Resource Library Category: Grid (131 items)

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Windmills increase fossil fuel consumption and CO2 emissions

Source:  Le Pair, Kees

Abstract

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.

1. Introduction

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.

Table 1.

Thermal efficiency η of different generators1
coal fired steam enhanced gas turbine, CCGT open cycle gas turbine, OCGT nuclear	0,455 0,59 0,32 0,377
latent heat2
Gas [J/m3] coal [J/kg] Uranium [kWh/kg]	32 × 106 29 × 106 7,4 × 106
CO2 emission when burning3
Gas [kg CO2/m3] Coal [kg CO2/kg] Uranium	2,5 2,6 nihil

The old model then tells: for every kWh wind electricity we save fuel and gas as is summarised in table 2.

Table 2.
Savings according to the old model.

Type generator	Per kWh conventional	Per kWh CO2 [kg]
Coal fired CCGT OCGT Nuclear	0,273 kg coal 0,191 m3 gas 0,352 m3 gas 0,358 mg Uranium	0,71 0,48 0,88 nihil

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.

Table 3.
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.”

savings					relative setback
old model all	current model
	Coal fired	CCGT	OCGT	nuclear	CCGT	OCGT
0% 20% 40% 60%	0% 19,1% 36,5% n.a.	0% 17,2% 35,6% 51,8%	0% 14,7% 28,9% 44,3%	0% 17,8% n.a. n.a.	n.a. 14,0% 10,9% 13,6%	n.a. 26,7% 27,8% 26,1%

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.

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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.

7. 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.

8. 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.

-o-o-o-o-o-o-o-

Towards an integral savings assessment of windturbines.

(Details of the calculations can be found in the Appendix.)

5. Cycling.

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.

Figure 1.

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

Figure 2.

This implies a loss that depends on the wind speed. At that site on August 28 this means a varying wind contribution shown in

Figure 3.

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, P_w,i, and the power of the adjusting CCGT+, P_GT,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 P_GT,i-1 to P_GT,i. For the first we part we use: η_i and for the second: 0,5 × (η_i-1 + η_i).

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.

We assume:

1. 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.)
2. 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.
3. 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 η_OCGt = 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.)

Table 4.
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
Old model	4,2%	8,3%	12,5%
Quasi stationary ≈ current	3,5%	7,1%	10,7%
Including ‘cycling’	1,4%	2,9%	4,4%
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:

NON-SUSTAINABLE. 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.

Click here to go to APPENDIX

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.)

1. 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.
2. Oscar Vlijmen.
3. CO₂-PROFIEL
4. K. de Groot & C. le Pair: The hidden fuel costs of wind generated electricity. Also: SPIL 263 – 264 (2009) p.15 ff.
5. C. le Pair & K. de Groot: The impact of wind generated electricity on fossil fuel consumption.
6. F. Udo, K. de Groot & C. le Pair: Wind turbines as a source of energy.
7. KEMA: priv. comm.
8. F. Udo: Wind energy in the Irish Power System.
9. Wind record Schiphol
10. Kent Hawkins: Wind Integration Realities: Case Studies of the Netherlands and of Colorado.
11. W. Post: Wind power and CO₂ emissions.
12. Hugh Sharman: Wind energy, the case of Denmark.
13. BENTEK Energy: How less became more: Wind power and unintended consequences in the Colorado energy market.
14. SEAI.
15. 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.

16. CBS Statline.

Click here to go to original paper (which may have been updated since posting here).



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Date added:  July 29, 2011
Economics, Emissions, Grid, U.S. •

Rational Look at Renewable Energy

Source:  Rasmussen, Kimball

Fundamental Issue: Intermittency

Despite robust wind development in the U.S., wind faces a nearly insurmountable issue: intermittency. Simply put, the intermittent nature of wind makes it difficult to harness effectively on a power grid that is finely tuned to deliver electricity around the clock. The down side of this intermittency is clearly evident in the actual performance data of wind turbines already installed. Wind performs poorly across all traditional utility metrics for generating resources. For reliability, stability, forecast ability, proximity to load centers, and economics, wind power is a poor choice for large-scale power production.

Nameplate Rating versus Actual Energy Delivery

For large utility grade generators the customary expectation is that once installed, they will deliver the name-plate output when supplied with sufficient fuel. Additionally, they will operate, if required, around the clock. In the case of wind energy installations this is simply not the case. The output over time is only a small fraction of name-plate rating because of the intermittency of the fuel resource. The ratio of actual output divided by maximum potential output is defined as capacity factor. The entire sector of U.S. wind energy is currently operating at a capacity factor of only 25 percent.

