Are Studies of High Penetrations of Wind Power Valid?

By Richard D. Patton

When examining penetrations of wind power, there seem to be two types of papers. In one type, wind penetration up to 20% is difficult but doable, and in the other type wind penetrations of 50-60% are quite easy. In fact, renewable penetrations of up to 90%-100% are claimed.

As an example of the first type, consider the Western Wind and Solar Integration Study performed by GE under contract to NREL (National Renewable Energy Lab). One of their conclusions is the following [1]:

“There appears to be minimal stress on system operations at up to 20% wind penetration. Beyond that point, the system’s operational flexibility is stretched, particularly if the rest of WECC is also aggressively pursuing renewables.”

The GE/NREL paper invites skepticism because they freely admit that their reserves are stretched and that interconnections provide extra reserves. They take up a 20/20 case – 20% wind in both the area and its interconnections. They also examine the case of 30% wind in an area, but not the 30/30 case, where both the area and its interconnections have 30% wind penetration. This is the actual case, if wind is to supply 30% everywhere. Thus, 20% is doable but 30% is much more doubtful. Note that the 30% case also had 5% penetration from solar energy, for a total of 35%.

For an example of a paper that shows high wind penetration, consider Examining the Feasibility of Converting New York State’s All-purpose Energy Infrastructure to One Using Wind, Water and Sunlight [2]. This paper has 50% wind power, and its only sources of dispatchable power are hydroelectric and concentrating solar power (CSP), and these only amount to 15.5% of the power. There is no fossil fuel energy in the system anywhere, and there is no biomass energy in the system.

The methodology for this paper is given in another paper: A Monte Carlo approach to generator portfolio planning and carbon emissions assessments of systems with large penetrations of variable renewables [3]. This is the methodology used in the previous paper. It treats the hourly wind speeds as a random variable of the mean and standard deviation of the wind speed for that date, combined with a cyclic allowance for the fact that the wind is stronger at night than during the day. It does so to simplify the problem and reduce the number of variables, so the design becomes manageable. Let’s take a look at this Monte Carlo approach. The authors state:

“The Monte Carlo simulation relies on the assumption that meteorological processes, demand forecasts and forced outages can be approximated as Markov chain processes.”

The authors then build all of their analysis on this assumption. The question then becomes – can wind speed be approximated a Markov chain process? The reason for asking this question is that if you asked a Math or Statistics prof what the most common error students make, they will tell you it’s not verifying your assumptions. If your assumption is not true, all of your work is wasted.

In order to understand what might be wrong with the assumption, we turn to Introduction to Markov Chains by Anders Tolver [4]. His first example is of a child being taken to daycare if he is well or staying home if he is ill. He achieves a series of well – ill states depending on whether his child went to daycare that day. Here is what the author has to say about that series:

“It is clear that many random processes from real life do not satisfy the assumption imposed by a Markov chain. When we want to guess whether a child will be ready for daycare tomorrow, it probably influences our prediction whether the child has only been ill today or whether it has been ill for the past 5 days. This suggests that a Markov chain might not be a reasonable mathematical model to describe the health state of a child.”

Random processes never look back, so that past cannot predict the future. In statistical terms, this means that the expected value of its autocorrelation is zero, when the time shift is non-zero. When the time shift is zero, the autocorrelation reduces to 1.0.

I tried several autocorrelations of NREL wind data. Tower M2 data was used because it was the most accessible. The autocorrelation for a 1-hour time shift for the wind measured hourly at the NREL M2 tower was 0.787 in the month of January 2018. In June the autocorrelation was 0.735. This is illustrative of the fact that wind speed does not behave as a random variable. Since it is not a random variable, Markov chain simulations are not valid.

The significance of this can be seen in the graph below. Both the orange line and the blue line have the same mean and standard deviation. The orange line represents a day in which there were strong winds which slowed down at midday and has an autocorrelation of .91. the blue line has an autocorrelation of -.076 (nearly zero).

clip_image001

Note that the random wind cannot model whether the wind is persistent or not because it has no memory. It is as likely to be high or low any time of the day.

When multiple random number series are added together, the sum converges to the average and the variance converges to zero. Here is an example.

clip_image002

As the number of independent random series added together increases, the deviations decrease. The lows become higher and the highs become lower. Translated to wind farms, this equates to the insistence that problems can be fixed by adding wind farms at different locations. If each wind farm is represented by a different random series, this will smooth at the result and make the system appear to be more reliable than it actually is. The effect of storms and calms will be lost. The intermittency is lost, because as more wind farms are added, the power output converges to a constant function. This is not true in practice.

This conclusion is not changed if the there is an effort by the analyst to add the correlation between the winds at different locations. The Monte Carlo simulation is still treating everything as a Markov chain. To repeat Dr. Tolver, “It is clear that many random processes from real life do not satisfy the assumption imposed by a Markov chain” [4]. Wind is one of those random processes that do NOT satisfy the assumption imposed by a Markov chain.

Any paper such as those cited that uses this methodology is faulty and gives a very unrealistic view of the value of wind power. This is because the technique itself tends to smooth out the flow of power from wind so that it approaches a constant value as more wind farms are added. This is an artifact of faulty math and does not exist in the real world.

Mark Z. Jacobson, the lead author of the paper on making New York 100% renewable, is a professor of Civil and Environmental Engineering and director of the Atmosphere/Energy program at Stanford University. According to his CV [5]:

“In 2009, he coauthored a plan, featured on the cover of Scientific American, to power the world for all purposes with wind, water, and sunlight (WWS). In 2010, he appeared in a TED debate rated as the sixth all-time science and technology TED talk. In 2011, he cofounded The Solutions Project, a non-profit that combines science, business, and culture to educate the public about science based 100% clean-energy roadmaps for 100% of the people. From 2011-2015, his group developed individual WWS energy plans for each of the 50 United States, and by 2017, for 139 countries of the world.

The individual state roadmaps were the primary scientific justifications for California and Hawaii laws to transition to 100% clean, renewable electricity by 2045, Vermont to transition to 75% by 2032, and New York to transition to 50% by 2030. They were also the primary scientific justifications behind United States House Resolution H.Res. 540, House Bill H.R. 3314, House Bill H.R. 3671, Senate Resolution S.Res. 632, Senate Bill S.987, and the platforms of three presidential candidates and a major political party in 2016, all calling for 100% clean, renewable energy in the U.S.”

It seems likely that all of the high penetration models are influenced by him and possess similar methodology. Since they are all faulty, at best it can be said that high wind penetrations might be possible. As of today, they are unproven and unlikely, given experiences in places like Germany and South Australia.

It also seems likely that the plans proposed and passed to reduce the carbon footprint in places like California and New York will fail badly and drive up utility bills. They are based on this faulty methodology and hence are very unlikely to succeed.

References

1) Western Wind and Solar Integration Study, prepared for NREL by GE, p 162

https://www.nrel.gov/docs/fy10osti/47434.pdf

2) Hart, Elaine and Jacobson, Mark Z., A Monte Carlo approach to generator portfolio planning and carbon emissions assessments of systems with large penetrations of variable renewables. Renewable Energy, Vol. 36, Issue 8, August 2011, p. 2281.

3) Jacobson, Mark Z., et. al., Examining the Feasibility of Converting New York State’s All-purpose Energy Infrastructure to One Using Wind, Water and Sunlight. Energy Policy, Vol. 57, (2013), p 589. www.elsevier.locate/enpol.

4) Tolver, Anders, An Introduction to Markov Chains, p. 8, http://web.math.ku.dk/noter/filer/stoknoter.pdf

5) Mark Z. Jacobson Curriculum Vitae, http://stanford.edu/group/efmh/jacobson/

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135 thoughts on “Are Studies of High Penetrations of Wind Power Valid?

