
about the future? How will Denmark (and other countries) be able to utilise such a high
percentage of wind power in a way so that neighbouring countries can do the same?
Various studies of researchers (university and consultancy companies) and authorities
(The Danish TSO and the Danish Energy Agency) have examined how to deal with
such a challenge [5-20]. From such studies the following results can be highlighted:
1.
Denmark has a high number of small CHP plants producing both heat for district
heating and electricity. Most plants were established in the mid/late 1990s and were
designed with heat storage capacity to be able to produce a lot of electricity during peak
hours and less or none when the electricity consumption is low during nights and
weekends. Changing the regulation of Danish small CHP plants to take account of
19

fluctuations in both demand and wind power instead of only demand was the first less
costly step to help the integration of wind power. Such step was (for a large proportion
of the small CHP plants) implemented in January 2004 and is one of the reasons why
Denmark is able to integrate the present share of 20 percent wind power.
2.
If Denmark subsequently supplements (and partly replaces) some of its CHP units with
heat pumps and additional heat storage capacity, the integration of wind power can be
raised from the present 20 percent to around 40 percent. The first steps of such measure
are in the process of being implemented along with the increases in the share of wind
power.
3.
If Denmark starts to replace fossil fuelled cars with battery or hybrid electric cars and/or
hydrogen cars in a long-term perspective, calculations show that Denmark will be able
to integrate a share of wind power of approx. 60 percent.
4.
Additional to these measures, a lot of other possibilities exist such as flexible demands,
hydrogen and/or similar energy carriers and various storage options which are also
presently being considered. Such measures would be able to further increase the share
of wind power.
5.
It is very important to include the small CHP plants, heat pumps and the electrification
of transportation as well as the wind turbines in the power balancing (i.e. the
stabilisation of voltage and frequency) if the abovementioned measures are to be
successful. Again, such steps are being taken and the small CHP plants are already
participating in almost all of these tasks via their participation at the following power
markets: Primary automatic control (frequency), Secondary automatic control (15
minutes), Manual regulating power (15 minutes) and spot market (day-ahead hour
market).
The conclusion is not only that Denmark with its present mix of energy technologies is
able to integrate 20 percent wind power in a way so that our neighbouring countries can
do the same, but also that Denmark has a strategy to raise this share to 50 percent in the
not so far future, and the necessary measures are in the process of being implemented.
1.4 Conclusions on Wind Power and Export
Of a Danish wind power production of 6,978 GWh in 2008, one can say for a fact that a
minimum of 0.1 percent was exported and a minimum of 63 percent was used in
Denmark. With regard to the remaining 36.9 percent, one cannot technically, physically
or from statistics of correlations over time determine which parts were exported and
which were used in Denmark.
One has to establish a causal relation, which can be found by observing the market
mechanisms of international electricity markets. Such observation leads to the
conclusion that the production of the last unit of electricity comes from the units with
20

the highest short-term marginal production costs, and consequently the wind export in
2008 was only 61 GWh equal to approx. 1 percent of the wind power production (or
less than 0.2 percent of the demand).
Consequently, it is only fair to say that the wind power production in 2008 supplied
approx. 19 percent of the Danish electricity demand. Furthermore, no evidence supports
the claim from CEPOS that approximately half of it was exported. In other words, by
serving the local demand, the Danish wind power has made it possible for existing CHP
units and condensing units to increase their export to neighbouring countries. This
possibility has been exploited due to the relatively low marginal costs of these plants at
the market.
Neither the hourly production statistics nor the market based argument presented in this
report can claim to be an in-depth analysis of the technical challenges of integrating
large amounts of wind power. There is no doubt that the wind power in Denmark has
pushed the traditional power units further up the merit order, and reduced their earning
potential. Also the hydropower with storage capacity in Norway and Sweden has proved
to be a cost efficient way to integrate wind on market terms.
The conclusion is that Denmark has demonstrated the ability to integrate 20 percent
wind power by use of local resources and the international market in a way so that our
neighbouring countries can do the same. Moreover, Denmark has a strategy to raise this
share to 50 percent and the necessary measures are in the process of being implemented.
21