Wind Is Weak at Peak

The intermittent and unpredictable nature of wind is further compounded by the fact that the wind tends to be weak during electrical peak load conditions. Wind blows most consistently and creates the best generation opportunities during off-peak hours, cooler days and evening hours; directly opposite the electric customer usage profile. This is a natural consequence of the climate forces that determine wind: daily and seasonal temperature differentials. On the hottest days of the summer the wind tends to be low or non-existent when air conditioning demands are at their peak. Then when it gets windy, the temperatures will naturally moderate and air conditioning loads drop off just in time for the wind energy to pick up. Therefore, during the summer months, wind generation is low during high demand times, and can be shown to reach maximum generation when power demands are down. The same phenomena can be demonstrated to occur during winter peak conditions. The very coldest days are also the days when the wind is not blowing. For this reason, utility-scale balancing regions simply do not plan for significant contribution of wind at peak demand periods.

Texas

Texas is home to the largest collection of wind generation facilities in the nation. More than one out of every four wind turbines in America is found in Texas. The Electric Reliability Council of Texas (ERCOT) only plans for 8.7 percent of wind name-plate rating as the “dependable contribution to peak requirements,” in accordance with ERCOT’s stakeholder-adopted methodology. This means that more than 91 percent of Texas wind turbines are expected to be off-line when it matters most—at peak load periods.

California

The State of California ranks third in the U.S. for total installed wind energy (behind Texas and Iowa). California is also the third largest state geographically (behind Alaska and Texas). … The wind capacity available at California peak demand times is about 200 MW. The name-plate capacity of California-based wind generators is about 2,600 MW. Hence, the wind power available at peak is less than 10 percent, which is very similar to the Texas experience. In other words, about 90 percent of California wind turbines are idle at peak load conditions.

Pacific Northwest

Oregon and Washington rank fourth and fifth in the U.S. for total installed wind energy. The prominent Federal Power provider in the region—the Bonneville Power Administration (BPA)—is a winter-peaking system with about 10,000 MW of load. On Tuesday December 16, 2008, the BPA system reached its peak for the entire year, with a demand of 10,762 MW. At the time of peak demand, the output of the entire fleet of wind resources, with a name-plate value of 1,599 MW, was only 116 MW, or about seven percent of the name-plate potential. This is very similar to the Texas and California wind experience, only in this case about 93 percent are not producing at the winter peak.

Western United States

Now let us consider an even broader region— all eleven western states, from Montana to New Mexico, from Washington to California, and everything in between. This vast area is served as a single “reliability” region known as The Western Electricity Coordinating Council (WECC). During the heat wave of July 2006, the WECC system reached its peak on Monday, July 24, 2006. The hottest day was actually July 23, 2006, but this was a Sunday so total loads did not peak until Monday. On the hottest day, the capacity factors for wind resources through most of WECC were well under five percent, and on the peak day, which was a slightly cooler day, the wind capacity factors were less than ten percent.

These real-world lessons illustrate the grave shortcomings of wind. Approximately 90 percent of wind turbines can be expected to NOT PRODUCE power at peak load periods, even when distributed over broad geographic areas.

Enter the “Twilight Zone”—A Control Area Nightmare

The demonstrated low performance of wind energy during peak load conditions is only one side of the coin. The other side occurs during off-peak periods when unscheduled, unanticipated wind energy comes booming onto the system ready to serve loads that are nowhere to be found.

This can easily happen because of the physics of wind energy: the power output of a wind turbine accelerates at a much faster rate than the simple change in wind speed. For instance, if the wind speed changes from 10 to 20 mph (a doubling of the wind speed) the associated power output will change by a factor of eight.

An actual case with the BPA brings the control area problem into perspective. On April 27, 2010 about 3:00 a.m., wind generation on the BPA system ramped up by 1,200 MW in only one hour, and then down 800 MW in only 20 minutes. … Such erratic changes in generation run directly counter to the needs of utility operators who select from a pool of different traditional generators to provide the right amount of power at the instant it’s required. In a normal day they blend the outputs of traditional power plants that include coal, nuclear, natural gas, and in some regions hydroelectric to work in concert to minimize operating costs while maintaining reliability.

