Resource Documents: Netherlands (12 items)
Documents presented here are not the product of nor are they necessarily endorsed by National Wind Watch. These resource documents are provided to assist anyone wishing to research the issue of industrial wind power and the impacts of its development. The information should be evaluated by each reader to come to their own conclusions about the many areas of debate.
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Author: Verheijen, Edwin; Jabben, Jan; Schreurs, Eric; and Smith, Kevin
The Dutch government aims at an increase of wind energy up to 6 000 MW in 2020 by placing new wind turbines on land or offshore. At the same time, the existing noise legislation for wind turbines is being reconsidered. For the purpose of establishing a new noise reception limit value expressed in Lden, the impact of wind turbine noise under the given policy targets needs to be explored. For this purpose, the consequences of different reception limit values for the new Dutch noise legislation have been studied, both in terms of effects on the population and regarding sustainable energy policy targets. On the basis of a nation-wide noise map containing all wind turbines in The Netherlands, it is calculated that 3% of the inhabitants of The Netherlands are currently exposed to noise from wind turbines above 28 dB(A) at the façade. Newly established dose-response relationships indicate that about 1500 of these inhabitants are likely to be severely annoyed inside their dwellings. The available space for new wind turbines strongly depends on the noise limit value that will be chosen. This study suggests an outdoor A-weighted reception limit of Lden = 45 dB as a trade-off between the need for protection against noise annoyance and the feasibility of national targets for renewable energy.
Noise Health. 2011 Nov-Dec;13(55):459-63
Edwin Verheijen, Jan Jabben, Eric Schreurs, Kevin B. Smith
National Institute for Public Health and the Environment, Centre for Environmental Monitoring, Bilthoven, The Netherlands
Author: le Pair, C.
Electricity production in The Netherlands using renewables, especially wind, has grown to a size that makes it visible in the national statistics of electricity generation. Its influence on fossil fuel consumption can be determined. Based on these ‘official figures’ we show the actual contribution of fuel reduction to be equivalent to about 4,1% of the installed – ‘nameplate’ – capacity. The actual data also provide some insight into the mechanism that causes wind electricity to have such a dramatically small influence on primary fuel consumption.
Renewables are being introduced into electricity generation in order to save fossil fuel and to reduce the amount of CO2 emissions. In an early stage of this process a simple supposition convinced authorities and the public at large of the effectiveness of using renewables. A kWh of electricity produced free of CO2, would replace a kWh conventionally produced. It would therefore save the amount of the fossil fuel otherwise needed to produce that same quantity of electricity.
This simple notion has been criticized. The renewable electricity generation influences the way conventional units operate which in turn reduces their efficiency, and actually results in less savings. Conventional units are necessary when some of the renewable resources like wind and PV solar, are not available. They come when the wind blows or only during daylight hours. Electricity storage, which would alleviate this problem, is only feasible in very special situations. Otherwise it is too expensive.
World wide, a debate has evolved between the protagonists of large-scale renewable systems and critics who argue that the systems do not function as promised. Because quite substantial amounts of money are involved, there is a lot at stake. Many people, whose incomes and occupations are linked to the renewable sector do not appreciate the arguments put forward by the critics.
Politicians, who have tried hard in the past to push renewables, risk damage to their green image if they suddenly change sides.
The dispute has continued for some time because of inherent difficulties in determining the decisive facts that would facilitate objective decision making. First of all, the electricity systems in different countries and regions are not alike. Therefore the way in which intermittent sources influence the overall operation differs from country to country. Thus, arguments that are valid in one place may not, or not as equally well, influence matters elsewhere. Secondly there is reluctance among producers to reveal the relevant production data. They claim that it is competitively sensitive data. Also we must realize that some of the data necessary to make final conclusions are simply not available. Thirdly, as some of the renewables advocates say, present day figures are not conclusive because the overall system is changing; for instance stronger interconnections between regions and so-called smart grids may improve the situation.
We took an active role in this debate as can be read in a number of earlier contributions (2, 3-9). We have been in contact with other investigators abroad, whose work helped us to better understand the complexity of the problem and strengthened our conviction that there is something fundamentally wrong with today’s large scale renewable development. To mention but a few, I’d ask the reader to review the work on developments in the USA by W. Post (10) and in Denmark by H. Sharman (11) and P.F. Bach (12). There are many more excellent contributions and I apologize to their authors for not listing them all.
Due to the lack of all the necessary data many studies have been based on models filled in with available, though incomplete, data and topped up with general knowledge about systems and components.
Noteworthy exceptions are the studies by Bentek on the electricity systems of Texas and Colorado (13), of F. Udo on the Irish case (5, 7, 9) and several studies about Denmark (11, 12).
Bentek used the actual pollutants’ emission data to show that adding wind did not achieve the objective of reducing the emissions. Udo used the detailed production time series provided by the Irish grid operator Eirgrid to show that wind accomplished much less than previously assumed. In Denmark the wind penetration is so strong that the results show up in all kinds of national statistics. They reveal that the Danes can use only half of their wind made electricity. They face other disadvantages too. For instance, they pay about twice as much for electricity as the French do.
However, these facts on foreign systems are not sufficient to influence policy at home. The argument that situations and systems are not alike and may not be easily compared provide an all too convenient veil to hide behind.
We have summed up most of the critical arguments in a recent article in Europhysicsnews (8). In a previous paper, I presented a model of a hypothetical wind turbine assembly in the center of the Netherlands using actual wind behavior and known properties of gas-fueled backup generation to show that wind electricity might even increase fuel use (6). But, of course, a model is not as convincing as actual facts.
Electricity production in the Netherlands
The Netherlands Central Bureau of Statistics collects data on electricity production. It composes annual time-series which are publicly available on its website ‘Statline’ (14). At present the relevant series cover the years 1998-2010. Some of the data of 2010 are still labeled ‘provisional’. But the actual figures that are expected later in the summer of 2012 will not differ too much from those already published. They will therefore not influence the trends we have computed and used below.
Renewable production has now reached a high enough level to show up in these macro statistics. We have analyzed them and present the results here. We produced graphs from which we derived the current trends. In our calculations we used these trend results. Because there is some spread in the data, actual values for a certain year may differ somewhat from the ones used. The graphs we present will show how much uncertainty this implies.
Throughout this contribution we use GWy (gigawatt-year) as the unit of electric energy and caloric energy. Power is expressed in GWe (gigawatt-electric) (15).
Contribution to the national electricity production in 2010 from trends.
other energy carriers
During the whole period domestic demand exceeded national production. The Netherlands was a net importer of electricity. The situation is changing however. Capacity was augmented and we expect the country to be a net exporter of electricity by 2012. We depict some characteristics in the next four graphs.