  1. Even if wind was truly random, the proposed solution of just adding more towers fails because the transmission of electricity from where it was generated to where it is needed is not lossless.

    • No, but it is not so massive either.

      Again you have to look at the size of mostly anti-cyclones – and 1000 miles across is not unknown. That is one whole AC coupled grid. (over 1000 miles DC links tend to be used as AC power gets weird as time delays approach significant parts of the 50/60Hz cycle).

      The analysis of intermittent renewables IS complex, and depending on which approach you take to simplify it, important details can get lost.

      It was really to understand the variability of wind that I build my website: https://gridwatch.org.uk

      There is now nearly 8 years of GB wind generation there, in 5 minute samples and it has enabled analysts to get a real feel for the variability of wind generation.

      The general consensus is that up to 20% penetration doesn’t really affect much at all, even emissions – the thermals station losses balancing it increase and thus offset emission gains. Over that figure the very high peak to mean ratio of the wind can be accommodated, but the cost both in cash and emission terms is very high.

      High peak to mean ratio means FAT power cables of considerable length (most wind is not where the demand is), international undersea DC inter connectors, and or expensive storage like pumped hydro. The FAT power cables are needed to accommodate peak flows. The fat cables spend most of the time being grossly underutilised. This is what happens as you get above 15% or so.

      (there is a general engineering principle. Costs are incurred to meet peak situations. Benefits accrue from average situations : you could have planes 10 times lighter and more profitable (or just cheaper) provided you never had to fly through worst case turbulence… the COST of a higher renewable grid is all about meeting the twin worst cases of massive power generation in high wind/sun and bugger all in low wind/sun).

      Further on there is then the spectre of curtailment. In order to raise your renewable percentage to meet arbitrary political targets, you start throwing away the generation peaks, because its seldom coincident with peak demand, and its cheaper than building 1000 mile inter-connectors or pumped hydro to store it, even when politics dictates you pay the wind operators for every MWh they WOULD have been able to produce had anyone wanted it or been able to accept it.

      This is where – around 25% – costs start to spiral out of control as conventional plant shuts down, because they can’t cover the costs of running plant that is only generating when the wind/sun isn’t. What then happens is that cheap peaking plant – diesel and OCGT, with appallingly high specific emissions, is built specifically to arbitrage ‘times of no wind’ when spot electricity prices soar…..typically up to three times the non renewable case.

      As wind penetration goes beyond this the costs get insane. You are throwing away the peaks,. You are exchanging power with utterly remote grids, you are building massively expensive storage and paying to have thermal plant idle to cover the no wind no sun winters…10 or even 100 upside to the cost base is possible.

      And there is a vicious circle. The more expensive power gets, the more expensive windmills and solar panels are to make…

      So, it is possible to do it, but no engineer would propose such a solution…

      An engineer is someone who can do for five bob what any damned fool can do for a quid

      Unfortunately engineers have been relegated to doing what they are told. Build all renewable grids. Or get sacked.

      It’s not their fault that electricity prices have trebled…

      • “Leo Smith January 26, 2019 at 3:44 pm
        No, but it is not so massive either.

        High peak to mean ratio means FAT power cables of considerable length (most wind is not where the demand is)”

        Sounds to me, that you just agreed with MarkW, in spite of your “No”.

        • No, it’s not lossless is an agreement. Try reading beyond the first word.

          Very interesting comment from Leo, many thanks. I did not realise you were behind gridwatch. Nice one.

          • Try reading the part quoted. The way he gets losses down to acceptable levels is by using uneconomical means.

      • Very good analysis. It seems to boil down to that all these renewable projects will work but at a very high cost. What is lost in the argument is that high costs cause industry to leave along with the jobs. They move to a country not part of the climate agreement. Standard of living and real income go down.

          • Its simple really. A bob is slang for a Shilling and quid is sland for a Pound. Starting from the bottom their are 12 pence (pennies) in a Shilling and 20 Shillings in a Pound. All useless old knowledge now and of course the US had the great sense to go metric with currency but claims its the end of the world if they count in tens for anything else (will using builders tape measures that break feet into tenths of feet)

        • In Australia we had the usual pennies, treys, zacs, denars and quids but also a dollar, that was 5 bob which was the exchange rate offered to US servicemen here during the war. Today Australia, the “lucky country” has slipped to where our dollar is worth just 71c US.

          Australian lingo is poorer for the passing of the pound as it is the influence of US pop culture. All the colourful terms and rhyming cockney slang are but a distant memory.

      • Thanks, this is an excellent and very clear account.

        Gridwatch is great. Its an undeniable record or what wind has actually delivered and its been going over a long enough period for the conclusion to be obvious.

        There is a huge amount of wishful thinking with wind and solar. People who never intend to come anywhere near responsibility for managing a grid having fantasies about how it can be done. Its like desktop airplane designers telling engineers how of course some different flaky design will reduce fuel consumption safely… Or its like the health food movement gurus explaining that if you modify your acid balance you will live to 200.

        Get a job and do it, if they are so sure.

      • So to save the world from the claimed dangers of fossil fuels eevare going to impose the industrialization of remaining remote and wild places with huge wind turbines,bdolsr cell farms and power line pylons.
        This reminds me of the rationalizations used during a war the best and brightest gave us:
        “We had to bomb the village in order to save it”…

      • Using normal interties, losses are on the order of 10% for every 500 miles. That’s quite sizeable, especially since in most cases the power will have to be sent more than 500 miles.

    • There have been recent developments in HVDC lines in last decade… these are now very efficient at transporting power over distance. I believe they improved the conversion from DC…

    • Although there is a variability in the way it blows, wind is a meteorological phenomenon, and therefore there is a great regional/continental correlation of power generated over time. So… no. It is not that much random.

    • Another point is that while 20% may be doable, it will be very expensive.
      Beyond that, as the article above demonstrates, the assumptions used to reach the conclusion that 20% is doable, are not valid.

  2. Only if they count hydro (like Costa Rica does unlike the left coast states) can they claim renewables get anywhere near 100%.

    So why don’t they count hydro? Hmmm. Follow the money 🙂

    Of all the so called renewables (which really aren’t if you look at resources consumed per BTU produced) only hydro is 24x7x365 which is required for a sane modern society.

    • “Follow the money.” But while you are doing that, don’t forget to follow the COST back past the most immediate source of the money so it then becomes evident WHO PAYS for systemic inefficiencies. Follow the cost until you have reached the point that it is possible to see that it is those with the least income who are being priced out of the market by the cost of systemic inefficiency being embedded in the prices that are paid for the goods and services that they wish to purchase. So, you may say, provide subsidies to those who are being priced out of the market? 🙂

    • “why don’t they count hydro?”
      The paper does include hydro. It is relied on for 5.5% of generation, representing a ~12% increase in existing capacity.

  3. You cannot do hourly averages for windspeed when looking at electricity generation. There are massive fluctuations hidden by that smoothing. If you look at the instantaneous generation data of a windfarm, it can vary by ±10%. So the large number of turbines spread over a geographical area don’t average out. Those fluctuations aren’t there for hydro or thermal plant.
    Electricity has to be consumed as soon as it is generated. The grid frequency and voltage depends on the balance. Pretending the start was high and the end was low so average is OK is just make believe modelling.
    So anyone using averaged data either doesn’t know what they are doing, or hiding something.

    • The AEMO 2018 report did exactly that. As a direct result, two days ago both South Australia and Victoria had massive rolling blackouts.