Consider an event that occurs during off-peak or twilight hours. The various utilities are operating with all of the peaking plants off line and many of the intermediate resources off line. Still running are base-load, coal-fired generators but they have been reduced to minimum-load status. The nuclear plants are running because they remain in “must-run” condition for safety and economic reasons. The wind turbines are cruising along at a modest output. Now assume that a sudden, unanticipated, change in the weather brings with it a rapid ramping of wind energy output. This can result in a large block of several thousand MW of unplanned energy that when combined with the operating status just described, that can easily swamp out the total load requirements of the utility—meaning there’s literally no place for the energy to go. Now the utility is forced to make quick and drastic decisions to balance loads and resources.

I call this the twilight zone—a control area no-man’s land. One option might be to enact the costly decision to shut down a base-load resource, such as a nuclear or coal unit, and then subsequently face a high cost “re-start” with its attendant unusual wear and tear on the affected units. In the case of a coal-fired unit, emissions will increase as the unit and its pollution control equipment ramp up during the few hours after startup. Another twilight zone choice is to try to sell the “hot potato” energy to a neighboring utility, or to another control area authority. What if the neighbor already is operating at optimum balance? … The host utility might actually have to pay a neighboring utility to accept the surplus schedule and allow delivery onto its system.

Many utilities have found themselves in precisely this situation. For this reason some system operators are now requiring wind turbines to be equipped with a “cut out” switch that disconnects the wind farm from the grid by remote control. This becomes an obvious waste of energy.

The Shadow Grid—The Fossil Fuel Stand-In for No-Show Wind

Wind’s unpredictable nature tends to provide energy that does not match consumer demand. As noted in the examples of ERCOT, California and the Pacific Northwest, wind volatility makes it unsuitable for electricity planners to rely on wind energy to meet peak demand needs. In order to mitigate these negative effects, the grid operators and planners must construct a shadow grid, typically consisting of fossil- fueled power plants (particularly gas-peaking units). This shadow grid stands as reserve generation for those times when wind resources are not delivering their potential capacity.

Effectively, we end up building new fossil-fueled peaking power plants (usually natural gas) to back up the wind resources that were intended to eliminate fossil-fueled resources in the first place.

Los Angeles Department of Water and Power

[T]he LADWP overtly recognizes that the wind projects on the system are only meeting the legislatively mandated RPS as they provide intermittent energy. But to actually operate a reliable system, with capacity and energy, LADWP must install natural gas generation resources. In spite of the obvious environmental objective of wind energy, the shadow grid of gas generation will result in air emissions, including carbon dioxide. Many such generators are “simple cycle” peaking units, which tend to be less efficient and have the highest emissions among gas-fired generators.

Increase in Carbon Dioxide from Wind Power—It Is Possible

In addition to the obvious investment and operating cost of the shadow grid, there is another unintended consequence of this fossil-fueled backstop system: carbon emissions. As discussed above, a significant penetration of wind turbines into an electric grid can cause base and intermediate resources to be fired up and energized onto the grid or dispatched at levels where design efficiencies are very poor. This results in unintended carbon emissions.

Think of it like this: Suppose that you were to go on a road trip where you are required to maintain an average speed of 60 mph. In the base case you do this by setting the car on cruise control. Now imagine an outside influence that requires you to suddenly stop, and then rapidly accelerate to 120 mph, and to do so at unpredictable intervals, all the while you are required to average 60 mph. Can you imagine the fuel economy differences between these two cases? This is more or less what happens to an electric system that attempts to accommodate a high percentage of wind resource into the grid.

Got Transmission? The Missing Cost Element

[T]he regions of maximum wind potential (the areas of red, purple and blue) do not coincide with the areas of dense population. The wind speed and duration are generally the greatest in the least populous areas far away from the big cities on either coast.

Technical Potential versus Economic Potential

This means that, in terms of their operating characteristics, and even for the best wind resources, the grid must be designed and operate as if 60 to 75 percent of the time a typical wind turbine produces very little or nothing at all.

The Electric Continental Divide

In addition to the obvious transmission challenges of renewable energy, there is a virtual wall between east and west. Unfortunately, the greatest “economic potential” of wind energy is electrically trapped in the Midwest. It is virtually impossible, or at least very cost prohibitive, to consider transmitting this resource to the west. It is also impractical and cost prohibitive to transmit this energy to the east coast population centers that are, in some cases, more than a thousand difficult miles away.