1. national production capacity
2. national electricity consumption
3. fossil production
4. renewable production
Efficiency is a crucial issue with electricity production. The CBS offers data about fuel consumption in caloric units (TJ) for the different fuels used. There are also data about the fuel consumption of different installations. But analysis is complicated by the fact that nowadays many generating units use fuel mixes. E.g. Steam turbines, once only coal fired, now have extensions for gas. Some Open Cycle Gas Turbines (OCGT) use waste industrial gas, which they top up with natural gas. And even the dominant generating type of Combined Cycle Gas Turbines (CCGT) may get some primary energy from burning coal.
Efficiency of conventional electricity generation, η, is defined as:
Windturbines convert wind energy directly into electric energy. There is a theoretical value for the fraction of wind energy a turbine can extract under favourable conditions. However, when the wind is not strong enough, the turbines produce less or even nothing at all. When the wind is too strong the turbines have to be stopped, also then there is no production. Therefore a capacity factor is used. It is defined as:
We present some of the relevant CBS data in the next series of graphs.
5. efficiency total fossil fuels
6. capacity factor all wind turbines
7. coal efficiency
8. natural gas efficiency
The electricity production using natural gas is mostly by CCGTs. Then there is a contribution by gas engines and finally by OCGTs. The separate contributions are depicted in figure 9.
9. production by different types of gas-fueled generators
Properties of the dominant generators in the Netherlands when operating under design conditions are as follows:
CCGT. For older types η ≈ 0,55. The newest types have η ≈ 0,60. The capacity has been extended by adding the more efficient types. Over the whole period one might expect about 40% replacement by the newer types. The present average efficiency is therefore estimated to reach η ≈ 0,59 (16).
The steam turbines are mainly coal fired. Their η ≈ 0,455 (16).
The OCGT number shows some increase, although the intention is to use them less because of their low efficiency, which have η ≈ 0,32 (16).
One can speculate about the reasons for adding yet more OCGT generators. One reason could be the need to compensate for rapid variations caused by windpower. They are also used in connection with low caloric waste gas of the steel mills. Given that the steel mills have not increased in capacity, this is therefore not the driver to install more of them.
The gas engine is popular among small industrial companies and the agricultural sector. η varies much with the size: ≈ 0,26-0,45 (17).
The nuclear reactor shows a stable behavior. After a renovation around 2007 a steady η of about 0,348 rose stepwise to 0,377 (18), where it remains.
No generator works all year round at design capacity. Repairs and normal maintenance prevent this. Taking this into account the data show that coal fired generation and the nuclear installation perform as expected. They are used as ‘must run’ units providing power in the range not affected by daily or even seasonal variations. The difference between their actual performance and the theoretical one under design conditions is small. It can be attributed to these normal maintenance windows stops and some minor contribution to demand variations.
For the gas segment this is different. Taking into account the numbers of different generator types, we would expect η to be 0,51. The actual efficiency according to the national CBS data is ≈ 0,394, i.e. about 12% less. This cannot be explained by repairs and maintenance alone. Here we see the influence of ramping: lowering and raising the production and of multiple stops and start-ups in order to cope with variations in demand and variations in supply by the increase in irregular production such as wind power.
In former discussions with the responsible Minister we were told that these variations would not adversely affect the efficiency by more than 1 or 2%. The actual data show that these effects have much more influence.
Stops and starts and steep ramp ups/downs influence the efficiency much more than 2%. This raises the question what the effect of wind electricity really is and how much it impacts the consumption of fossil fuel?
Fossil fuel saving by renewables
In order to compute the efficiency with which electricity produced by renewables saves fossil fuel, we write the national production, E(t), as sum of its components:
E(t) = ∑ Ei(t)
where: i = f (fossil-fuel produced electricity), n (nuclear ibid), r (renewables ibid), o (other energy carriers ibid).
From the CBS data we derive the trends over the period 1998-2010:
Ef(t) = 0,1547 × Yr − 299,99 (fig. 3)
En(t) = 0,0023 × Yr − 4,1561 (fig. 10 below)
Er(t) = 0,0907 × Yr − 180,5 (fig. 4)
Eo(t) = 0,0042 × Yr − 8,11 (fig. 11 below)
E (t) = 0,252 × Yr − 493,49 (fig. 12 below)
Yr = 1998, 1999, …, 2010.
The unit of energy = GWy.
NB. Adding the four components would result in:
E (t) = 0,2519 × Yr − 492,7561
The difference is due to rounding and is not visible in the graph.
The electricity production is growing (dE(t)/dt). The annual increment being ΔE = 0,252 GWy.
ΔE = ∑ ΔEi
ΔEf = 0,155 GWy
ΔEn = 0,002 GWy
ΔEr = 0,091 GWy
ΔEo = 0,004 GWy
In order to realize the same growth without renewable contribution, the fossil contribution would have to increase: ΔE′f = 0,155 + 0,091 = 0,246 GWy. The incremental saving of fossil fuel by renewables is due to 0,091 GWy of electric energy. If this would be 100% effective, we would see a caloric saving equal to 0,091/ηe,f(t). The CBS data let us calculate ηe,f:
ηe,f(t) = 0,0019 × Yr − 3,425 (fig. 5)
yielding: ηe,f(2010) = 0,394. As a result this fuel saving would be equivalent to its caloric content: 0,091 / 0,394 = 0,231 GWy.
The CBS data also allow us to calculate what this contribution actually does. The consumption of fossil fuel, If(t), is among the Statline data provided:
If(t) = 0,2774 × Yr − 529,23 GWy (fig. 13 below)
This means that at present the system needs an annual increment of fuel equivalent to:
ΔIf(2010) = 0,2774 GWy.
Under the same circumstances an increase of fossil produced electricity of 0,246 GWy in stead of 0,155 GWy would require:
ΔIf′(2010) = 0,246 × 0,277 / 0,155 = 0,440 GWy
which is 0,440 − 0,277 = 0,173 GWy more than at present.
The 0,091 GWy renewable incrementally produced electricity therefore does not save 0,231 GWy but 0,173 GWy, which means it is 0,173 / 0,231 = 75% effective.
Please note: the validity of the differential approach to the whole of the developments rests on the data. All but the total capacity and the change in import/export (not shown) can be represented by linear trends. The two exceptions were not used in the calculations. Renewables were virtually not on the scene before 1998.