2. The Financing of Danish Wind Power
The CEPOS study claims on page 19 that “a significant fraction of the charges and
taxes paid for by Danish domestic consumers is recycled to support ….. the feed-in
tariffs that make it attractive … to invest in wind power”. This statement is incorrect.
2.1 Why is the CEPOS statement on financing not correct?
On page 18 in the CEPOS report, a section starts with the headline: “How Denmark
finances wind power”. This section starts by showing the following Figs. 8 and 9 (see
below), including the two black arrows each pointing at the electricity prices in
Denmark for households and industry. We have added the two horizontal dashed red
lines showing the Danish electricity production costs excl. taxes and VAT. As one can
see, the Danish electricity production costs are at the level of the European average or
below. For example, the Danish electricity prices for industries (excl. tax and VAT) are
the 7
th
lowest out of 27 countries.
Source: CEPOS´s reproduction of EUROSTATS electricity prices for first semester 2008. (The black
arrows are added by CEPOS, and the horizontal red line by the authors of this publication.)
22

Based upon Figs. 8 and 9, CEPOS concludes, quote page 18 and 19:
“Taxes and charges on electricity for Danish household consumers make its household
consumed electricity by far the most expensive in the European Union (EU). In contrast
and in order to keep Danish Industry competitive, power to industry is hardly taxed at
all. So the disparity between what householders and industry pay for their power is very
wide. As the foregoing charts show, Danish householders pay 2.5 times more than
Danish industry. Not all the difference goes to general expenditure. A significant
fraction of the charges and taxes paid for electricity by Danish domestic consumers is
recycled to support new energy research and the feed- in tariffs that make it attractive
for Danish individuals and companies to invest in wind power. The feed-in support-
for-wind-turbines tariff has been the key feature of the Danish wind power expansion
from the beginning.”
As this quote shows, the CEPOS report claims that the difference between private and
industrial consumer prices in terms of taxes can be partly explained by feed-in support
to wind power. The CEPOS description and conclusion are not correct. They involve
two basic mistakes:
Mistake no. 1: The extra payment for CO
2
free energy to wind power is not made by
the tax-payers. It is made by the transmission company Energinet.dk, and is therefore
contained in the electricity price indicated by the blue pillar in Figs. 8 and 9. Taxes and
VAT (the green and purple elements of the price pillar) are general taxes and have
nothing to do with the cost of wind power. Thus, it is wrong when CEPOS claims that
they do.
Mistake no. 2: The extra payment for CO
2
free energy to wind power is made not only
by household consumers, but also by all other consumers, including industrial
consumers. This payment is included in the blue element of the price pillar. Thus, the
cost of wind power has nothing to do with the difference between the prices for private
and industrial consumers.
2.2 What is correct then?
If these two mistakes are removed, the horizontal dashed red line shows the price
including payment to CO
2
free wind energy production in comparison with electricity
prices in other EU countries. The conclusion is:
a.
The price of electricity production and distribution for household consumers including
payment to 20 percent wind power is the 10
th
highest out of the 27 EU countries.
Furthermore, the Danish electricity prices for households, incl. payments to wind
power, but excl. general taxes, are below the average among the old EU members, EU
15.
b.
The price of electricity production and distribution for industrial consumers including
payment to wind power is the 7
th
lowest out of the 27 EU countries, and much below
average in both EU 27 and EU 15.
23