Wind Energy Storage—Not Ready for Primetime

Storage of electricity would, indeed, answer many of the operational concerns raised when it comes to renewable energy. The notion that electricity cannot be stored is not entirely accurate, and in fact, there is much effort underway to develop new storage technologies. An ideal storage mechanism would be able to capture unlimited quantities of electricity, at a near infinite rate of charge and discharge on demand. It would be able to hold a charge for long periods of time and would be free, or at least very inexpensive to install and operate, with little or no losses. Unfortunately, as of today, this dream set of criteria is a fantasy, although there is an obvious need for energy storage technology. An effective wave of new, renewable energy can only function properly in a world that is ripe with near-ideal energy storage opportunities.

It is true that devices have been invented to store bulk electric energy. These are all minuscule in scale, and expensive to acquire and operate. … It should also be noted that storage technologies always come at a cost—both a capital cost to develop and acquire the storage mechanism, as well as an operating cost or storage penalty (essentially the execution of thermodynamic laws). There is always some amount of energy loss associated with storage. The flywheel system previously described claims a storage penalty of about five percent, including transformation, while hydroelectric pumped storage requires about 30 percent more energy to fill the storage pond than can be extracted upon retrieval. The energy output of storage is always net negative.

Wind Turbines Can Consume Electricity

One of the little known ironies about utility scale wind turbines is that they require an external source of grid-provided electricity in order to run properly. Particularly in cold climates, where much of the best wind resources can be found, these units must be heated to maintain proper viscosity in lubricating fluids and to protect vital components from damage. When it’s cold in Wyoming and up into the Dakota badlands where the calm night air drops to below zero, it will be the fossil-based fuel from gas and coal-fired power plants in the region that are called upon to warm the massive wind turbines towering hundreds of feet above the windswept plains.

The Hard Realities of Renewable Pricing

Value of Power—Demand versus Energy

Having electricity intermittently available, at unpredictable times and quantities, is not acceptable in today’s electric system. A practical example will help illustrate this point. When it comes to our automobiles, we have a tendency to demand cars be reliable and to meet our wants and needs at our beck and call. Consider a choice between two automobiles: one gets 50 miles per gallon, but only runs intermittently about 25 percent of the time; the other car gets about 20 miles per gallon, but it runs all of the time. How would you value each of these cars? If the first car had low fuel cost, but no reliability, how much would you pay for such a car, and are you prepared to call a taxi when your car stalls half way down the road? If the value of
a car is based, shall we say, half on fuel economy and half on reliability, then the market value of the intermittent car will be intrinsically lower because it fails to meet the primary purpose of reliable transportation. Who wants a car that rarely runs?

This concept is very relevant to a discussion about renewable energy. A claim might be made, for instance, that a certain wind turbine can produce power at a cost of 8 cents per kilowatt hour (kWh). But cost is only half the story. The actual value of such power is properly assessed by considering both the demand and energy provided by any given resource.

Download original document: “A Rational Look at Renewable Energy”



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Date added:  June 25, 2011
Economics, Grid, Technology •

Wind turbines as a source of electricity

Source:  Udo, Fred; de Groot, Kees; and le Pair, Kees

Introduction


Wind turbines are being built in large numbers. In the Netherlands the Government aims facilitating 12 GW wind power in the coming 10 years. Aiming to provide 20% of Dutch electricity from wind, Minister Verhagen of Economic Affairs, Agriculture and Innovation gave the following response to questions in Parliament:

“In order to realize an increase in renewable electricity (generation) from 9 to 35% by (the year) 2020 a further growth of wind power on land is necessary as this is a relatively cheap form of sustainable electricity (generation).”

His answer is similar to that given in many countries. Why is that so?

We can think of 3 main reasons:

1. Subsidizing or otherwise promoting wind energy is an easy and very visible way of showing voters how “green” and sustainable the government is, and how serious it is in combating global warming or as it is now coined: climate change. Wind turbines provide favorite images in any publication on green issues.

2. As long as the total wind turbine capacity is small (say < 5% of total power generating capacity) the negative consequences for conventional power stations are modest and may not even be noticed. The amount of subsidies required and visible impact on the landscape stay below the threshold of public awareness.