10. nuclear electricity production
11. electricity from other sources
12. national electricity production
13. consumption of fossil fuel
Fossil fuel saving by wind power
The electricity production of other renewables than wind and biomass is negligible. PV solar – another intermittent source, which could influence normal conventional production – contributes < 0,5% of all renewable production. Hydro makes about 1% and is not considered a disturbing contributor.
So for the time being we deal only with wind and biomass, presently contributing 0,49 GWy and 0,73 GWy respectively.
Biomass. We have not investigated the merits and problems of biomass-produced electricity as thoroughly as we did with wind for obvious reasons. We suppose the conversion of liquid or gas fuel obtained from bio-material into electricity to be similar to the conversion of fossil fuels. If any problem exists, it is with the process of turning biomass into these fuels, i.e. a problem preceding the electricity production proper. There is no problem with random electricity supply variations. Bio-fuel can be stored. The generating equipment is also the same.
If biomass does have issues these are problems arising before it has been made into fuel. They are not visible in the Statline statistics dealing with electricity. One could think of costs – also energy costs – connected with collecting bio-waste, producing energy-rich crops, fertilizers, harvesting etc. There are other considerations regarding the competition with food production, acquiring soil to grow them and so on. We have studied the contents of a recent lecture on bio fuels by H.O. Voorma in which he outlines possibilities and difficulties of producing enough biomass for energy purposes (19). We understand there are quite some technological difficulties to tackle before biomass can be counted on in sufficient quantity to substantially fill our energy needs. We would add that it is necessary, as with other renewables, to do thorough energy studies of the whole chain in advance, before we decide to apply biomass on a large scale. If not, we cannot exclude that what is advocated as a solution, will turn out to be an expensive hoax, costing more in terms of energy than it delivers.
For the present study this is of no relevance. Bio-fuel is available in small quantities and it can be used in a conventional way to produce electricity. Apart from economic matters like costs, it is a matter of straightforward reliable operation based on known techniques. Therefore we assume that producing bio-based electricity is not different from that with fossil fuel. I.e. producing according to demand. This is a very important consideration, because it implies that adding bio electricity to the grid, does not impair the functioning and efficiency of other units.
Thus the reduction of the efficiency when adding renewable electricity to the grid, which we calculated in the preceding section, cannot be attributed to bio electricity. It must be solely due to the intermittent character of wind power (6).
The (trend) share of wind electricity equals 0,492 GWy, that of biomass: 0,732 GWy in 2010. Together this amounts to 1,224 GWy. 75% of this amount is actually saving fossil fuel. This reduces the saving of fossil produced electricity to 0,75 × 1,224 = 0,918 GWy. The addition of bio-electricity is assumed to be 100% effective. This leaves for wind: 0,918 − 0,732 = 0,186 GWy of electricity saving. This should be compared with the actual 0,492 GWy fed into the grid by wind developments. This leads to the conclusion:
Wind electricity. However, there is another catch, which does not show up in the Statline statistics. The construction of windturbines, their installation, grid adaptation and connection require considerable investments of energy. Some think these costs should not be taken into account because that is also not done for conventional plants. This is erroneous. Conventional plants are being installed to produce electricity according to societal demand. Wind turbines are not. They are being added to the system in order to save fuel and to diminish CO
2 emissions. The question of whether they actually do therefore becomes essential. If not, they would only be superfluous supplements adding to the investment and other costs of the system.
The matter of energy costs associated with wind developments is another topic about which there is much dispute. The marketing blurb on wind electricity would have us believe that a wind turbine earns its energy investment back in about one half year of production. This is contrary to our findings. According to research done by one of the main contractors installing windturbines in the Netherlands and abroad, it takes about 1,5 year to earn this energy investment back (20). A more recent Australian study, analysed by F. Udo, shows an earn back period of 2,8 year (21)(!). (In this study the energy costs of on shore grid adaptation were included. Off shore requires more energy. On the other hand distances in Australia are larger than in the Netherlands.)
Let us consider the additional investment in the grid in the Netherlands. Connecting wind developments to the grid in terms of money is almost as costly as the construction and installation of the turbines themselves. This is the case for onshore and offshore systems taken together. In addition, the grid itself has to be re-enforced. In Germany recent estimates predict an extra 4000 km high-Voltage lines have to be installed to handle wind production. The problem of overproduction when there is adequate wind and the need to import electricity when there is a shortage, require regions to be connected. The Netherlands has for that purpose recently laid two under-sea cables, one to Norway and one to the UK. Combining all those adjustments we conclude that the 1,5 year “earn back time” should at least be doubled.
Another dispute continues about the expected lifetime of wind turbines and their additions. Promotors of wind turbines state a life time of 25 year. But the experience in the Netherlands is that wind developments had already to be renewed after only 12 year of operation. Sharman reported that the useful lifetime of wind turbines in Denmark is between 10 and 15 year (11).
Therefore we conclude that the energy investment should be discounted over a useful lifetime of 15 year. The total “earn back time” for wind developments is 3 year. Combining these figures means that the net amount of savings of fossil fuel for producing electricity should be cut down by 20% of the gross production of wind electricity.
Conclusion and outlook
Adding it all up, one must conclude that under the present conditions in the Netherlands a 100 MW (Megawatt) ‘name plate’ capacity wind development produces on average 23 MW because of the capacity factor. 4,6 MW (20%) of this has to be subtracted from the final net result because of initial energy investments. From the actual Statline production figures we know that 38% of this 23 MW = 8,74 MW represents the actual fossil fuel and CO2 savings. But from this figure we need to subtract the amount of energy invested in the construction works: 4,6 MW. The net total of fuel saving electricity provided by our windturbines therefore is 8,74 – 4,6 = 4,14 MW on average over the year. That is ~4% of the installed capacity. It makes wind developments a Mega money pit with virtually no merit in terms of the intended goal of CO2 emission reduction or fossil fuel saving.
What is going to happen next? The current plan is to extend wind capacity to 8 GW onshore and 4 GW offshore. Presently wind capacity is about 15% of the domestic electricity consumption. If the capacity exceeds 20% we enter into a new phase in which curtailment sets in: there wil be periods in which the grid simply cannot absorb the supply. This situation already exists in Denmark and Ireland. Then we shall see a further dramatic decrease of the fuel-replacing effectiveness. In a previous study (6), we used a model in which the most favorable scenario had a windpenetration of 20%. We found that in that case savings were already negative, which means that wind developments actually caused an increase in fossil fuel consumption. The present study based on actual data shows that we are well on the way to reach that stage.
August 15, 2012.
Nederlandse origineel (pdf): Brandstofbesparing door windmolens bij de Nederlandse elektriciteits-voorziening.