Appendix 3 shows a comparison of industrial electricity prices and the share of
renewable energy sources for the 19 out of the 27 EU countries, where the industrial
electricity price is higher than the Danish electricity price for industrial consumers incl.
payment to wind power. Such comparison shows that for instance the UK has industrial
prices that are 18 percent higher than the Danish electricity prices for industrial
consumers, despite the UK using only 5 percent renewable energy and 3 percent wind
power and having an energy system relatively similar to the Danish one. Out of these 20
countries, Denmark has the lowest electricity prices for industrial consumers, including
the cost to wind power, and the highest share of wind power.
Therefore, we can conclude that Danish electricity prices, including extra payment for
20 percent CO
2
free wind power, are below the European average and among the lowest
amongst the old EU members, EU 15.
Even though the Danish electricity prices including payments for wind power are
among the lowest in Europe, wind power still influences consumer prices. However,
when looking at the impact wind power has on consumer prices, one has to consider
two effect areas, namely 1) payments from the consumers to wind power, and 2)
lowered consumer prices caused by wind power at the Nord Pool market. These two
elements are elaborated on in the following:
Payments from electricity consumers to wind power for CO
2
free electricity.
The payments for wind power are handled by the Danish TSO Energinet.dk and are
listed in the table below which shows consumer payments to wind power based
electricity. Again, it should be noted that these payments are included in the “Blue
pillars” in Figs. 8 and 9, and thus paid by the power consumers and not via public taxes.
Year Consumer payment to wind power
for CO
2
free electricity (million
DKK)
Consumer payment to wind
power for CO
2
free electricity
in million Euro
2004 1440 193.3
2005 1690 226.85
2006 1085 145.6
2007 1875 251.7
2008 720 96.6
Table 3: Extra payment for CO
2
free wind energy. Source: Energinet.dk
The effect of wind power on the electricity prices at the Nord Pool power market
Consumers’ payment to wind power is not the only influence wind power has on the
consumer prices. Wind power also creates additional competition at the Nord Pool
market which induces a downward price pressure on an oligopolistic market (as already
illustrated by the examples in Tables 1 and 2). The effects are further explained and
illustrated in Appendix 3.
The losers are the large power companies.
The net effect of wind power on the electricity prices combining both aspects.
By combining the two abovementioned aspects, the net effects of wind power are
calculated and shown in Table 4 below.
24

As the table shows, in recent years, the influence of direct payments to the wind
turbines has made consumer prices vary between 0.28 and 0.73 €¢/kWh with an average
of 0.54 €¢/kWh. However, this is reduced by the lowering effects of wind power on
consumer prices varying between 0.10 and 0.38 €¢/kWh. The net price impact, column
4, is at an average of 0.27 €¢/kWh. This is equal to approx. 3 percent of industrial and 2
percent of private consumer prices (not including taxes and VAT). If taxes and VAT are
included, the net influence of wind power is as low as 1 percent of the electricity price
for private consumers.
Consequently, it is only fair to conclude that the influence of wind power on Danish
consumer electricity prices is small and in general negligible.
Moreover, it should be noted that the net influence in 2008 was positive (seen from the
consumers’ point of view) and actually decreased the consumer price slightly for both
industrial and private consumers. This is interesting since CEPOS in Figs. 8 and 9 uses
the same year to postulate the opposite, namely that wind power causes higher
electricity prices.
Year
(1) Wind
power
production /
electricity
consumption
(TWh/y)
(2)Average
consumer
payment
per
consumed
electricity
(€
¢/kWh)
(3)Average
reduced
market
price due to
wind power
(€¢/kWh)
(4)= (2)-
(3) Net
price
impact of
wind
power
(€¢/kWh)
(5)
Annual
net cost
(M€)
(6)
Tonnes
CO
2
saved
due to
wind
power
(1000 t)
(7) Cost
per tonne
CO
2
reduction.
(€/t)
2004 6.55/33.06 0.58 0.096
0.48
158.7 4.585 34.6
2005 6.62/33.53 0.677 0.35
0.327
109.6 4.634 23.7
2006 6.11/33.92 0.429 0.19
0.24
81.4 4.277 19.03
2007 7.17/33.73 0.73 0.38
0.35
118.1 5.019 23.5
2008 6.93/33.37 0.284 0.33
- 0.046
2
-15.4 4.851 -3.17
Sum
2004-08
33.4/167.6
452.4
23.366
Average
2004-08
0.54
0.27
0.27
19.4
Table 4: Price and CO
2
effects of wind power production 2004-2008. Source: Pillar (2) calculations
based on data sent from Energinet.dk. Pillar (3) based on data sent from P.E. Morthorst, and [21].
The numbers in Table 4 do not take into account the fact that wind power also
influences the electricity price in hours of no wind. The reason is that the wind power
produced during hours with wind replaces hydropower which is then saved and put on
the market in hours of no wind. As a result consumer prices decrease. Such an effect is
not included in the calculations and will increase the positive influence of wind power
even further.
2
It should be underlined that these 2008 numbers show reduced consumer prices caused by the wind
power production, and that Figs. 8 and 9 in the CEPOS report are used for saying that wind power causes
higher electricity prices.
25

