From Stanford University , along with actor/activist Mark Ruffalo, and “Gasland” movie fabricator Josh Fox. I’m amazed the university would allow themselves to get used by these clowns. The website they are pushing actually doesn’t offer any solutions, but asks you to “Join the Movement”
Stanford scientist to unveil 50-state plan to transform US to renewable energy
Stanford Professor Mark Jacobson and his colleagues recently developed detailed plans to transform the energy infrastructure of New York, California and Washington states from fossil fuels to 100 percent renewable resources by 2050. On Feb. 15, Jacobson presented a new roadmap to renewable energy for all 50 states at the annual meeting of the American Association for the Advancement of Science (AAAS) in Chicago.
The online interactive roadmap is tailored to maximize the resource potential of each state. Hovering a cursor over California, for example, reveals that the Golden State can meet virtually all of its power demands (transportation, electricity, heating, etc.) in 2050 by switching to a clean technology portfolio that is 55 percent solar, 35 percent wind (on- and offshore), 5 percent geothermal and 4 percent hydroelectric.
“The new roadmap is designed to provide each state a first step toward a renewable future,” said Jacobson, a professor of civil and environmental engineering at Stanford. “It provides all of the basic information, such as how many wind turbines and solar panels would be needed to power each state, how much land area would be required, what would be the cost and cost savings, how many jobs would be created, how much pollution-related mortality and global-warming emissions would be avoided.”
The 50-state roadmap will be launched this week on the website of The Solutions Project, a national outreach effort led by Jacobson, actor Mark Ruffalo (co-star of The Avengers), film director Josh Fox and others to raise public awareness about switching to clean energy produced entirely by wind, water and sunlight. Also on Feb. 15, Solutions Project member Leilani Munter, a professional racecar driver, will publicize the 50-state plan at a Daytona National Speedway racing event in Daytona, Fla., in which she will be participating.
“Global warming, air pollution and energy insecurity are three of the most significant problems facing the world today, said Jacobson, a senior fellow at the Stanford Woods Institute for the Environment and Precourt Institute for Energy. “Unfortunately, scientific results are often glossed over. The Solutions Project was born with the vision of combining science with business, policy, and public outreach through social media and cultural leaders – often artists and entertainers who can get the information out – to study and simultaneously address these global challenges.”
Jacobson delivered his AAAS talk on Saturday, Feb. 15, at 1:30 p.m. CT, at the Hyatt Regency Chicago, Columbus Hall CD, as part of a symposium entitled, “Is it possible to reduce 80% of greenhouse gas emissions from energy by 2050?”
Relevant URLs:
Jacobson Lab
https://www.stanford.edu/group/efmh/jacobson/
The Solutions Project
http://thesolutionsproject.org/
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Externalities can also be positive as well as negative. Isn’t it time we brought in the greening of the biosphere and increase agricultural output? [references] Coal powered stations are paying through the nose for their negative externalities. We need to look at the positive too.
Jimbo:
You make a good point in your post at February 18, 2014 at 8:53 am where you say
It really upsets ‘greens’ when the point is made.
As example I cite the reaction of an exceptionally obnoxious troll posting as drumphil who asserted that CO2 emissions should be accounted as being “a negative” when assigning costs to power generation systems. I replied by asking
For days the troll avoided an answer by floundering about making every imaginable excuse and waving various Red herrings. Any impartial onlooker could only conclude he was wrong and did not have a clue what he was talking about.
This outcome must have hurt the troll because this morning he jumped into another WUWT thread herewith the sole purpose of aiming personal abuse at me. My response was to again demand an answer to the question and the resulting discussion in the thread exposed his irrational behaviour for all to see. Importantly, Jimbo, it demonstrated both the truth and the importance of your point for all to see.
Richard
@Phil at 8:32 pm
I’ll give Jacobson this, he does show his work: http://www.rsc.org/suppdata/ee/b8/b809990c/b809990c.pdf
I was struck by the calculation for Turbine Power:
Wind turbine characteristics (High Low)
D1(S8): Mean annual wind speed (m/s) 8.500E+00 7.000E+00
D2 (S9): Turbine rated power (kW) 5.000E+03 5.000E+03
D3 (S9): Turbine rotor diameter (m) 1.260E+02 1.260E+02
D4=(0.087*D1-D2/D3^2)
(S10): Turbine capacity factor 4.246E-01 2.941E-01
D5: Hours per year (hrs) 8.760E+03 8.760E+03
D6=D2*D4*D5: Turbine energy output without losses (kWh/yr) 1.860E+07 1.288E+07
D7: Turbine effic. with transmission,conversion, array losses 9.000E-01 8.500E-01
D8=D6*D7: Turbine energy output with losses (kWh/yr) 1.674E+07 1.095E+07
D9=(4*D3)*(7*D3)/10^6:
(S10) Area for one turbine accounting for spacing (km2) 4.445E-01 4.445E-01
First, it is based upon a 5 MW name plate, whereas most installed today are 1.5-2 MW nameplate. at $2-4 Million each. 126 meter diameter. Estimated cost should be about $10 million each (onshore).