Notes and references
This article is a shortened version of a report in Dutch: ‘Brandstofbesparing bij de Nederlandse elektriciteitsvoorziening’ sent to the Netherlands Government and Parliament in August 2012. Parts usually well known to insiders have been left out.
C. le Pair & K. de Groot: The impact of wind generated electricity on fossil fuel consumption. http://www.clepair.net/windefficiency.html
K. de Groot & C. le Pair: The hidden fuel costs of wind generated electricity; Spil 263-264(2009) nr.5, 15/17 & http://www.clepair.net/windsecret.html
F. Udo, K. de Groot & C. le Pair: Wind turbines as a source of electricity; http://www.clepair.net/windstroom%20e.html
F. Udo: Wind energy in the Irish power system; http://www.clepair.net/IerlandUdo.html
C. le pair: Electricity in The Netherlands; Wind turbines increase fossil fuel consumption and CO2 emission; http://www.clepair.net/windSchiphol.html
F. Udo: Wind energy and CO2 emissions – 2; http://www.clepair.net/Udo-okt-e.html
C. le Pair, F. Udo & K. de Groot: Windturbines as yet unsuitable as electricity providers;
Europhysicsnews 43 (2012) nr.2, p. 22/5 & http://www.clepair.net/europhysics201203.html.
F. Udo: Curtailment in the Irish power system; http://www.clepair.net/Udo-curtail201205.html
W. Post, many contributions on The Energy Collective; http://theenergycollective.com/index.php?q=willem-post/64492/wind-energy-reduces-co2-emissions-few-percent
H. Sharman: Wind Energy, the case of Danmark; http://www.CEPOS.dk; download: http://www.cepos.dk/fileadmin/user_upload/Arkiv/PDF/Wind_energy_-_the_case_of_Denmark.pdf
P.F. Bach (on his website): http://pfbach.dk
BENTEK: How less became more. Wind, Power and unintended consequences in the Colorado Energy Market, 2010. http://www.bentekenergy.com
CBS, Statline: http://statline.cbs.nl/StatWeb/dome/default.aspx
1 GWy = 1 000 000 × 24 × 365 kWh. 1 kWh = 1000 × 3600 J. J = Joule. 1 TJ = 1012 J
G. Dijkema, Z. Lukszo, A. Verkooijen, L. de Vries, M. Weijnen: De regelbaarheid van elektrische centrales; een quickscan i.o.v. het Ministerie van Economische zaken, 20 april 2009.
Priv. comm. Borssele.
H.O. Voorma: Biobrandstoffen, lecture Zeist, 2012 04 18. Prof. (em) dr. Voorma, biochemist, former Rector Magnificus of Utrecht University
(2), note 13.
Lenzen, M.: Life cycle energy and greenhouse emissions of nuclear energy: a review; p. 137 ff. & Energy conversion and management 49 (2008) 2178-2199, download: http://www.isa.org.usyd.edu.au/. See also http://bravenewclimate.com/2009/10/18/tcase4/.
Author: Møller, Henrik; Pedersen, Steffen; Kloster Staunstsrup, Jan; and Sejer Pedersen, Christian
Sound and noise can be characterized by their frequency. The range from 20 Hz to 20 kHz (20 cycles per second to 20,000 cycles per second) is usually called the normal hearing range or the audio frequency range. Sound with frequencies above 20 kHz is denoted ultrasound and cannot be heard by humans.
Sound with frequencies below 20 Hz is denoted infrasound. It is usually understood that also infrasound cannot be heard, but this is wrong. Infrasound is audible at least down to 1 or 2 Hz, provided that the sound pressure level is sufficiently high. The sound is perceived with the ears, usually giving a feeling of pressure at the eardrums.
The 20‐200 Hz range is denoted the low‐frequency range. Slightly different limits are sometimes used, e.g. 10‐160 Hz. …
Low‐frequency wind turbine noise is usually described as humming or rumbling. It may have a more or less pronounced tonal character, e.g. in terms of tones that fluctuate and vary in level and/or pitch, or of tone‐ like pulses excited with regular or random intervals. The feeling of pressure at the eardrums is also reported. It is characteristic that the noise varies a lot in time and with wind and other atmospheric conditions.
The rate of modulation of the low‐frequency noise from wind turbines (and higher frequencies as well) is often in the infrasonic frequency range, e.g. the blade passage frequency, and the noise may thus be mistaken as infrasound, even when there is little or virtually no infrasound present.
What are the main effects of low-frequency noise (LFN) on humans and when specifically do these effects occur?
Noise with prominent low‐frequency components may affect human health and well‐being to a larger extent than noise without such components.
At low frequencies, the loudness increases more steeply above the hearing threshold than at higher frequencies. Thus, a sound moderately above threshold may be perceived not only loud but also annoying. Since there is a natural spread in hearing thresholds between individuals, a low‐frequency sound that is inaudible or soft to some people may be loud and annoying to others.
Low‐frequency sound is particularly annoying, when it occurs alone or with low levels of sound at higher frequencies. This means that it is usually more annoying indoors than outdoors, since the high frequencies are more attenuated by the sound insulation of the house than the low frequencies are. Also it is often more annoying in the evening and at night, when it is otherwise quiet.
Prolonged exposure to audible low‐frequency sound may cause fatigue, headache, impaired concentration, sleep disturbance and physiological stress as indicated by increased levels of saliva cortisol.
The Danish Government has changed the regulations for erecting wind turbines as a result of your research. Is that correct? And if so, what specific changes have been made?
The general (i.e. not for wind turbines) Danish limit for low‐frequency noise in dwellings is an indoor A‐ weighted sound pressure level of 20 dB (evening and night) and 25 dB (day). Only frequencies in the 10‐160 Hz frequency range (third‐octave frequencies) are included. … Unlike for other noise sources, the low‐frequency noise is not measured but calculated from measurements close to the turbine of the emitted sound. … This need not be a problem, if the calculations are correct. But they are not. … The issue is that sound at low frequencies varies within a room – usually by many decibels – and … the level should – briefly explained – be measured where the annoyed person finds it loudest. The sound insulation must be measured the same way in order to be applicable for calculations of relevant indoor levels from outdoor levels. But it was not. The indoor measurements were simply made at arbitrary positions that were not selected for a high level. Thus the obtained values of sound insulation are too high.
Figure 1 shows an example of the sound distribution in a room. Each frame shows the sound distribution in a given height, and the color scale gives the sound pressure level (scale at the right).
As a result, the calculation of the Danish regulation gives values that underestimate the low‐frequency noise that would be measured in neighboring houses. The magnitude of the error is estimated to be around 5 dB.