2.3 Conclusions on the Financing of Danish Wind Power
The CEPOS report is based on a basically wrong understanding of how Danish wind
power is financed. Thus, the statement, quote page 19, is wrong: “A significant fraction
of the charges and taxes paid for electricity by Denmark’s domestic consumers is
recycled to support new energy research and the feed-in tariffs that make it attractive
for Danish individuals and companies to invest in wind power.” This wrong
understanding built into the arguments of the CEPOS report leads to the report’s
misleading conclusions that the high electricity prices for Danish households in 2008
are caused by wind power. The high household prices are caused by high electricity
taxes and a 25 percent value-added tax. The additional subsidy payment to wind
turbines is not financed by taxpayers, but entirely via the electricity charges before tax,
i.e. the blue part of the pillars in Figs. 8 and 9, and therefore made by both household
and industrial consumers.
The Danish wind power programme with around 20 percent wind power on average has
resulted in an annual electricity price increase of 0.27 €¢/kWh in the years 2004-2008.
This equals a price increase of around 3 percent of the electricity price for industrial
consumers, and a price increase of 1-2 percent for the household consumers depending
on whether or not taxes and VAT are included in the calculation.
In 2008, wind power production created a slight reduction in the Danish energy prices.
This contradicts the CEPOS report which, based on the 2008 price statistics in Figs. 8
and 9, postulates that Danish electricity prices are high due to payment to wind power.
Danish industrial electricity prices excl. taxes, but including payment to wind power,
are in the lowest 30 percent amongst the 27 EU countries. In general, the 19 out of the
27 EU countries having higher industrial electricity prices than Denmark have a much
lower fraction of renewable energy in general and wind power in particular.
Danish household electricity prices excl. taxes, but including payment to wind power,
are slightly higher than average in EU 27, but lower than the prices in the UK, Belgium,
The Netherlands, Ireland and Germany, where incomes are at the same level as in
Denmark.
26

3. Can the Danish experiences regarding wind energy´s effects
on employment be transferred to the US?
CEPOS is against the arguments of President Obama when he, by referring to the
Danish example, concludes that wind power gives jobs, and that investing in wind
energy is a win-win activity for the economy. CEPOS says, quote page 37 in the
CEPOS report: “The Danish experience also suggests that a strong US wind expansion
would not benefit the overall economy.”
This conclusion is based on an array of arguments of which a couple will be discussed
below. CEPOS writes page 33, quote:
“The conclusion is that there is no significant tendency for the energy technology sector
to have a higher growth rate than the Danish manufacturing industry as a whole”.
This conclusion is wrong, as illustrated by Table 5 below.
1992 1997 2002 2006
Industry as a whole 100 156 280 328
Energy technology sector 100 175 355 515
Table 5: Growth in industry as a whole and the energy technology industry (index with 1992=100).
Source: Danish Energy Agency, Energi erhvervsanalyse, 2009
As the table shows, the Danish energy technology sector has grown by 415 percent
whereas the manufacturing industry as a whole has grown by 228 percent from 1992-
2006. In this period, the energy technology has had almost twice the rate of growth as
the manufacturing industry as a whole. In 1992, the energy technology sector comprised
5.7 percent of the manufacturing industry as a whole, and in 2006, this had increased to
9 percent (and 11 percent in 2008). Therefore, the Danish experience shows that it is
possible by means of a systematic policy to develop and implement a new and
successful green industry.
CEPOS says that the Danish wind power development is based on ongoing heavy
subsidies, page 35, quote:
“Based on the total subsidies to the industry, the average subsidy per worker employed
in the sector equals 60,000-90,000 DKK ($9,000-14,000)”.
This is wrong:
Firstly, since CEPOS does not include the price reducing effects of the production of
wind power on the market. This means that there was, for instance, no net subsidy to
wind power in 2008. See Table 4.
Secondly, because during 2004-2008, close to 100 percent of the manufacturing of
Danish wind turbines was exported.
27