      • Bingo, we have data on existing systems trying this experiment. See southern Australia and notice gird crisis and price crisis. If it worked already are the Aussies just ignorant? This is why we cannot have nice power, when politicians think they know something….

  4. Given Mark Z. Jacobson’s record of making bad estimates, seeing his name on a proposal is nearly enough to discount it on that basis alone.
    Given how wind and solar has worked out in practice in South Australia and the Energiewende, Jacobson’s models are preposterous.

    • Unfortunately – people that should know better – people that have or should have a basic grasp of science and engineering – embrace jacobson’s BS
      simply because their myopic view of the dangers of climate change or is that moronic view

  5. Wind is stronger at night?
    I have always noted that wind is far stronger during the day every place I have ever lived.
    Often it is breezy every day, calm at night.
    Is this a typo/mistake?

    • Wind at ground level is stronger away from sunrise and sunset when the thermal gradient is low. Wind flow becomes laminar – and as a model plane enthusiast I used to fly at dusk because of calm air below a couple of hundred feet.

      Thermal activity increases gustiness as turbulence creates gusts and lulls as the thermals roll in and past.

      So you would associate gustiness with the day time. And since most people are asleep at night, associate calmer ground level winds with dawn and dusk.

    • There are parts of the world where it is stronger at night, but that is far from universal. Here’s the diurnal hourly pattern of power output in deciles over the course of a year at the Hornsdale windfarm in South Australia

      http://nemlog.com.au/nem/quantile/hdwf1/20170601/20180531/

      It’s clear that there the softest winds tend to occur in the middle of the day, with modest breezes overnight. The strongest winds occur more frequently approaching sunset and just after.

    • I agree. Surfers call it glass off. Then there us the dawn breeze. AFAIK, there is nothing inherent to the night to make the wind stronger.

  6. Great analysis! I have been wondering how the idea that 100% wind and solar was feasible was justified. The killer case that randomization misses is the persistent high pressure system that creates hot and cold extremes, hence high power demand, while also creating low wind conditions, hence no wind power.

  7. ” This is an artifact of faulty math and does not exist in the real world.”

    (the artifact here is an “unrealistic view of the value of wind power.”)

    No.
    It is an intended feature of climate change advocacy, that is, to destroy affordable electrical energy and alter the energy market in favor of “Green” investors. That it does not exist in reality is irrelevant to the advocates and reality is intentionally ignored to further the climate hysteria propaganda, again to prop up a false narrative.

    However Richard, this a very nice paper. Well written. Easy to follow. Though the academic fraudsters like Mark Jacobson at Stanford and his fellow rentseekers must simply ignore it to carry-on with their fraudulent schemes and artifices. But like all fraudsters, history will not be kind to them when enough time has past to judge their claims and where their financial support and encouragement has come from.

  8. As of 2015 in South Australia, there was an installed capacity of 1,475 MW of wind-power, which accounted for 34% of electricity production in the state. Now the figure is higher at a total installed capacity of about 1,789 MW. The recent heat-wave problems in South Australia are starting in earnest and blackouts are following destroying industry and people’s AC right when they need it. In a recent heat wave, wind-power output fell below 20% as the calm that caused the heat wave crippled the wind-turbines. To fix it, diesel powered generators were rushed in before the peasants reached for their pitch-forks.
    Joanne Nova covered this brilliantly yesterday at http://joannenova.com.au/

    • The real calamity will occur when a cold climate locations like New York state and Vermont attempt to replicate those levels of wind penetration. It will only be on reliance of interconnects to states (and Quebec) that human deaths might be avoided. This is currently Germany’s salvation to next week’s Euro old plunge.
      These of course will also open major financial opportunities for Just-in-Time CCGT peaking plant owners to come in and make an economic “killing” by selling their very high price electricity to the spot market. High prices which state regulators will have to allow the utilities to pass on to the customers as “seasonal charge adjustments” on their bills.
      Of course, such economic opportunities from such manufactured market disruption of an existential commodity for politically connected investors is one reason that Pay-to-Play Democrats love the idea, while giving lip service to carbon emission savings (just as Germany does with it EnergieWende disaster).

  9. There is one thing that all the models don’t do, which shows they are shit, and that is look at the system inertia. At low penetration, the inertia is high, so the pulsing of the wind is damped out, and often lost in the noise of load changes. However, at high penetration, the lack of synchronous generation makes the grid very unstable – basically unmanageable. The straw that broke the camel’s back in the South Australia blackout was the lack of inertia – manifest itself as high RoCoF. It is why they now dispatch wind off to keep GTs on.
    The best mechanical analogy for a high penetration wind/ solar grid is driving a car where the engine is without a flywheel.
    There also needs to be droop as well but that is a bit more complex.

  10. As reported by ercot.com, in Texas, in 2017, there were two 19 hour periods when wind generation was below 1%. You can as many turbines as you have room for but 1000 x 0 = 0.

    • Ercot is great example of a self-contained grid. It clearly demonstrates reality where it must have Texas-based back-up/base-load generation capability for every KW of expected power from it’s ten’s of thousands of wind turbines. Fortunately for Texans several nuclear plants and lots of cheap nat gas can hide the inherent, unreliable problems of its wind power build out.

  11. Over last Australian winter I noted one ten hour period during the day when total South Australian wind output was zero, it even turned negative at times due to farms drawing electricity from the grid.

  12. ….high wind penetrations might be possible.”
    =============
    But only if they skirt the downwind pressure anomalies, always a bane to production.

  13. “The Monte Carlo simulation relies on the assumption that meteorological processes, demand forecasts and forced outages can be approximated as Markov chain processes……If your assumption is not true, all of your work is wasted.”
    Another erroneous assumption the CAGW hypothesis is based on is that human emissions of greenhouse gasses are building up in the atmosphere and we can reverse the build up by reducing fossil fuel use. If this one had been rectified 30 years ago Dr. Jacobson would have never made his erroneous assumption to design a fix for the wrong cause of the perceived potential problem.

  14. Richard Patton,
    Your expose’ of the inappropriate application of Markov Chain processes is well written and enjoyably readable. Thank You for reporting your findings here!

    It makes me wonder if Mark Z. Jacobsons’s individual energy plans lurk behind the ‘green energy’ push in the states of Washington and Oregon.

  15. What is further sad about Professor Jacobson is he is in the Depart of Civil Engineering at Stanford.

    Civil Engineers have a trust in American society, which Jacodson has severely abused IMO. But I might add, he is not a Registered PE (RPE) in California or anywhere else that I can determine. RPE’s have ethical standards for their work, to ensure what they produce as a professional Civil Engineer is of sound engineering practices and meets standards both of uncertainty in design and in formal codes for the profession. The take-down that his PNAS paper received was epic and put him and all his fellow traveller academic engineers they are being watched by their peers outside of academia, i.e. the working engineers that politicians and know-nothing regulators would demand they try to make work in the real world.

    • Jacobson wrote a paper that contended that 100% renewable energy is feasible.

      21 scientists wrote a paper rebutting Jacobson’s paper.

      Jacobson sued those scientists and PNAS because the resulting press coverage …

      … made him look “sloppy, incompetent, and clueless.” link

      Hah!

      Although he teaches engineering, as far as I can tell Jacobson has never been a professional engineer. link

      • He withdrew the lawsuit I believe. His DC lawyers were probably initially funded by some deep-pocketed Green interests that support Jacobson’s renewables work. Once they really got into the meat of it, they realized they:
        1) had no chance of winning,
        2) continuing the suit with the media interest would only publicize Jacobson’s incompetence as an engineer (to be gracious),
        4) give Stanford’s CE department a reputational black-eye, and
        3) they’d likely have to pay the defendant’s legal costs in the end.