Even when an error of 5 dB might seem small, it is far from being negligible. … The loudness and annoyance increase more steeply above threshold than at higher frequencies. This means that when the level is a few decibels above the 20 dB limit, the consequences are more severe, than if a limit at higher frequencies is exceeded by the same amount. Most people will hear a sound at 20 dB, and some will find it annoying. Few people would probably accept 25 dB in their home at night and hardly anyone would accept 30 dB. …
Is it possible to indicate the expected LFN that will be produced by the planned four wind turbines of type Vestas V112 3MW, hub height 119 m?
Because of differences in sound insulation, not all houses will have the same indoor noise, and higher sound pressure levels than calculated will be observed in some houses. It is the expressed objective of the Danish regulation that higher levels will be observed in 33% of the houses. Hoffmeyer and Jakobsen had otherwise proposed that the calculated level should only be exceeded in 10‐20% of the houses. In the following, calculations have also been made with their proposed sound insulation data (results likewise corrected by the estimated 5‐dB measurement error). …
It is seen that the 20‐dB limit will be exceeded in a very large area with many dwellings and not only at the nearest neighbors. It should be remembered that the loudness increases more steeply above the hearing threshold than at higher frequencies, and that “The perceived annoyance from low frequency noise increases strongly when the noise reaches above 20 dB” (quote from Danish EPA).
General comments to the project
Total noise outdoors
The Dutch noise limits for wind turbine noise45,46 are based on the day‐evening‐night concept, Lden, the long‐term (yearly) equivalent level, where noise in the evening is given a penalty of 5 dB and noise in the night a penalty of 10 dB. This concept was developed to allow traffic noise with a typical 24‐hour pattern to be characterized by a single figure. However, such diurnal pattern does not exist for wind turbines, since wind turbines run around the clock, and we do not find it suitable to characterize wind turbine noise by Lden. Also Pedersen argued against using of Lden for wind turbine noise.
Since most complaints relate to the wind turbine noise in the evening and at night, we appreciate that there is an additional Dutch limit for the level at night Lnight. However, this limit also applies to a yearly average, which allows more noise at some nights, if there is less noise at other nights. This is not the way the human organism works, though. If we are disturbed by noise in the night, we cannot take advantage of the fact that, after a while – tomorrow, after some days, maybe a week – there will be nights with less or no noise. It is our conviction that limits should apply to the actual noise in situations that occur regularly.
Prepared for the City Council of Maastricht, 10 April 2012.
By Henrik Møller,* Steffen Pedersen,* Jan Kloster Staunstrup,† and Christian Sejer Pedersen*
*Section of Acoustics, †Department of Development and Planning, Aalborg University, Denmark
Author: le Pair, C.
First we describe the models presently used by others to calculate fuel saving and reduction of CO2 emission through windparks. These models are incomplete. Neglected factors deminish the calculated savings.
Using wind data of a normal windy day in the Netherlands it will be shown that windparks of various size cause extra fuel consumption instead of fuel saving, when compared to electricity production with modern gas turbines only. We demonstrate that such losses occur.
Factors taken into account are: low thermal efficiency at low power; cycling of back up generators; energy needed to build and to install wind turbines; energy needed for cabling and net adaptation; increase of fuel consumption through partial replacement of efficient generators by low-efficient, fast reacting OCGTs.
Several countries invest heavily in the construction of windmills in order to save fossil fuel and to reduce CO2 emission. The wind comes free, the mills do not pollute and there is no need to burn fossil fuel. However, this simple notion defended by staunch supporters of windturbines, has been criticized by critical analysts, e.g. refs 4, 5, 6, 8, 10, 11, 12.
Wind does not blow according to demand of electricity users. Sometimes there is no wind or little wind and sometimes there is a lot. It would be no problem if there was an economic way to store electricity and to use it from that storage whenever needed. Unfortunately we do not have such a storage. Batteries have little capacity and they are much too expensive. There are other possibillities but none of them comes near to anything that is economically feasible. The only exception is hydro power, i.e. lakes in mountains, that can be pumped full if there is an electricity surplus and emptied when the power is needed. Unfortunately there are no mountains in the Netherlands. (Also many other countries that do have them, do not have sufficient place there for such storage lakes.) So the current practice is to have windparks operate in connection to conventional powerplants. These generators step in when the wind fails and they can be switched off, or their output is reduced, if the wind blows. Thus, when considering wind power, one must do that normally in connection with ‘back up’ conventional systems. That is why the wind influences from minute to minute the performance of the conventional generators.
A handicap prohibiting the settlement of the dispute is the absence in the public domain of factual data of the different producing units. So the the arguments are mostly about model computations. There are exceptions. In the USA a BENTEK study used real emission data of power plants in Texas and Colorado. They became available due to the freedom of information act. Its conclusion was: wind has no visible influence on fuel consumption for electricity production and the emission of CO2 in the atmosphere is not reduced13.
This shocking result did not convince decision makers. At least not in Europe. The negative result was attributed to a difference in fuel mix. Coal-, oil-, gas- and nuclear heated generators behave differently. So what might be true there, does not mean that it holds true for us.
In August 2011 Fred Udo analysed the data put on the internet by EirGrid, the grid operator in Ireland. His web page article was termed by colleagues abroad ‘The smoking gun of the windmill fraud’. He showed that the substantial wind contribution in the Irish republic caused such a small saving of fuel and a corresponding small reduction of CO2 emission, that it shatters the whole economy of the wind policy. He also was able to show that more wind penetration caused an increase of CO2 emission8.
The real situation, however, is even worse. The way EirGrid derives its data on CO2 emission does not correspond with what is actually happening in fossil fired power plants. More over, the Irish data do not enclose some serious other factors that deteriorate the fuel saving aimed at. An indication could be, that the overall CO2 emission in Ireland is 20% higher than the emission calculated in the EirGrid tables, as Udo showed. (His source: ref. 14. A difference of 3% might be due to import of electricity. Transport losses have been accounted for.)
In this present study we shall explain what is wrong. On the basis of existing data and new information on the behavior of conventional generators when they are cycling – i.e. ramping up and down in order to compensate for the variations in wind power – we shall show how much worse the influence of adding wind electricity to the grid really is.
2. The old model.
During the early days of modern wind turbines the argument was simple and appealing. Every kWh electric energy generated by wind replaces a kWh produced by a conventional power plant. As a result the fuel needed to produce it, is saved and the CO2 that would be produced is not released in the earth’s atmosphere.