This export has no direct links to the subsidy mentioned by CEPOS, which is the annual
subsidy given to the electricity production of all wind turbines located in Denmark that
were built in the period 1980-2003.
Thirdly, because the subsidy is given to wind turbine owners as a payment for their
(public service) production of pollution free energy. The average cost per tonne of CO
2
from this wind power production in the period 2004-2008 was 19.4 € per tonne (Table
4), which is below many estimates of socio-economic costs of CO
2
emissions.
Thus, it is problematic that CEPOS labels a public service payment/subsidy paid to
owners of wind turbines built in the period 1980-2003 an “export subsidy” per
employee for an export production taking place in the years 2004-2008.
CEPOS states that the development of a wind turbine industry in the US will generate
no extra employment.
We believe that Obama was too modest in his statement of the potential positive effects
of wind power in the US. He could have added that wind power in the future will be
able to supply electricity for electrical vehicles, and in that way become an important
part of a solution to the US balance of payment problem by reducing the amount of oil
being imported and at the same time generating new jobs. The current economic crisis
in the US is in part caused by the large and long lasting deficit on the US balance of
trade. This deficit is partly caused by an increasing import of oil which means that
money is sent abroad as payment for oil instead of invested in US jobs replacing oil
import.
The problem of the increasing US import of oil can be illustrated by Table 6 below.
Net import
1000 barrels
per day
Average price
per barrel
($/barrel)
Annual net
import of
petroleum
products
Billion US$
Balance of
payment in
billion US$
US increase in
foreign debt
per member of
the workforce
(140 million
people)
1970 - 2 - 2
1995 7.886 16 46 -96 685
2001 10.900 21.5 86 -365 2.607
2008 11.100 95 386 -677 4.835
2001-2008 -4.732 33.800
1993-2000 -1.286 9.185
Table 6: US oil import and the economic crisis. Source: U.S.Energy Information Administration, 2009
and U.S. Department of Commerce, Bureau of Economic Analysis, 2009
As the table shows, the US has increased its import of oil at a considerable rate from
1995-2008. Importing such a large amount of oil transfers purchasing power and jobs
out of the US. If an ambitious wind power programme is introduced in the US, they
could reduce the almost 400 billion US $ spent importing oil. The money saved could
be used to modernise the energy system. This could be done by improving the building
stock, introduce low-temperature district heating and district cooling as well as
improving the vehicle stock by further developing electric cars to replace petrol and
28

diesel powered cars. As a result, implementing wind power in the US would generate
employment and reduce their oil dependency and CO
2
emissions.
Our conclusion is that the general Danish experience of replacing energy and oil import
with the development and implementation of energy- and oil-saving technologies can be
transferred to most countries, and especially to the US.
29