3. Large wind-power installation generates a significant subsidy-addicted industry, which will try to sustain itself using a body of professional lobbyists. The latter employ the customary scares of imminent fossil fuel depletion and global warming, nay, climate change.

The results of this development are rather ominous. This article discusses some of these.

1. Installing wind turbines


Building and installation of a wind turbine costs as much energy as it generates in one and a half years. In addition, wind farms require an extensive infrastructure in the form of cables, transformers and other equipment for grid access. The Dutch grid management company TenneT calculates that it requires € 4,5 billion ($ 6.4 billion) to connect the planned offshore installations to the power grid. How long will the turbines have to produce their current to pay back that investment to finally start their intended contribution to renewable energy?

One should note that the average lifetime of a turbine is 15 to 20 years. Those on the dike near the town of Lelystad were scrapped after 12 years. The Netherlands Bureau of Statistics (CBS) tells us that in Holland the average turbine on land yields 22% of the nameplate capacity. This is equal to the turbines running at full capacity 22% of the time, and standing idle 78% of the time. To extend the lifetime of the bearings the turbines are kept moving also at low wind speeds, when virtually no electricity is generated.

A horror scenario

The original objective of installing 8 GW offshore and 4 GW onshore has just been changed to 4 GW offshore and 8 GW onshore in view of the excessive costs of offshore wind farms. The government has stated that onshore wind power is “relatively cheap” (Verhagen, March 2011) A state of the art turbine of 2 to 3 MW has its turbine at 120 m and a wingspan of over 80 m. Such installations dominate the (flat) Dutch landscape at distances of as much as 10 kilometers. Turbines have to be installed at distances of at least 10 rotor diameters from each other, so a turbine requires 0.7 km² of space. The required three to four thousand turbines may make more than 2,000 km² of land unfit for human habitation. This is 6% of the Dutch land surface, one and a half times the surface area of the province of Utrecht, or 90% of Limburg.

The key issue is whether a responsible government can wreak havoc in the landscape and in society in order to generate less than 10% of our electricity or satisfy between 1 and 2% of our total energy demand. How many billion Euros will the Minister set aside to compensate for the property devaluation caused by the wind parks? We fear that the citizen will be the victim.

The turbines need to be positioned in the provinces with most wind: e.g. North Holland, Friesland, Groningen and Zeeland. Planning of wind energy in Holland is left to the provinces. However, the provinces of North Holland and Friesland have just decided either to prohibit new wind parks onshore, or to allow them only in small, designated strips of land (Newspaper Trouw, March 2011.) So luckily until the arising dispute between government and provincial administrations is settled we will not have to dwell on the manner in which the turbines would be forced onto the population, with placement in “Natural Landscapes” (protected areas), ecological exclusion zones, etc.

2. The (un)predictability of wind power


Electricity generation varies with the third power of the wind speed. That means that when wind speed falls from the level at which the turbine delivers peak power to half that speed, the power produced becomes only 12.5% of peak power. (Note: Modern turbine blade design compensates somewhat for this effect by allowing for higher blade efficiency at lower speeds and lower efficiency at top power.)

Therefore the Dutch power producers must know ahead of time what the wind velocity will be in order to compensate for wind over or under supply by regulating the output of the conventional power stations. ECN researchers have now concluded that meteorologists can predict wind speed in the next 24 hours within 10% accuracy, after having spent significant effort on determining this predictability [1]. Improvements are not expected in the short term.

This 10% uncertainty leads to a 30% uncertainty in the forecast of energy production. The grid managing company, which keeps extra “spinning reserve”, i.e. conventional power plants on standby, takes this uncertainty into account. The unpredictability of wind costs extra (fossil) fuel. In compensation this company is paid € 0.01 per kWh wind energy produced. The Dutch government has now decided that this extra cost will be charged to the consumer rather than to the wind energy producer. In our opinion this amounts to hidden subsidy to the wind industry.

The “spinning reserve” uses mainly or exclusively natural gas, because coal and nuclear power stations are not able to adjust to the rapid variations in wind. The Dutch Gas grid manager has announced that they need to provide extra gas pipelines “because the wind costs so much gas”. This does not sound like “sustainability” and “energy saving”.

3. CO₂ emission reduction by wind electricity


The wind turbine community does not publicly address the impact of varying wind supply on the efficiency of conventional power plants, although each graph of wind output as a function of time demonstrates the importance of this effect. Here is the graph of wind power feed-in of the 7000 turbines, which the German utility E.ON had in operation in the year 2004.