Different generators have different thermal efficiencies. And the CO2 production is different for gas, coal and other fuels. Some basic data for certain generators and fuel used in the Netherlands are listed in table 1. The coal fired unit in the table is the most efficient one currently under construction. Others presently in operation do not have efficiencies better than 0,44 or 0,42. The data about CCGTs should be read as of the best units running at the moment. The newest OCGTs may under optimal conditions reach an efficiency of 0,36. But there is quite a number of older ones that will remain in operation till after 2020.
|Thermal efficiency η of different generators1|
steam enhanced gas turbine, CCGT
open cycle gas turbine, OCGT
|32 × 106
29 × 106
7,4 × 106
|CO2 emission when burning3|
|Gas [kg CO2/m3]
Coal [kg CO2/kg]
The old model then tells: for every kWh wind electricity we save fuel and gas as is summarised in table 2.
Savings according to the old model.
|0,273 kg coal
0,191 m3 gas
0,352 m3 gas
0,358 mg Uranium
These figures have opened the market for the large size windmill introduction. Governments and the public became convinced. Wind offered a possibillity to offset the thread of climate change and depletion of fossil stocks. Even today the same numbers are often used in public debates, sometimes disguised in terms of ‘so many windmills are capable to provide for the electricity needs of so many households’.
Critics pointed to flaws in the assumption. There are several reasons why these figures are wrong. This lead to a new model, which is now accepted e.g. by the Dutch government. (Also the EirGrid uses this model in order to calculate the CO2 emission on the basis of the amount of electricity produced by the different conventional power plants during their operation in co-operation with the windparks.) We shall therefore call it the current model.
3. The current model.
The current model acknowledges variation of the thermal efficiency of the generators. A generator is designed for a certain optimal output. If one lowers the temperature, i.e. feeds in less fuel, the electricity output does not deminish proportionally. Every conventional generator has its own ‘heat rate curve’ describing how its efficiency, η, depends on power output. With increasing wind electricity penetration conventional power generation has to be reduced and the efficiency of the units becomes less. This reduces the savings calculated with the old model. The results are presented in table 3. For data & algorithm see Appendix.
Comparison of savings in fuel and CO2 emission between the old model
and the current model with resp. 20%, 40% and 60% less than
‘design power’ of the back up conventional plants.
We left out the ones not relevant: “n.a.”
The current model shows saving under the given circumstances. The Netherlands government assured parliament that the previously assumed savings had to be reduced by at most 10%. When we look at the figures in table 3, we see that it was slightly overplaying its hand. Our calculations show a relative savings reduction exceeding this for the most relevant generator types, CCGT & OCGT. OCGTs ought to be used as little as possible in view of their low efficiency. They are only needed when rapid power changes are required.
(Coal and nuclear plants are almost irrelevant in this respect as they cannot be ramped up and down sufficiently fast to follow wind variations. Nuclear plants do not produce CO2 anyway and their fuel is virtually inexhaustible.)
4. Errors in the current model.
Unfortunately the current model does not represent what is going on in a power plant. It neglects completely other factors that reduce the supposed fuel and emission savings. We shall first list the important factors that influence the fuel consumption and the savings. After that we discuss them and show their implications.
- Cycling, § 5.
As we mentioned before, cycling i.e. ramping up and down of conventional generators, differs from running them at less than their designed power in a stationary mode. The latter can be dealt with using the well known ‘heat rate curves’ for that particular type of generator. For cycling there is no public data. If it exists, it is kept secret. The power industry world wide consider it ‘competition sensitive’. We have argued several times that cycling is important because it is inherent to the task of following wind energy variations. It has such a strong impact on the fuel consumption of the plants, that authorities should insist that this data becomes available before they decide on huge subsidies for the wind industry. The argument that generators did cycle also before wind electricity was added because of variations in demand, is irrelevant. The wind variations add up almost to their full extend and they are more frequent and less predictable than demand variations, see for instance figures 1 & 3 below.
Recently we received some information concerning a fuel flow recording of a coal fired generator during cycling. The generator running stationary for some time at 100% of its optimal capacity reduced its output to 80% and up again to 100%. The whole cycle took place in one hour. The total fuel consumption during that period was 1,2% more than it would have been had the machine continued running at 100%. It was suggested that for a CCGT this outcome should have been 1%7. One might wonder whether this measurement is at all representative for the conventional segment? There is good evidence, that it is. A few decennia ago power companies in the Netherlands were owned by public authorities, cities or other regional entities. They were nation wide united in a co-operative association, the SEP. Within that organisation there was a free exchange of information. The SEP regulated the production of the individual plants in such a way that variable costs were minimised. Therefore the individual heat rate curves were precisely known. Please note: these were measured data, not theoretical! It turned out that the actual fuel use of the units doing the regulation and delivering the variable part of the power needed, nation wide, was always some 0,3 – 0,5% higher than that calculated with the heat rate curves. This remarkable difference was attributed to the ‘hysterysis effect’. Variations in demand required the plants to ramp up and down causing this extra fuel consumption. One should take into account that some 30% of the joint producing units took part in this cycling and provided for the extra demand above the permanent load. The demand variation was higly predictable. It consisted more or less of only two major cycles per day and yet 0,3 – 0,5% more fuel for the whole top production. This strenthens our trust in the validity of the figure of the test run.
In our calculation later on we shall assume this behaviour as a cycling fact15.
- Energy costs of construction and installation, § 6
Windmills are considerable units. They require energy for their constituents, their construction, their foundation and their installation. One of the firms actually doing this type of work figured it out. (See ref. 5. Note 13.) It boils down to an amount of energy equal to the assumed production of the wind turbine during a period of 1½ year.
This energy investment has to be ‘written off’ during the whole life time of the installation. This according to wind supporters is supposed to be around 25 year. We have seen recently that a whole windpark in the Netherlands with that supposed life time had to be renewed after 12 year. Subsidy regulations applied by the government are based on a write off in 15 year. That is the period we deem realistic.
We shall incorporate the energy costs factor in our subsequent calculations with a life time of 15 years. To appease the wind fans, we’ll add a line based on 30 year.
- Energy costs of connection and adaptation to the grid, § 7
The same as in b must be assumed for the extra cables and the adaptation of the wind generators to the grid. Germany has to construct for instance 2700 km extra high power lines. The Netherlands for that reason was connected by under water cables to Norway and to the UK. The Norwegian connection had already to be renewed partly two years after initial construction. The new to be built off shore windpark in Denmark ‘Gwynt y Môr’ will cost ~ 2 G€. 1,2 G€ of that is required for the wind turbines, 0,8 G€ for the connections etc.