  16. Thanks for this.

    A Monte Carlo approach was successfully used, I think, in the study of vibrations as the U.S. missile and space program was underway.
    It seems there is much work done today without examining data to see if it fits the method of analysis.

    • In both SE Australia and NZ, it has been shown that windfarms at either end of the network have significant co-relation, especially at times of low output. Organisations like Renewables UK only talk about models because they know that the actual data doesn’t support their assertions.

    • All you need to do is look at a few large scale weather maps to know that winds are highly correlated over days of time and continental scales of geography.

      • Especially in the case of huge stagnant high pressure systems which in the US can be as big as half the country or more and last for a week or more. They feature low wind conditions because there is no pressure gradient. These are far to large to resolve with interconnection.

    • I did my own back-of-the-napkin analysis a few years ago. I got historical hourly wind speeds from a couple dozen airports all around the US for a period of about five years. I made some rough assumptions about min and max useable speeds, then calculated the the mean square wind speed at all locations for each hour. (Square since kinetic energy varies as the square).

      What I found was that the total appeared to be almost completely random, with a very weak negative correlation to some electrical demand data I had. (Wind data and load data from different years – VERY rough analysis).

      What smoothing effect there was from the large geographic area still permitted violent swings in output. There were several brief periods of about 10% maximum output. (Hours? Days? I don’t recall – but even a one hour blackout gets attention.) Essentially 1:1 backup with reliable power is necessary. There is no avoided cost with wind power.

      • (Square since kinetic energy varies as the square).

        You should have used the cubed speed. Extractable power of a static wind turbine also needs the rate at which the wind energy is passing a static point. Wind speed data sometimes include the cube for this reason. I made the same incorrect assumption as you did until I came across this.

      • I can’t speak for observations in the US.

        My study of European wind data, obtained from METAR reports over 9 years from nearly 50 airports reveal both time and geographic correlation. This is not surprising because Europe is crossed by successive areas of low pressure and occasional periods of widespread high pressure. This is not good news for the wind industry. If wind generation was random, as you say you observe, then we could expect that the higher penetration of wind over a geographic area, the more likely the output of an installed wind fleet would approach a value equal to the capacity factor.

        The nonsense of that last sentence might explain why some claim that the capacity credit of wind (used when calculating LOLP for a grid system) is equal to the capacity factor. Collection of the enormous amount of wind data I describe above allows me to produce a wind generation time series to model the variability and intermittency of wind. I can use this time series alongside fossil fuel production distributions, and thus compute LOLP for the UK system. At the present level of wind installation, the capacity credit for the wind fleet is about 5 % of nameplate capacity.

        In the UK there has been a recent claim from government that the capacity margin is 11 %; I think they’re assuming that wind generation is completely random, the error that the author of this paper has revealed.

  17. Denmark claims it is doing 43%. link That’s because Denmark is connected to Germany, Sweden, and Norway. Denmark is less than 10% of the overall grid.

    What counts is the effective size of the grid. As commented above, if everyone on the grid is doing 20%, nobody can go above that without causing problems.

    Mark Z. Jacobson teaches engineering but I can’t find any evidence that he has ever had a license and practiced. His career appears to be entirely academic. In that regard, he has no more credibility than any other bloviating expert.

    • It strikes me as pathological how democrat-run states and municipalities gravitate towards this kind of impractical academic nonsense.

    • A local food store, which purchases renewable electric shares claims 100%.

      No one in authority will go after them for a false advertising claim.

    • Denmark’s electricity production from wind is 43% but their carbon emissions haven’t gone down. That is the take home from it. Wind doesn’t work.

  18. Energy is not free if you pull the KE out of the wind in large amounts you will change the wind patterns because the wind will be slowed down as the KE is pulled out. Its easy to calculate but I have not seen in considered.

    As to solar well its a mixed bag but very large areas of PV panels change the earth’s albedo which also means they will warm the planet by the conversion percentage i.e 100 watts absorbed and 30 watts of electrical power generated plus 70 watts of heat. This basic calculation would have to be adjusted by the albedo of the surface where the PV panels were place.

  19. A recent paper produced by Australia’s intermittent energy proponent ARENA takes a somewhat realistic view of what they term Dispatachable Variable Renewable Energy. The figures given for costs are optimistic but the methodology is quite good:
    https://arena.gov.au/assets/2018/10/Comparison-Of-Dispatchable-Renewable-Electricity-Options-ITP-et-al-for-ARENA-2018.pdf
    It makes interesting points such as:
    1. LCOE has been misused to compare intermittent generators and dispatchable generators – this is a first in Australia.
    2. There is an optimum amount of energy collection overbuild to produce dispatchable power that depends on the cost of storage and the period of firm power.
    3. Dispatchable solar is inevitably lower cost than dispatchable wind due to the greater certainty of solar on a daily basis (this is from actual data in Australia where sunshine is good over all of the big island)
    4. Dispatchable rooftop solar at the load using battery storage is more economic than dispatchable grid scale solar with battery storage due to cost of transmission.
    5. At fundamental level modern coal fired generation is about half the cost of dispatchable VRE but giving intermittents priority access to the market due to their high merit order makes coal fired generation much more expensive (reduced volume to spread cost).
    6. No one will invest in grid scale Dispatchable VRE without subsidies.

    One myth it still promotes is the diversity fairy but there is a statement about this being a technology comparison and not a system based comparison.

    Another factor that is becoming apparent in Australia is so-called curtailment, which means output being restricted below potential output. The wind generators in South Australia are regularly restricted. When the wind increases rapidly, the price usually goes negative so the gas turbines come off load quickly to their minimum, set by stability standards, until the wind generators are wound back. At those times the gas fuelled generators are paid to stay connected on a separate scheme to power payment for the stabilising rotating inertia they offer.

    Also the grid scale solar generators in Queensland have realised that the sun rises and falls at the same time in a single time zone (who could have predicted this). The wholesale cost of power is tanking through the middle of the day due to the high take up of rooftop solar. In fact in the cooler months when air-conditioning demand is low the wholesale price has been negative through the middle of the day. The rooftops are paid a mandated price irrespective of time of generation so the only factor that limits their output is local over voltage. Reverse power flow has become a significant factor for distributers and handing the high generation from traditionally load areas is an added cost.

    As yet there is no one questioning the idiocy and cost implications of permitting intermittents to have priority access (they have stamina bids in the market at a large negative price to ensure supply if they can produce it). This reduces volume for low cost dispatchable generators until one of those falls off the perch (so far two coal generators have gone). The coal generators continue to supply base load at very low marginal cost until the intermittents build enough capacity to destroy the next level of base load and eat away at the volume of the low cost coal. Very expensive gas and some limited hydro fill the gap when sun is down and wind is low.

    The actual economic market share for intermittents depends on the nature of the existing grid. It the grid has existing 10% hydro then 10% to 15% intermittents might actually reduce costs, particularly if perched storage is restricted. In Australia electricity costs started to rise once intermittents got to around 5% of market share.

    My personal view is that intermittents should not have been given market access via the grid. There are some circumstances where they offer value such as location remote from an existing grid when competing with diesel generators.

    I have both household on-grid and off-grid solar systems. Income from electricity pays for my gas heating requirements but I recognise that this would not be possible without generous subsidies that electricity consumers are forced to pay me.