Appendix 1:
Statistical analysis of the correlation between wind power and export
This appendix shows three diagrams illustrating the correlation over time between
Danish export of electricity and electricity production from 1) wind power, 2) large
power plants and 3) small CHP plants, respectively, in 2008.
WindPowerandExportin2008
y=0,675x‐282,07
R
2
=0,3885
‐2000
‐1500
‐1000
‐500
0
500
1000
1500
2000
2500
0 500 1000 1500 2000 2500 3000 3500
WindPowerMW
ExportMW
LargePower PlantsandExportin2008
y=0,5398x‐652,94
R
2
=0,2573
‐2000
‐1500
‐1000
‐500
0
500
1000
1500
2000
2500
0 500 1000 1500 2000 2500 3000 3500
LargePowerPlantsMW
ExportMW
As can be seen, wind power as well as large and small power plants seem to produce
more electricity during hours of high export than during hours of low export. Normally,
one would require a correlation, R
2
of around 0.9 or above, to conclude that there is a
strong correlation. As one can see, the correlation coefficients between export and wind
power, large power plants and small CHPs are R=0.62 (R
2
=0.3885), R=0.51
(R
2
=0.2573) and R=0.46 (R
2
=0.209), respectively. Consequently, there is a very weak
correlation for all three. Even if the correlation were stronger, none of these diagrams
would say anything about the causal relation, i.e. which units cause the export.
30

Moreover, it is not possible based on any of these diagrams to conclude (as CEPOS
does) that all export by default is caused by wind power.
SmallCHPplantsandExportin2008
y=0,9678x‐425,99
R
2
=0,209
‐2000
‐1500
‐1000
‐500
0
500
1000
1500
2000
2500
0 500 1000 1 500 200 0 2500 3000 35 00
SmallCHPplantsMW
ExportMW
31

Appendix 2:
Statistical analysis of the correlation between changes in wind power
and export
y=0,5771x‐0,0054
R
2
=0,0872
‐1000
‐800
‐600
‐400
‐200
0
200
400
600
800
1000
‐1000 ‐800 ‐600 ‐400 ‐200 0 200 400 600 800 1000
Windpowergradient[MW/h]
Import(‐)/export(+)gradient[MW/h]
y=0,5859x‐0,0026
R
2
=0,4269
‐1000
‐800
‐600
‐400
‐200
0
200
400
600
800
1000
‐1000 ‐800 ‐600 ‐400 ‐200 0 200 400 600 800 1000
Centralpowerplantpowergradient[MW/h]
Import(‐)/export(+)gradient[MW/h]
Fig A2: X,Y plots of hourly changes in export and changes in wind power (top diagram) or large power
plants (bottom diagram) in western Denmark in 2008.
32

In Fig. A2 (Top), all dots in the upper right quadrant represent hourly changes in which
both wind power and export increase. Similar dots in the lower left quadrant represent
hourly changes in which they both decrease. Thus, all dots in these two quadrants
represent a correlation between hourly changes in wind and changes in export.
However, in the other two quadrants, the opposite takes place. In this case, export
decreases as wind power increases and vice versa. If there was truth to the CEPOS
study presumption that all changes in export derive from wind power, then one would
expect all dots to be on the red line. However, as one can see, this is far from the case.
In the table we have identified the number of dots in each of the four quadrants.
Increasing
export and
decreasing
wind
power
Increasing
export and
increasing
wind
power
Decreasing
export and
decreasing
wind
power
Decreasing
export and
increasing
wind
power
Increasing
export and
decreasing
PP
production
Increasing
export and
increasing
PP
production
Decreasing
export and
decreasing
PP
production
Decreasing
export and
increasing
PP
production
Positive
feedback,
wind
Positive
feedback,
PP
No. of
hours
1.817 2.576 2.613 1.777 1.632 2.761 2.993 1.397 59% 66%
GWh
power
993 1.597 1.705 898 1.036 1.553 1.667 936 64% 62%
Table A2: Distribution of number of annual number of hours and production viz. Fig. A2
On the basis of the table, the analysis shows that there is no special correlation between
hourly changes in wind power and export. There is a high-high and low-low
coincidence in approx. 60 percent of the hours. However, in the remaining 40 percent,
wind power decreases when export increases and vice versa. Such correlation is not
unique for wind power. The same is the case with regard to large power stations.
Looking at the energy (GWh) instead of the number of hours does not change the
picture.
The two correlation coefficients (R) are calculated and shown in the diagrams above.
Normally, one would require an R
2
of around 0.9 or above to indicate a strong
correlation. As one can see, the correlation between changes in wind power and
import/export is as low as R=0.30 (R
2
=0.0872) while the correlation between changes in
large power plants and import/export is R=0.65 (R
2
=0.4269). Consequently, such
analysis does not in any way suggest that changes in import/export are generated by
changes in wind power. On the contrary, it points in the direction that such changes may
be generated by changes in production at large power stations. As elaborated on in this
report, the reason is that the causal relations are more complex and involve market
mechanisms and cascading effects between power suppliers, i.e. wind power releases
capacity for export on e.g. large CHPs. These are in turn competitive with e.g. German
and Finnish power plants, thus leading to an export of electricity from large CHPs, in
situations with high wind. High wind, thus, leads to Danish fossil power plants
replacing foreign fossil power plants due to market mechanisms, and not due to wind
power being exported.
33