“E.On Windreport 2005”.[3]


These machines are spread out from North Germany to Bavaria in the South. This graph demonstrates that spreading the turbines over a large area will not eliminate the wind variability. The total daily production of the 7,000 turbines varies between 0.2% and 38% of the daily peak grid load. We conclude that weather systems are larger than Germany…

Similar evidence has just been provided in the western USA where large variations in output are evident when looking at total output of turbines over a 300,000 square mile area (778.000 km²) more than twice the total German territory, which is that much bigger than E.ON’s wind mill spread.[2].

Wind electricity requires conventional power plants to work in spurts. Plant efficiency then falls, an effect comparable to that of stop-and-go city driving (power plants compensating for erratic wind) when compared to highway driving (power plants running more steadily). Some wind promoters compare wind turbines, which stand still 50% of the time, with private cars, standing still 90% of the time. The comparison is false. The car will move when demand is there, while the turbine only can perform when there is wind. The crucial difference between “demand-driven” and supply- driven” has either not landed or is not understood in the wind turbine community.

The E.ON graph demonstrates that electricity supply based on a high proportion of wind energy is an illusion. Wind energy application on any significant scale requires large-scale energy storage. This may only be possible with hydro-electricity, which cannot work economically in our flat country. For Holland this simply means that no conventional power station can be closed. It is also clear that even for large spreads of wind turbines the result is:

No wind means no electricity.


A study for the John Muir Trust by Stuart Young consultancy [4] even puts into question whether the available UK hydro storage can provide the storage required for the present number of wind turbines in the UK. As an aside, it also questions the validity of the five key assertions by the wind turbine industry and governments. Their work is based on analysis of publicly available data, not on model studies.

We will now comment on five discussions of this problem. Two of them are model-based predictions, to find out how much wind energy can be accommodated. The last three use real data to determine the overall net effect of wind electricity addition to the grid.

1. Ummels [5] attempts to demonstrate on the basis of model calculations that 20% wind electricity can technically be accommodated in the Netherlands. In the introduction of his thesis he states that this leads to 19 million ton reduction in CO₂ emissions, but on page 139 in his thesis he qualifies this conclusion as follows: “These benefits are dependent on fuel prices, the conventional generation mix, electricity consumption, the yearly wind regime, the international market design, interconnection capacity, etc. but are considerable in any case”. Efficiency losses in the conventional power stations are hardly taken into account in his model.

2. The thesis of Soens [6] concludes on the basis of model calculations analogous to those of Ummels for the Belgian situation, that accommodation of wind energy beyond 5% of the peak demand is uneconomical. If the situations in both countries would be comparable, we would have reached our quorum in the Netherlands already with the present 2 GWatt capacity.

3. We [7] have shown that a modest overall reduction in the efficiency of conventional power stations in response to the need to compensate for wind fluctuations leads to a significant decrease in the amount of CO₂ supposedly saved by wind energy. In part 6 we will expand on this statement and introduce the power duration curve.

4. The BENTEK Report [8] concludes that the addition of 1 GW wind power in Colorado has resulted in higher rather than lower CO₂ emissions. This report is based on actual emission data not on a model study.

5. The electricity generation system in Denmark has seen major changes in the last 20 years. The effects have been carefully documented by Energinet [9].

   The Danes converted power stations to combined heat and power units, and in addition switched from coal to gas feed in 25% of the cases. Furthermore, some biomass is also used in the coal-fired stations. Finally, they added 20% (of total generating capacity) as wind power in the years 1999 to 2005.

   The graph made by Energinet shows the development of CO₂ emission per fuel unit and kWh electricity generated.



CO₂ emission by electricity production ‘wind leader’ Denmark.


The blue curve shows the CO₂ emission per fuel unit employed. The decrease is due to conversion from coal to gas in the power stations. This curve shows a decrease to 2009.

The red line shows the emission per kWh electricity generated. The red line departs from the blue line as from 2000: the reduction in emission per kWh lags the reduction per unit of fuel. As from 1999, the Danes have built massive amounts of wind turbines, and the sum total is that the red curve deviates in the negative sense from the blue one! If wind energy would save fuel and CO₂ emission, the red line would have to “dive” under the blue line after 1999. The result is the opposite deviation! Actual data (rather than model studies) from Denmark thus show:

Wind does not save fossil fuel, therefore does not reduce CO₂ emissions.