    • I have looked at the AEMO “100% Renewables” 2012 study which was heavily influenced by the work of Andrew Blackers. Here’s a chart that looks at the cumulative deviation from average wind output over the 9 years of simulation:

      https://uploads.disquscdn.com/images/b4e6133c77a943ffc3fc369885ebd0d6285d923fd65856ab820fcd2f32fe2994.png

      It is immediately apparent that the methodology for the final two years is radially different from the first 7, where a seasonal cycle dominates, with very little random variation (which would give a “hairy” appearance to the curve) outside that: conveniently, solar power shows almost the exact opposite seasonality. Bear in mind that a positive slope implies above average output, and a negative slope below average output, and that July is midwinter.

      When I analysed the data more fully, I discovered that the inter-regional correlation matrix was essentially singular: that is a sure sign of using statistical fixes to generate the data.

      It is plain that these data are nothing like a real world picture: here’s European wind and solar output across 2016

      https://uploads.disquscdn.com/images/2d016b56defbd182eed5d112b26a2ef5a7f598add0e542eee5974d1f821a91c1.png

      Here’s a breakdown by country of the wind element:

      https://uploads.disquscdn.com/images/299a16b711c550d558abacd71da89ad95c4991579bdda2151a3b7936d47bbbf0.png

      These are qualitatively very different from the fake data Blakers used.

    • I’ve looked at the ARENA study. It fails to tackle the real issue – which is how much storage do you need? For Australia, with a 100% renewables system based on wind and solar, the answer is of the order of 10TWh at current demand levels in order to cover for a bad month in a bad year – perhaps more. Snowy 2 is 0.35TWh. You need to find locations and pay for another 30 Snowy 2 schemes. For the UK, and equivalent figure is of the order of 35TWh, because demand is much more seasonal. Our biggest store, Dinorwig, is 0.009TWh. Excluding stockpiles of coal and nuclear fuel, of course.

      • The ARENA report specifically states that it does not take a system view. Also they are really not looking beyond about 50% intermittents. That way base load coal generators can work steadily and efficiently. The report does give a figure for storage but it is from a different study:

        By 2030, for a 50% renewable scenario, the modelling showed a need for 5 GWh of stored energy to maintain power system adequacy and 16.8 GW for system security.

        The comment goes on to say that storage increases significantly above 70%.

        Solar in Australia is getting impressive capacity factors with new tracking arrays, particularly those in northern Queensland on the western side of the ranges.
        https://www.rpc.com.au/pdf/Solar_Radiation_Figures.pdf
        The new solar generators in Queensland have insolation similar to Longreach in the linked table. Note even the worst month in this location for a tracking array averages 8 hours full sunshine equivalent per day. The data from the new installations are almost constant output from 9am to 3pm summer or winter.

        • South Australia is at 50% renewables. 5GWh would have covered 180 minutes of their heat wave crisis if they didn’t have the reserve fossil fuel capacity. That’s meant to cope with the whole of Australia, not just 10% of it? And for sustained periods of low renewables output? It’s a joke, not an estimate.

  20. Most annoying to me is that there are plenty of meteorological data sets that include wind speed and direction out there. Not too difficult to get one and apply it unless of course you know it may not get the answer you want.

      • I think it’s worth having a look at the work of Staffel and Pfenniger who do seem to try to tie back/calibrate with real wind output data based on reanalysis of weather/satellite data.

        https://www.sciencedirect.com/science/article/pii/S0360544216311811

        they claim We model hourly national capacity factors with R2 > 0.95 and RMS error <4%

        An advantage is that they provide a long run of hourly data across a wide area of Europe. Data are freely available from

        https://www.renewables.ninja/downloads

        Big files ~130MB you’ll need a 64 bit spreadsheet.

        I’ve looked at some of the correlations across Europe, with time lags (it’s immediately clear that on average Ireland gets much the same wind as we do a little in advance, as you’d expect), which show significant high levels of positive correlation until you move into completely different weather regimes – e.g. Greece/Cyprus – though no anti-correlation that is really needed if you hope that it will be windy somewhere else. I really should try looking at scatter plots between modelled and actual data, and trying to spot patters in the differences between them.

        • Thanks for the reference, I’ll look at it in detail.

          But just quickly, they give for
          onshore UK wind capacity factor of 29.1 %, REF actual 2017 is 25.4 %.
          offshore UK wind capacity factor of 38.4 %, REF actual 2017 30 %.

          These are quick calculations, but they’re also large errors.

          • You have to be careful which data set you are looking at. I remain somewhat suspicious of their assumptions for the performance of future wind fleets (and solar come to that, as I don’t think I know of a UK solar farm with 1or 2 axis tracking). Better are their assumptions around the existing wind fleet.

            I did find it instructive to look at manufacturer claims for turbine performance curves in comparison with Betz limit theory. Real world performance is somewhat smeared around the claimed curves anyway due to effects such as inertia of the spinning blades and differential wind flow across the disk, measurement error, etc.

            http://drømstørre.dk/wp-content/wind/miller/windpower%20web/en/tour/wres/pwr.htm

            (incidentally, the whole Danish presentation (in English) is excellent for anyone wanting to get properly up to speed with understanding technical issues about wind turbines, and particularly good at explaining several common fallacies)

  21. So why doesn’t the media expose this lunacy? They can’t all be barking mad or is that just my silly optimism?

    • It is too complex for someone with basic maths to comprehend.

      Anyone with basic maths can see that solar panels producing electricity at $60/MWh is cheaper than the wholesale electricity price of $80/MWh from coal. So more solar competing with coal is obviously going to lower the cost.

      Anyone who brings up the notion of dispatchable electricity is just a denier. I was told today I am going to hell because I do not support intermittents:
      https://reneweconomy.com.au/grid-held-together-by-solar-load-management-as-coal-fails-in-heat-18324/#comment-4307849252

      • Anyone who brings up the fact that the sun sets everyday (except the highest latitudes at summer) is also labeled a denier.

      • More to the point… it is too complex for the vast majority of journalism majors to grasp. So what do they do? Like the sheep they are, the trot on over the academic Mark Jacobson rentseeking wolves for some comforting bias confirmation.

  22. So Jacobson is likely behind this latest round of US states pledging to go 100% (or so) renewable. I lost track of his lawsuit against some who disagreed with his paper.

      • Thanks, commieBob!

        From the link you supplied:

        “RW: Your case has drawn many comparisons to the defamation filed in 2012 by Penn State climatologist Michael Mann’s in the same court. Mann’s case has been going on for almost six years. How long did you think yours would take?

        MJ: When I first set out, I figured it would take on the order of a year. It should never have gone to court in the first place.

        I was expecting them to settle. What I found was not one bit of interest in settling. It surprised me a bit that their attorneys made no effort to settle, they were only interested in dragging it out

        Basically, he did it to get the press headlines and hopefully to scare the contrary scientists and publication into caving and paying a substantial early settlement fee.

        Since Jacobsen dropped the suit days after the Court hear oral arguments, it is far more likely that he realized he was not going to win, it was going to be very expensive and that he would then be liable for all court costs.

        • The defendant’s attorneys were not interested in settling because they knew Jacobson would lose his ass and his DC Green-fund backers paying the legal bills would get soaked for defense legal fees.

          Jacobson is just trying to whitewash the fact that his original lawsuit was just hot-air bluster to cover his malfeasance as an academic engineer. When the other side didn’t blink, he knew he was standing naked and the tide had gone out.

      • Sounds like he got his feewings hurt, tried to intimidate them and it backfired.

        RW: How much have you spent on this case?
        MJ: I decline to comment.