We shall include in our calculations a similar ‘write off’ for this purpose as for the energy costs in b above.
- Need for more OCGTs, § 8
There are two types of gas fired generators fit to co-operate with the wind turbines: CCGTs and OCGTs. CCGTs are beautiful effective machines. Their efficiency might before long reach a thermal efficiency of 60%. However, their ability to ramp up and down is not suited for very rapid variations. It is in the order of ½ hour. But frequent ramping is unlikely because of the damage in terms of wear and tear (see g. below) it causes. OCGTs on the other hand can deal with variations within minutes. But their efficiency is sadly low. It is about 32% while running at design power. The wind variations may sometimes come sudden.
The centralised grid regulation is to a large extend done on the base of frequency regulation. This requires sophisticated manipulation of the available units. As a consequence units are often condemned to operate on less than their design power with less than optimal fuel efficiency.
Therefore it is necessary to make more often use of the OCGTs than would be the case without wind power. More use of OCGTs means more fuel. It reduces the savings the wind might give.
In our calculations we have made a moderate estimation for this factor.
- Quasi static ramping, § 5 (cycling)
In the current model it is assumed that there is an instantanious transition in a cycle from one stationary state to the next with different η. In reality there is a transition that takes time. In our calculations we have used a slightly more sophisticated approach. We assume the transitions to take place as a quasi static proces. (The cycle loss is taken into account separately.) This means that at any time during the transition we account for conditions pertaining to those at the power level at that moment. The results as shown in table 3 are not significantly altered. In a more frequently occurring ramping up and down in which the transiton time becomes more important with respect to the time in which the generator is in a stationary state, there is a difference.
- Self consumption of electricity
Windmills do not only produce electricity, they also use it. Electricity is needed to start them, and to heat some of their parts. The power regulation electronics consume electricity all the time. It is not known, whether the actual production data provided by the national statistics bureau, CBS, are nett figures. We suppose that the turbines, while running, provide for their own needs. But when they are not producing, that cannot be the case.
For the time being and by lack of information we have not included this element in our calculations.
- Extra wear and tear
Life time and maintenance of conventional plants depend largely on the ramping activity. More than on the number of stationary running hours. Ramping is a fact of life in the electricity business because of variations in demand. However, the connection with wind power adds extra to the normal, that is according to demand variation, cycling routine. Also the wind varations are often less predictable. This issue was reason for the government to ask for a special assessment. The report1 of a research group at Delft University of Technology came out in April 2009. It contains serious warnings about this phenomenon. In the USA there are firms active, which make their business by consulting power producers about more efficient ways to deal with ramping in order to save on extra fuel costs and to protect their costly equipment against faster wear and tear than what is absolutely necessary. The extra maintenance and life time shortening must have consequences in terms of energy costs.
We have to omit this factor in our calculations by lack of sufficient information.
- Spinning reserve
In actual situations it happens that conventional units must be turned off because of the wind electricity preference. In such cases normally these units remain spinning idle and thus are using fuel without production of electric energy. Data there about is also not available.
We also have to omit this factor in our calculations by lack of sufficient information.
Towards an integral savings assessment of windturbines.
(Details of the calculations can be found in the Appendix.)
The biggest CCGT presently in operation has a maximum capacity of 440 MW. In our model we use a hypothetic gas fueled plant with a capacity of 500 MW. In combination with a 100 MW windpark 3% or 15 MW of this is supplied by an OCGT. In that case the remainder has to be supplied by two smaller CCGTs. For a mainly CCGT based plant with a design capacity of 500 MW the cycle properties as described in § 4a implicate that the assumed fuel saving during one hour with a cycle 100% – 80% – 100% and a ramp rate of 12 MW/min actually becomes a loss in stead:
|assumed saving||~ 16 400 m3 gas|
|actual loss||~ 950 m3 gas|
The substantial difference is not so surprising; think of a car in town and on an express way. The fuel use of a normal diesel engine while driving at a constant speed of 100 km/h is normally about 50 – 60% of its consumption in a city with continuous speed variation. This happens also with power generators that have to adjust their output continuously following the variations of their wind powered counterparts.
|We now consider a region to be served by a windpark in combination with a conventional system. We assume a constant demand of 500 MW. The conventional system, we choose, consists of the most efficient generator units (CCGT), only when necessary assisted by a small fraction of OCGT. In order to cope with lulls in the wind, the conventional power system has a design capacity of 500 MW. For the wind park we shall look at 100, 200 and 300 MW name plate capacity. To approach average conditions, we’ll choose a normal windy day, picking the wind record of Schiphol Airport on August 28, 2011.|
A wind turbine depends for its power on the flow of the wind energy, i.e. it varies with the 3d power of the wind speed, v. If v ≤ 5 kn (= 2,5 m/sec) the turbines do not produce electricity. (Their wings may still be rotating. That is better for the bearings, but there is no output.) At 19 knots they reach their maximum capacity, i.e. P = 100 MW (or 200, or 300 MW).
In between the power must be interpolated by:
|P = 0,03644 × (v − 5)3 (or 2x, or 3x)||(1)|
as depicted in
This implies a loss that depends on the wind speed. At that site on August 28 this means a varying wind contribution shown in
If we would calculate the total power contribution using the old model, on that day the 100 MW wind park would have saved 4,2% of the use of the conventional power plant. Details of the arithmatic can be found in the Appendix. Wind power experts attribute a ‘capacity factor’ of 25% to wind mills in the Netherlands. That is to say with a name plate capacity of 100 MW the average contribution over the year would be 25 MW, which means 5% saving. However, in 2008 the overall capacity factor of the wind turbines in the Netherlands was 22,63%16. Thus an average wind day in 2008 would have saved 4,5%. We found 4,2% which means that August 28 was just slightly less than an average wind day that year.
But, because of the cycling effect the real result is appreciably different.
The Schiphol record tells us the wind speed every half hour (i). With (1) we find the wind power, Pw,i, and the power of the adjusting CCGT+, PGT,i.
|PGT,i = 500 − Pw,i||(2)|
We calculate the fuel consumption during that half hour with the quasi stationary method. That is we split the 30 minutes in a part in which the CCGT+ produces stationary and a part at which the system is ramping from the previous level PGT,i-1 to PGT,i. For the first we part we use: ηi and for the second: 0,5 × (ηi-1 + ηi).
For details see Appendix.
We know what cycling does in the case of 100% – 80% – 100% for a 500 MW generator. During a full cycle there are three phases: up, down & stationary. In a cycle during a full hour with 12 MW/min, these last ~8,3 min, ~8,3 min and ~43,4 min. During the 43,4 min there is saving. During the two times 8,3 min there is saving while going down and extra fuel consumption going up. The nett cycle cost in the example is the same whether it happens during an hour or during a half hour as long as the ramp rate remains 12 MW/min. Only the stationary minutes are less.