Appendix 3:
Wind Power and Electricity Prices
Table A3.1 shows a comparison of industrial electricity prices and the share of
renewable energy sources for the 19 out of the 27 EU countries, where the industrial
electricity price is higher than the Danish electricity price for industrial consumers incl.
payment to wind power.
Country Industrial electricity price
excluding taxes Eurocent per
kWh
Share of renewable energy of
electricity consumption in
percent
Denmark 7.85 29
(hereof 19.6 wind power)
Latvia 8.29 36
Greece 8.6 7
Romania 8.9 27
Slovakia 11.97 17
Malta 12.21 0
Ireland 13.02 9
Portugal 8.95 30
Czech republic 10.95 5
Cyprus 14.05 0
Hungary 11.24 5
Slovenia 9.04 22
Luxembourg 9.99 4
UK 9.37 5
Spain 9.15 20
Belgium 9.88 4
Poland 8.14 4
Germany 9.29 15
Netherlands 8.6 8
Austria 8.97 60
Table A3.1: Renewable energy share and industrial electricity prices in 20 EU countries.
On the basis of Table A3.1, it can be seen that for instance the UK has industrial prices
that are 18 percent higher than the Danish electricity prices for industrial consumers,
despite the UK using only 5 percent renewable energy/3 percent wind power and having
an energy system relatively similar to the Danish one. Out of these 20 countries,
Denmark has the lowest electricity prices for industrial consumers, including the cost of
wind power, and the highest share of wind power.
Therefore, we can conclude that Danish electricity prices, including extra payment for
CO
2
free wind power, are still below average in EU 27.
Wind power creates additional competition at the Nord Pool market which induces a
downward price pressure on an oligopolistic market where additional competition is
desirable.
The losers are the large energy power companies.
Fig. A3 summarises the impact of wind power production on Nord Pool electricity
prices. As the figure illustrates, it is generally found that in 2004-2008 the consumer
34

price of power (excluding transmission and distribution tariffs, taxes and VAT) would
have been approx. 3-10 percent higher in Denmark, if wind power did not contribute to
power production (left part of Fig. A3). The strongest impact of wind power is
estimated for western Denmark owing to the high penetration of wind power in this
area. In 2007-2008, this adds up to approx. 0.3-0.4 €¢/kWh saved by power consumers
due to wind power lowering electricity prices (right part of Fig. A3).
Fig. A3: Price impact of wind power at the Nordpool market, 2004-2008. Source: Poul Erik Morthorst
2009 updated with 2007 and 2008 numbers from [21,22].
0
2
4
6
8
10
12
14
16
DenmarkWest DenmarkEast To tal
%

l
o
w
e
r

s
p
o
t

p
r
i
c
e
LowerSpotPrice
2004
2005
2006
2007
2008
0
0, 05
0,1
0, 15
0,2
0, 25
0,3
0, 35
0,4
0, 45
2004 2005 2006 2007 2008
c
€
/
k
W
h
PowerConsumersSaved
35

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36