    • Fascinating when it starts coming together. All because of one unfounded assumption in one stupid paper

      This unexplained discrepancy [in Jacobson’s paper], they argued, unraveled the entire premise. If Jacobson can’t balance the grid without an inconceivable and unexplained multiplication of installed hydro capacity, then one can no longer accept the conclusion that the 100 percent renewable grid is a realistic goal.

      This isn’t simply theoretical. The research has migrated into the policy realm. Hawaii has legally committed to 100 percent renewable energy; California tried to last year. Solar executives and Hollywood stars have taken up the 100 percent renewables rallying cry, and they tend not to include a footnote about the hydropower question.

      The dispute did not stop advocates from heralding the 100 percent renewable vision. For the sake of scientific completeness, any such pronouncements should include a disclaimer that the vision relies on a massive expansion of hydropower capacity without any practical mechanisms to deliver it. That adjustment, however, would threaten the snappiness of the slogan.

      https://www.greentechmedia.com/articles/read/mark-jacobson-drops-lawsuit-against-critics-of-his-100-renewables

  23. This is an excellent paper explaining why the citizens of California and NY State in the not to distant future are going to some super pissed of people when it dawns on them they’ve been scammed by the governments.

    • The usual play out is the Democrats milk the system to just before it collapses.
      The voters get a clue, and vote them out. The newly elected Republicans are left holding the bag of dog poop that is on fire.
      Voters blame the Republicans for the mess the Dems left behind (healthcare is on example).
      Dems come back as voters forget it was Dems who made the mess in the first place (like underfunded govt pension promises).

      The problem for the Dumbocrats in California is they have now enacted an electoral system that strongly favors incumbents and liberal “vote harvesting” on election day. In the coming few years as Cali heads into the economic toilet by the smoldering bag of dog feces Moonbeam left behind, there won’t be a GOP Arnold Schwarzenegger Useful Idiot governor to blame.

      • Interesting. I had never heard of ballot harvesting before. Could it have affected the election? I have no clue. I do prefer my mid-continent explanation that the west coast attracts crazies.

        Actually, California may produce crazies. California is more urbanized than the nation as a whole. link Living in cities increases the danger of schizophrenia. link Wow … just wow … I think I just found an explanation for the Democrat/Republican vote distribution in America.

        Recently, however, population density has become a strong proxy for political preferences. Today the 13 most densely populated states have 121 Democratic House members and 73 Republican ones; the remainder have 163 Republicans and 72 Democrats. According to data compiled by Jonathan Rodden of Stanford, nearly half the variance in the county-level vote shares in the presidential election of 2016 could be explained solely by their number of voters per square kilometre. link

        Population density produces schizophrenia and population density produces Democrat voters. I know, I know, correlation is not causality. 🙂

        • Republicans have finally woken up to the long history of Democrats working the dead vote, the illegal alien vote, and the felon vote. GOP-run states have enacted enacted ID laws, they purged voter rolls of dead people, and uncovered illegal alien voting. The Supreme Court has upheld some or parts of many voter ID laws in various states. Cal’s Democrats, ever resourceful with a Democrat Party run Assembly and governor, have found a new artifices for voter fraud.

          And ballot harvesting/voter harvesting Cal now has is such a rich fertile ground for activism, yet so distributed and subtle for real voter fraud, that is will be so hard to investigate, much less prosecute.

          This will be HUGE issue in the 2020 elections as dishonest Dumbocrats, desperate to remove Trump from the WH, will try to force the swing/purple states to adopt ballot harvesting.

  24. Of course,just because large percentages of wind power is feasible for a given area doesn’t mean it makes any sense to use it. Wind turbines are environmentally obnoxious – their geographic footprint is enormous. And the recent study demonsttrated that the technology, especially the preferred enormous 2MW+ turbines have a very short lifespan and their output capacity reduces significantly with age. This is a primitive, uncontrollable technology that belongs in the 16th century, where it began. When will these morons learn that advanced nuclear technology, especially small modular molten salt nuclear reactors are the future. I guarantee you that India and China believe this, as they have banned govt support for wind power, declaring it disruptive of the grid, and are actively developing molten salt reactors,as well as building quite a few conventional light water nuclear reactors. Wind power truly sucks.

  25. Even if the wind is random and indendently dustributed don’t you still have to maintain and build lots of turbines ? There is a trade off between having enough turbines all over the place to smooth out the power generation and the cost of the extra turbines and maintaining them.

    • Yes exactly, and at the risk of re-stating the obvious if regions A and B are required to cover the shortfall in adjacent regions C and D then regions A and B have to have enough capacity to cover the demand in all four regions A, B, C, and D at the same time. That’s a hell of an overbuild (and someone else in these comments has pointed out that even an infinite overbuild cannot cover for the certain eventuality of no wind anywhere).

  26. “Mark Z. Jacobson, the lead author of the paper on making New York 100% renewable”

    Several years ago I took a deep dive on this subject to assuage my own curiosity, looking at the only large set of real numbers I could find:

    https://energy-charts.de/energy.htm

    Based on the numbers available at the time, up to early 2016, it was clear that Germany would repeatedly see periods of 3-6 weeks where it would require hugely more solar, wind, and storage resources if it would power itself with a domestic “renewable” infrastructure. Vastly more. A later look at energy import/export also confirmed that Western Europe could not likely do much to solve regional temporal challenges via long-distance undersea and overland interconnects. Not to mention the security implications of a national economy which hangs from an undersea thread.

    About this time Jacobson was telling the world that 100% renewable was a piece of engineering cake and I called him out on it, and suggested he look at the real numbers from Germany. He would not hear of it.

    My takeaway was that snake-oil salesmen make the money and at some point the engineers take the fall.

  27. Switzerland and Germany were traditional examples of grid stability.

    Today Swiss Grid has already dropped the concept of public service, meaning, we’ll do at best with what we have, our service is no more guaranteed.

    The actual situation is well described and documented in this post:
    http://notrickszone.com/2019/01/26/the-green-energies-of-instability-swiss-power-grid-requires-200-fold-more-intervention-than-8-years-ago/

    Our outages and breaks learning curve progresses fast.

  28. To take a simple example, let’s build a grid with 30% wind generation on average. Allowing for an average 30% capacity factor, that means that when the wind blows strongly, wind could theoretically supply 100% of demand. So all other generators must be idled. But on occasion when the wind doesn’t blow, back up generators must be available to supply 100% of peak demand. We now have a grid with 100 % wind nameplate capacity, and 100% deliverable other generators. Double the investment.
    The Australian experience has been that large high pressure systems can stall over all of south east Australia. The grid there has a nominal wind generation capacity of 5,500 MW but on occasion wind only supplies 200 MW in a grid that requires 22,000 MW on average with a peak of 33,000 MW.
    The alternative is storage. Batteries have yet to prove themselves (Sth Australia installed the “”world’s biggest battery” courtesy of Elon Musk with a capacity of only 129 MW for one hour). Hydro is the most effective storage, and wind can be paired effectively in places where hydro is available. In the Australian grid hydro supplies about 2,000 MW on average, with a high of about 5,000 MW.
    But in the world’s wind test bed of Sth Australia, there is no hydro. Wind nameplate capacity is 1900 MW and total demand varies from 700-2000 MW with summer peaks up to 3000 MW. Their other sources of power are solar and gas. They survive because of a 650 MW interconnector to the far larger Victorian market that has coal, gas and hydro. But Victoria has plans to go to 50% “renewables” and is already experiencing shortages in peak times.

    • Jay got thrown out before he had to make the phone call to Dan. In any case once Hazelwood went Dan was in the same boat as Jay. Now Dan has to call both Bill and Gladys to keep the lights on.