The amount of extra fuel required by conventional units in order to compensate for wind fluctuations varies. It is dependent on the overall mix of power stations (gas, combined heat and electricity, coal, nuclear, etc.) and on the policy of the power authorities: do they go for minimal cost, minimal risk, do they prefer a certain fuel type etc. Strictly speaking the figures for one country or area are not applicable to another. However, the configurations in Colorado and Texas – largely coal and gas use – are very much like the mix in the Netherlands.

Therefore the BENTEK results are quite relevant in this country. In Belgium more nuclear power is installed, and thus the situation will be different, as the nuclear stations are used in a “must run” mode. However, the difference between the two countries is not large enough to explain the different outcomes of the model studies of Ummels and Soens: Coal fired units do not differ that much from nuclear units in their “must run” properties.

4. How can we fit in the planned amount of wind electricity?


The government target is to have 12 GW wind energy installed before the year 2020, in order to be able to produce 20% of our electricity demand in a “sustainable” manner. The turbines will thus produce 12 GW at peak power. The total Dutch consumption during the low demand periods is only some 10 GW. That means that when the wind is blowing at Bft 6 we need to dispose of 2 GW of generated but unwanted electricity.

This is no minor issue, as conventional power stations cannot be stopped without consequences. A “cold start” when the wind speed decreases, and especially when the demand increases on say Monday morning, takes too long, is very costly and requires considerable extra fuel. Also remember that the lifetime of a large generator is to a considerable extent dependant on the number of cold starts. [9]

The so-called “must-run” power level is the lowest power output that must be kept available in the conventional systems. According to wind energy promoters this level is only a few GW. Power generation experts [9] put this level at 8 to 10 GW. This means that during the low demand hours must-run and demand are in balance, and that there is no room for wind energy.

The issue of fitting-in additional power can be treated by using the so-called “power-duration” curves as developed in the PhD thesis of Ummels [4]. These graphs are based on experimental data. We will review the technical details in a separate chapter (6). Our conclusion from that chapter is that when 12 GW wind power is installed in the Netherlands, a full 40% of this wind power cannot be accommodated in the Dutch grid. This result is given additional credibility by the actual data from Denmark (see below).

Export is still touted as the solution for wind energy oversupply. This argument is not valid: when we have high winds in Holland, it also blows in the surrounding countries in Western Europe. Such is the nature of our weather systems.

Let us turn again to the great example for the wind promoters, the Danish situation. The Danes produce 18% of their electricity by wind, but a full 50% cannot be accommodated locally. This oversupply is exported to Norway and Sweden, where it is used to replace hydro electricity. For about a year the Scandinavian Power market rewards electricity oversupply with a negative price of up to € 200 per MWh, or € 0,2 per kWh. CEPOS, an independent Danish scientific institute, has issued a report entitled: “Wind energy, the case of Denmark”. The authors are quite explicitly negative about the practice of supplying free (subsidized) electricity to their Scandinavian neighbors at times of oversupply, and the purchase of electricity at high cost during periods where the wind cannot deliver. We quote from page 29:

“The very fact that the wind power system, that has been imposed so expensively upon the consumers, cannot and does not achieve the simple objectives for which it was built, should be warning the energy establishment, at all levels, of the considerable gap between aspiration and reality.”

Negative electricity prices are the only way to stop the turbines, but we made it clear that this phenomenon makes the running of a conventional system virtually impossible. It endangers the overall power generation system, unless the government (i.e. the citizens) pays additional subsidies to keep the back up systems running.

We note that as from this year in the Netherlands all so-called green electricity subsidies (SDE+ ruling) will be charged directly to the customer, so that the government is no longer seen to subsidize the “green” sources.

5. Conclusions


From the foregoing it is clear that 20% wind energy cannot be accommodated in our current grid. Half of this wind-generated electricity cannot be accommodated at all, and the other half will disturb the existing system to such a degree, that fuel and emission savings will hardly materialize.

If one does want to go for wind energy, one must be patient until such a time that technology allows the accommodation of large amounts of wind generated electricity. This may once happen, but it requires years of hard work.

6. Appendix: Power-duration curves, the details


Figure 17 from [3] shows the electricity demand variations over a certain week in the year 2007.