The net cycle costs will depend on the amplitude of the cycle and to some extend on the power level at which the CCGT operates. Also the duration of cycling depends on the amplitude.
- The net cycle loss does not depend on the power level. (Probably the loss at low power i.e. with high wind penetration increases, because the relative diferences are bigger and the CCGT has a lower efficiency there.)
- The nett cycle loss is proportional to the amplitude. It is zero if the amplitude = 0 (stationary) and at amplitude = 100 MW the loss is as in the example.
- During the half hours we only see half cycles. We assume that they require also only half the nett loss. Because the wind speed over a longer period always returns to its earlier value, our CCGT ramps as much up as down, which justifies this assumption.
Now we are able to compute for each half hour the savings of the system. (Quasi stationary saving minus the pertaining cycle loss.) Summing them up and comparing them with the fuel use of our CCGT at full power, we obtain the percentage fuel (and emission) saving over the 21½ hour period.
6. Energy costs of construction and installation.
We use the data of the energy costs for construction and installation of the research department of Volker Wessels Stevin, a major installer of windturbines5: 1,5 year windmill production to recover the needed energy. If we then assume the life time of a windmill to be 15 year, it means that 10% of its production must be deducted to compensate for the earlier loss. We shall also do our calculation for a life time of 30 years, meaning a 5% deduction.
7. Energy costs of connection and adaptation to the grid.
Here wil work with the same deductions as in § 6, see § 4c.
8. Need for more OCGTs.
OCGTs are the best generators to compensate for rapid variations. Their thermal efficiency is about half of that of a CCGT. OCGTs are always used because of fast changes of demand. Now the variations of wind power add to the variations of demand, which requires more often production with their low efficiency and accompanying more fuel use.
We assume that with windparks of 100 MW, resp. 200 MW and 300 MW the participation of OCGTs has to be increased by resp. 3, 6 and 10%. That we are not dealing here with a negligible complication can be illustrated with a comic remark by the CEO of the Gas Union, the main natural gas supplier in the Netherlands. While he was being interviewed on Dutch TV about the huge activity of constructing new gas pipe lines, he said: “It is because all that wind takes so much gas.”
In our computations we reduced the effective η of the conventional plant according to the said percentages with the η of the OCGTs, for which we took ηOCGt = 0,32.
The other factors mentioned in §§ 4f, 4g & 4h we leave out.
9. Results & conclusions.
The result of our calculations are summarised in table 4. One must keep in mind that the conventional plant by itself is capable to fullfil the whole electricity demand. So all costs for buying the wind equipment, the costs of installation and those of the extra cables and net adaptation are extra. (See Appendix for the algorithmes.)
Fuel saving and CO2 emission saving through windparks according to different models and including other relevant factors.
Results for a 500 MW production provided by a modern gas fired plant with design capacity of 500 MW together with a windpark with name plate capacity, V, near Schiphol on a normal windy day.
|V||100 MW wind||200 MW wind||300 MW wind|
|Quasi stationary ≈ current||3,5%||7,1%||10,7%|
|Ibid. incl. lifetime 30 yr.||1,0%||2,0%||3,1%|
|Same lifetime 15 yr.||0,6%||1,2%||1,9%|
|Same (30 yr.) + OCGT||−0,3%||−0,5%||−1,0%|
|Same (15 yr.) + OCGT15||−0,8%||−1,4%||−2,3%|
It is clear. The alleged savings provided by windparks that could cover 20%, 40% or 60% of the electricity demand during favourable winds are not just negligible, they are even negative, when the most relevant factors are taken into account. As we remarked before, there is substantial evidence that a life time of 15 year is not an exaggeration. We mentioned the park that had to be renewed after 12 year. That was an on shore park. The parks to be constructed off shore operate under more difficult circumstances. Therefore we conclude:
A 300 MW nameplate windpark near Schiphol on August 28, 2011, a normal windy day, during 21,5 h would have increased the amount of natural gas needed for the electricity production of 500 MW with 47150 m3 gas. This would have caused an extra emission of 117,9 ton CO2 into the atmosphere.
The windparks do not fulfill ‘sustainable’ objectives. They cost more fuel than they save and they cause no CO2 saving, in the contrary they increase our environmental ‘foot print’.
A decision to invest thousands of millions Euros in the construction of windparks ‘to save fossil fuel and to reduce CO2 emission’ is irresponsible. There are no savings, THERE IS LOSS!
We do not consider it likely that more knowledge of the factors influencing the present outcomes would change our results appreciably.
Nieuwegein, October 7, 2011.
References & notes.
- This web page article is aimed at readers with some background knowledge. It is a short version of the Dutch report Gas, Wind en CO2 op Schiphol. De crash van de windmolens. (The Dutch report tries to explain the subject to the laymen.)
- Dijkema, Z. Lukszo, A. Verkooijen, L. de Vries & M. Weijnen: De regelbaarheid van elektriciteitscentrales; quickscan in opdracht van het Ministerie van Economische Zaken; TU Delft, 20 April 2009.
- Oscar Vlijmen.
- K. de Groot & C. le Pair: The hidden fuel costs of wind generated electricity. Also: SPIL 263 – 264 (2009) p.15 ff.
- C. le Pair & K. de Groot: The impact of wind generated electricity on fossil fuel consumption.
- F. Udo, K. de Groot & C. le Pair: Wind turbines as a source of energy.
- KEMA: priv. comm.
- F. Udo: Wind energy in the Irish Power System.
- Wind record Schiphol
- Kent Hawkins: Wind Integration Realities: Case Studies of the Netherlands and of Colorado.
- W. Post: Wind power and CO2 emissions.
- Hugh Sharman: Wind energy, the case of Denmark.
- BENTEK Energy: How less became more: Wind power and unintended consequences in the Colorado energy market.
- In discussions among us (De Groot, Udo and myself) it has been asked whether the data of ref.7 should not be interpreted as ’1% more than the current model’? We think not. Remember the ‘car in city’ argument above. Nevertheless, we have also done the calculations using that assumption. In this case the outcomes taking into account the other factors as well are for a 15 years life time:
savings of resp. 1,2%; 2,6% and 3,7% for 100 MW wind, 200 MW wind and 300 MW wind, i.e. 20%, 40% and 60% of the total demand capacity in the form of windmills.
These are also absurd low savings in the view of the economics of electricity production.
- CBS Statline.