      It appears they will go on building these things a long way into the future and keep wondering why power prices keep going up and reliability keeps coming down. If they left the city and went out into the country for a road trip they would get a better appreciation of why wind generators are a waste of money.

    • Victoria was using over 2GW of Snowy hydro and 500MW from Tasmania via Basslink during the heatwave. Even Snowy 2 isn’t going to help if they go to 50% wind.

  29. Testing my new emergency generator tomorrow; next house will have full propane standby generator capability. Dependable power is to important to leave to anyone who either believes in renewables or is required to comply with a renewable mandate.

  30. I made my living for a good number of years doing Monte Carlo simulations of objects going through the atmosphere. If my assumptions of the variation of the atmospheric parameters were as wrong as these authors used, there would have been some notably bad things going on.
    (Of course, there are efforts to improve things so that simpler prediction methods such as these can be used.)
    I had to revise my initial hack at the work because randomizing some things based on a normal distribution using the mean and standard deviation does not result in the right answer in the real world.

    This is the problem with all of these climate studies. There is no check on whether the answer is correct. Even if the things done seem logical, that does not mean that they are correct in the real world.

  31. Finally, some light shines down on the madness.

    Without energy storage, wind generated energy will never be reliable enough to exist without nuclear or fossil fuel backup power. It just is not economically viable to build batteries big enough to store a reasonable amount of backup power using existing technology (but maybe someday it will be). Until then, Wind is at best just intermittent, and completely unreliable at worst. You just cannot build a nations power grid based on the premise that “everything will work just fine”.

    Say you build more and bigger wind farms… It takes one big event (like a hurricane, or severe winter storm) to knock out hundreds of the turbines – and this could be spread over a huge area. It just takes one big high or low pressure system to become stationary to reduce the output of wind energy to 1/10th its normal for days or even weeks. Because wind power is so remote, you end up building lots of feeders to trunks to get the power moved about – it takes one trunk to cut off half or more of your power, and its more likely as those trunks become more distant from the cities that use the power. I have been arguing for years that you cannot just assume that wind is available 100 miles away when its quiet nearby – it depends on the weather system.

    Can wind supply some of the load – yes, but at a higher cost. No one seems to realize that wind turbines wear out and need to be taken down, replaced, and something down with the old parts. Add the costs of replacement and recycling or turning into waste the last generation wind turbines, add in the costs of batteries to even out the load a little, the cost of backup power sources for when there is a long term disruption, and the costs are ridiculous. Just build a reliable nuclear power plant and be done with it.

    Just imagine a long cold winter system where its cloudy and the wind is quiet for a week. Heating needs are peaking, solar is almost dead, and wind turbines can barely rotate. Now imagine that is a few hundred miles across. Then imagine neighboring power grids are already stretched because of cold temperature. This is a very real possibility. What do we do then? Let Kansas freeze? Or Ohio, or…

    Modern society needs dependable power grids and sources. The source needs to be a close to the users as feasible. There needs to be enough capacity to allow for maintenance and a the unexpected. Wind Turbines fail at all of these missions. It is a wonderful niche power source where the main grid will not reach. Leave it at that.

    Kill the Wind Warts! They are ugly, destructive to birds and bats, and expensive. Only the rich pushing their use and making huge profits off the subsidies are winning.

  32. “… they are unproven and unlikely, given experiences in places like Germany and South Australia. It also seems likely that the plans proposed and passed to reduce the carbon footprint in places like California and New York will fail badly and drive up utility bills …”.
    =====================================
    That is the purpose of these ridiculous contraptions viz. to reduce demand or euphemistically “demand response” through ever higher prices.
    Empirical evidence trumps computer models every time — mad professors or your own eyes, who are you going to believe⸮

  33. WHAT IS GRID-CONNECTED WIND POWER REALLY WORTH? [GERMAN EXAMPLE]

    Wind power is intermittent and non-dispatchable and therefore should be valued much lower than the reliable, dispatchable power typically available from conventional electric power sources such as fossil fuels, hydro and nuclear.

    In practice, one should assume the need for almost 100% conventional backup for wind power (in the absence of a hypothetical grid-scale “super-battery”, which does not exist in practical reality). When wind dies, typically on very hot or very cold days, the amount of wind power generated approaches zero.

    Capacity Factor equals {total actual power output)/(total rated capacity assuming 100% utilization). The Capacity Factor of wind power in Germany equals about 28%*. However, Capacity Factor is not a true measure of actual usefulness of grid-connected wind power.

    The true factor that reflects the intermittency of wind power Is the Substitution Capacity*, which is about 5% in Germany – a large grid with a large wind power component. Substitution Capacity is the amount of dispatchable (conventional) power you can permanently retire when you add more wind power to the grid. In Germany they have to add ~20 units of wind power to replace 1 unit of dispatchable power. This is extremely uneconomic.

    I SUGGEST THAT THE SUBSTITUTION CAPACITY OF ~5% IS A REASONABLE FIRST APPROXIMATION FOR WHAT WIND POWER IS REALLY WORTH – that is 1/20th of the value of reliable, dispatchable power from conventional sources. Anything above that 5% requires spinning conventional backup, which makes the remaining wind power redundant and essentially worthless.

    This is a before-coffee first-approximation of the subject. Improvements are welcomed, provided they are well-researched and logical.

    Regards, Allan
    ____________________________________________________________

    NOTES (Edited):

    The excellent E-On Netz Wind Report 2005 (1) provides excellent information. See Figure 7 re Substitution Capacity.

    Sadly, green energy is not green and produces little useful energy – intermittency and the lack of practical energy storage are the fatal flaws.

    Germany has calculated that it needs 95% spinning backup of conventional energy (e.g. natural gas turbines) to support their wind power schemes – it would make much more economic sense to just scrap the wind power and use the gas turbines.

    Driving up energy costs just increases winter mortality, which especially targets the elderly and the poor. Excess Winter Deaths in the UK this year totaled over 50,000, half the annual average 100,000 in the USA, which has FIVE times the population of the UK.

    When politicians fool with energy policy, real people suffer and die. Most politicians are so scientifically illiterate they should not even opine on energy, let alone set policy.

    Posterity will judge this climate/ green energy nonsense harshly, as the most costly and foolish scam in human history.
    ____________________________________________________________

    REFERENCES:

    1. “E.On Netz Wind Report 2005” at
    http://www.wind-watch.org/documents/wp-content/uploads/eonwindreport2005.pdf

    2. DEBATE ON THE KYOTO ACCORD
    PEGG, reprinted in edited form at their request by several other professional journals, THE GLOBE AND MAIL and LA PRESSE in translation, by Baliunas, Patterson and MacRae, November 2002.
    http://www.friendsofscience.org/assets/documents/KyotoAPEGA2002REV1.pdf

    This is what we KNEW in 2002:
    [excerpts from our Rebuttal in the APEGA debate}

    “The ultimate agenda of pro-Kyoto advocates is to eliminate fossil fuels, but this would result in a catastrophic shortfall in global energy supply – the wasteful, inefficient energy solutions proposed by Kyoto advocates simply cannot replace fossil fuels.”

    “Climate science does not support the theory of catastrophic human-made global warming – the alleged warming crisis does not exist.”

  34. The real situation is that winds are driven by low and high pressure regions which can vary in size from a few miles across up to that of a large country. When a large system sits overhead, which it can do for days or even weeks, with no pressure difference to drive airflow the wind output for that entire region is zero.

    We’ve had this situation in the UK many times, where winds are near nil for two or three weeks at a stretch. This casts a totally different light on the need for backup capacity compared to a purely random wind distribution, in which so long a total outage would be a statistically rare event.