Demand curve. (Monday through Sunday)


Such curves have been in use by the grid to balance supply and demand. We now take a full year of such curves, and then look at the total demand over 15 minute periods. This gives 365 x 24 x 4 = 35000 periods of demand. The computer program now searches for the 15-minute interval with the highest demand at puts it on the Y-axis of the graph below.





It then looks for the next highest demand per 15 minutes and plots it next. In this way 35000 demands per 15 minutes are plotted. These form the top curve in the graph. It shows the real demand- duration curve for the Netherlands. One can see that for 2007 the maximum actual electricity demand was around 20 GW, and the minimum just below 10 GW.

Next one can obtain the data on wind force per 15-minute interval from the meteorological Institute KNMI. From this one can calculate the actual wind electricity yields for any desirable total installed capacity. This wind generated electricity yield (for each relevant 15 minute time slot during the year) can be subtracted from the demand. Ummels [4] has done this for installed capacities of 2 to 12 GW in 2 GW steps. The results are depicted in the graph.

We have added a line at the 10 GW level, the “must-run” level as set by the experts for the Netherlands situation [8]. The amount under the horizontal line is the amount of wind energy that cannot be accommodated in our grid. With 12 GW wind power installed one could theoretically provide 20% of the required electricity. However, the power duration curve demonstrates that about half the time there is surplus wind current. The total surplus amounts to 40% of the supply by wind, a figure remarkably similar to the Danish situation.

The graph also shows that at the current 2 GW installed capacity there are few problems. Let us reiterate that the power demand curve and the wind data are actual and factual, and not the result of model studies!

Finally, the power duration curves also show that the efficiency loss caused by 20% installed wind capacity is much larger that the few percent admitted by the wind lobby. The capacity factor of wind turbines is on average not above 25% (even allowing for presence of a sufficient number of offshore turbines). Therefore wind electricity is generated by a set of turbines having a capacity of 80% of the conventional power stations.

The impact of the “20% wind” is thus felt by almost all conventional power stations. Throttling back the conventional stations is possible, but if the conventional stations have to be ready and operational (as in case of no wind) switching off is no option. Below a certain minimum power output level the power stations become instable and are damaged. Admittedly this is dependent on the type of station, but a power level below 30% of the nominal one is not possible. In the year 2020 , having 12 GW of wind energy installed, the Dutch conventional stations are forced to work at minimal level during half the year! Surely this is an undesired consequence of sustainability.

Notes


*Translated and partly re-edited from the Dutch text "Windmolens als stroombron" by one of us (KdG) May 2011.

1. Supply prediction sustainable energy (sic)- part 2 Short-term prognosis of wind power (in Dutch) A.J. Brand en J.K. Kok; ECN publication ECN-C-03-049
2. John Petersen: A reality check for wind power investors, 6-04-2011, (http://seekingalpha.com/article/262050-a-reality-check-for-wind-power-investors)
3. E.On: “Windreport 2005” (http://www.eon.de)
4. Analysis of UK wind power generation, [period] November 2008 to December 2010, Stuart Young Consultancy, March 2011, John Muir trust, www.jmr.org.
5. “Wind integration” Thesis Delft 2008 by B.C. Ummels.
6. J.Soens: Impact of wind energy in a future power grid. (2005).PhD Thesis. Katholieke Universiteit Leuven. Faculteit Wetenschappen: Leuven(Heverlee), Belgium. ISBN 90-5682-652-2. 257 pp.
7. C. Le Pair en K. De Groot (www.clepair.net/windrendement.html)
8. “How less became more: Wind power and unintended consequences in the Colorado energy market” by BENTEK Energy
9. “Energistatistik 2009” (www.ens.dk).
10. G. Dijkema, Z. Lukszo, A. Verkooijen, L. de Vries & M. Weijnen: De regelbaarheid van elektriciteitscentrales. Een quickscan in opdracht van het Ministerie van Economische Zaken, TU Delft, 20 april 2009 (The controllability of power stations, a quick scan for the Ministry of Economical Affairs)



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Date added:  April 15, 2011
Emissions, Grid •

Adverse consequences of wind integration

Source:  Gotschall, Harold

The following slides are examples of events/conditions associated with “as yet unaccounted” costs of wind integration (click images to enlarge):







From:  “2008 Update to the EPRI-DOE Handbook Supplement of Energy Storage for Grid Connected Wind Generation Applications”, by Harold Gotschall, Technology Insights. DOE Peer Review Meeting, September 29, 2008



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