  35. Every 20 years or so you have to replace all the major parts of all the turbines…… at the top of a 300ft tower.

    No problemo for an academic at a University desk.

  36. Why bother with models when you have real working examples of higher wind penetration in real life?

    Eire in 2015 had 23% of electricity from wind and is almost entirely powered by gas/wind generation…

    UK was 15% in 2017… same as Germany’s onshore turbines.

    Spain had 23% of wind power in 2017.

    • And Australia produces on average 32% of installed wind capacity in a year but lefties simply don’t do marginal analysis-
      https://anero.id/energy/wind-energy/2019/january
      they seem to ignore seasonal variation completely-
      https://anero.id/energy/wind-energy/2018/june
      Notice the virtual zeros but all they see is a lovely hump.
      https://anero.id/energy/wind-energy/2018/april

      No matter just grab the headline 32% figure and ooh and aah over that. I take my car in under warranty because it’s hard to get going some days and it suddenly decelerates to a crawl or lurches forward and takes off with a mind of it’s own and Griff the mechanic tells me no worries it’s all fine mate as you’re achieving the average kms a year for that model.

    • Ireland depends on being able to dump surplus wind on the UK (and curtails it to ensure that the grid remains stable with sufficient inertia) – and then depends on imports when the wind isn’t blowing. The balancing flows are up to +/-1GW. You can see these modes of operation in the period of Storm Ophelia in this chart (although the Moyle interconnector was limited to 250MW at that time, so it was +/-750MW):

      https://uploads.disquscdn.com/images/12fcfe6e695b58a2a497ed4521dd30b631cb058268799591829498342f4e951b.png

      Peak demand was about 5.5GW, so a swing of 1.5-2GW is a substantial fraction of demand.

      Spain is also significantly dependent on interconnectors to nuclear powered France.

      You can’t view those grids as isolated instances.

    • griff likes to pretend that each nations grid is independent when he makes these absurd claims.
      He’s been corrected over and over again.

  37. in doing an assessement of the capabilities of wind generation, surely the output should be used not wind speed as the two do not have a linear relationship. From what I’ve read the relationship of wind speed to power output is a cube law so small wind speed deviation produces larger power deviations?
    Perhaps that might convince these modellers that their conclusions are wrong. And it would be useful also if they actually looked at real installations to see how poorly they work?

  38. In June the autocorrelation was 0.735. This is illustrative of the fact that wind speed does not behave as a random variable.

    So who was saying it did. You start out explaining they subtract a diurnal cycle, so at least you need to do the same before looking at the a/c of the residuals. what you are currently doing is a straw man.

    • A very simple approach is to aggregate into 24 hour periods. I have presented data on that basis in this thread: it shows a large disconnect between modelled and real data.

  39. GB National Grid status 24 January 2019 at 11.35.
    Demand 45.71 GW
    Wind 0.26 GW or 0.57% of demand (Installed capacity per RenewableUK is “Operational Capacity (MW)
    20,687.505”. That is 20.68 GW. So all the turbines installed on and off shore managed just over 1% of installed capacity. Wow.

    Most of the demand was met by dispatchable energy including coal at 6.89 GW. Of course the UK Government have plans to shut down all coal plants by 2025. Nuclear provided 6.11 GW and the Government is struggling to replace our nuclear power stations. So beyond 2015 it would appear that a return to paraffin lighting and wood stoves will be required.

    • “the UK Government have plans to shut down all coal plants by 2025”

      I suspect they will convert them all to burning wood pellets, as they have done at Drax.

  40. I just had a look at M2 tower data ( which you forgot to link in the article ).
    https://midcdmz.nrel.gov/nwtc_m2/

    Here is their wind speed plot for 26/12/18 to 26/1/19 at 80m
    https://climategrog.files.wordpress.com/2019/01/wind-80m-m2-colorado.png

    Of course it’s auto-correlated. Now subtract that cycle and try again. Also remember that by taking hourly averages you’re reducing the variance and messing with the stats.

    You do not say explicitly what data you were using but it seems to be a monthly average of hourly rates as I showed above. Again you are reducing the variance and leaving an auto-correlated cycle.

    You need to be as critical ( or more so ) of your own methods as you are of the papers you wish to challenge ( see Feynmann ).

    This is an important question and you may have valid points. You need to apply valid methods to support that. It seems here you are diving straight in with the bias confirmation since you are opposed to wind generation and not seeing the serious flaws in your processing.

  41. Everything Jacobson writes about wind and solar can be ignored. His models have been thoroughly torn apart by the community of serious modelers.

    The GE/NREL model studied instantaneous penetration, not annual energy penetration.

    A system that can only handle 20% of power from wind and solar at a given moment (instantaneous penetration), will get something less than 10% of energy from those resources over the course of the year (annual energy penetration).

    Transmission planners talk about the first type of penetration. Politicians and activists talk about the second. Because they rarely speak to each other, they use the same word to mean two very different things.

  42. Our local Melbourne TV invested 15 minutes to show parents how to make schoolday lunches for their kids.
    In the good old days they would include some kids in the show to road test the theoretical advice.
    Not these days, when advice from authority reigns.
    Even more interesting would be footage showing pupil after pupil throwing lunches into bins, unopened and untasted, as tuck shop volunteers see daily.
    I could not resist this quick mention of how domination by authority – even by self-appointed authority – is eating away at the order of society.
    In just the way that leads to multiple yellow vests on French streets. Geoff.

  43. From the ‘Monte Carlo’ paper:
    “Wind speed realizations are produced using an algorithm that includes treatments of the temporal and geographic correlations and any diurnal character present in the wind speed dataset.”
    I don’t think this analyses’ representation of the paper’s methods matches the description in the paper.

    In more detail:
    “Realizations of the random variable are generated using the Cholesky decomposition of the correlation matrix built from site-specific mean daily wind speed data. This approach maintains any geographical correlations due to proximity or weather phenomena that are present in the wind dataset. Diurnal character is imposed by a function, αi(t), which gives the monthly-averaged ratio of the wind speed in the hour of the day corresponding to the tth time step to the mean daily wind speed. Hourly wind speeds, vi(t), are generated from the mean daily wind speed realizations and αi(t), as well as a term that considers the deviation from αi(t − 1) in the prior time step to preserve temporal correlations, and a random variable term”

    • Using the Cholesky decomposition of the spatial correlation matrix is done simply to ensure that the spatial correlation of the generated data match the real world correlation matrix over whatever limited time span of data it was generated: however, it uses random numbers to create the generated data for the daily model data with no temporal correlation. Note that the spatial correlation matrix is based on simultaneous spatial data, and thus does not capture the effect of weather systems moving from one place to the next – a temporal correlation effect.

      Intra day data is derived by some curve fitting that is a bit like fitting splines, but allows some variation around the curve, while giving some appearance of continuity. It simply implies that if the previous day had a high wind total, then it will be assumed to be windier than average at 1 a.m. on the current day, with the wind dying down over the day to match the random number for the current day. Much depends on the assumed windiness at midnight on an average day: if this is low, then the discontinuity between a windy random number and a low wind random number will appear much less, and the diurnal pattern dominates the generated data at the intra day level.

      The random walk of the daily data will not emulate real world behaviour: seasonal variations, and periods of lull or protracted storms, or seasons or years with well below or above average levels of windiness are not properly modelled by these methods. It is precisely these anomalies that give rise to real difficulties in modelling high renewables scenarios, and to grossly inadequate estimates of storage or backup requirements.

      There is no adequate substitute for collecting long runs (many years) of real data, and scaling them for the assumed installed capacity to begin to give a flavour of how these systems perform in practice.

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