But the kicker is that the energy is based upon MEAN annual wind speed with a historically high capacity factor. Maybe it is a reasonable approximation for the integrated power curve. The D4 formula looks a little wonky. It’s dimensional result is kW/m2. Is it missing ()? Is it a typo?
If you take a 5 MW/turbine (nameplate), 25% Capacity factor, and 8760 h/yr, you can get 11 GWhr/yr/turbine. D8 (w/ losses) is estimating 17 to 11 GWhr/yr/turbine. A little high for my taste, but not obviously wrong.
But at $0.057/kwh, that 11 GWhr/yr/turbine generates $0.624 million/yr/turbine. So capital accounting payout, no discounting, sans maintenance, is 16 years.
He lists only an energy payback time of 0.14-0.36 years at D16.
Just proving that SNODFART UTIVERSINY is still in Pola Atlo.
@Stephen Fisher Rasey at 10:32 am:
Using last year’s German capacity factor of 16.57%, I came up with only 6,17 GWhr/yr/turbine for D8. And the 11 GWhr/yr/turbine was at 29.4% capacity factor, not 25%.
However, looking further at this, it starts to get weird. In column one, he states that the formula for capacity factor is 0.87 times D1, the mean annual wind speed (m/s), – D2, the turbine rated power, divided by D3 squared, the turbine rotor diameter (m). He references footnote S10. S10 in turn cites references 11 and 33 in the original paper.
Reference 11 is a 654 page book by G. M. Masters titled Renewable and Efficient Electric Power Systems. G.M. Masters is another Stanford University professor that is also a co-author with Jacobson of Reference 33, which is a Science magazine “Policy Forum” article titled: “Exploiting Wind versus Coal.”
In Reference 33, Masters and Jacobson explain their formula for capacity factor:
Ref. 7 reads: G.M. Masters, in preparation.
Catharine M. Lawton prepared a refutation of “Exploiting Wind versus Coal” here.
She states:
The rest is worth a read.
In Ms. Lawton’s refutation, there is a very interesting part where she speculates that:
I found Reference 11 here.
On page 391 of the pdf, Masters derives the formula theoretically as Equation 6.65, which is a linear fit of the roughly linear portion of an S-shaped curve, for a turbine operating in winds that follow Rayleigh statistics. The whole thing is a theoretical derivation. In short, the difference between Master’s and Jacobson’s capacity factor used in their calculations and the capacity factor I calculated from the German report for 2013 may be operational factors. It would seem that no turbine could exceed the capacity factor model used by Master and Jacobson. The fact that they seem to make no allowance for mechanical breakdowns, etc. would seem to indicate extreme “ivory tower” thinking, with little connection to reality.
The actual German capacity factor for 2013 implies that Jacobson would need, at best, between 2 and 3 times as many turbines as he thinks – a substantial difference.
Willis Eschenbach says:
February 17, 2014 at 11:51 am
You will excuse me I hope if I do not hold my breath ?
These are the same idiots that hand wave their way past the material requirements. Get ready to triple worldwide production of rare earths just to handle the US conversion. Just more of the rehashed garbage they published in the ironically named SciAm a few years ago.
DirkH says: @ur momisugly February 17, 2014 at 10:30 pm
No problem, I am glad you did.
Phil says: @ur momisugly February 17, 2014 at 10:31 pm
Here is the final technical report for the liquid hydrogen fueled Cryoplane…. The safety discussions center around the Hindenburg, which is not comparable. They think that the chances of a detonation are slim….
>>>>>>>>>>>>>>>>>>
They have never had the experience of trying to keep the hydrogen tank and plumbing to the gas chromatograph from leaking day in and day out for decades. No matter what state I was in or what company I worked for the darn system ALWAYS LEAKED. And those systems were not traveling and therefore vibrating. I have also had two tanks blow. Luckily while I wasn’t nearby. One company had their propane fill system blow. It was used to fill deodorant cans after CFCs were banned.
richardscourtney says: @ur momisugly February 18, 2014 at 9:27 am
….Externalities can also be positive as well as negative….
>>>>>>>>>>>>>>>>>
For what it is worth. The USA went from producing 100 bushels of corn on 2-1/2 acres in 1890 with commercial fertilizers to producing 100 bushels of corn on 1-1/8 acres in 1987. For 1945 it was 100 bushels of corn on 2 acres. Corn is a C4 plant.
US farmers were producing 100 bushels of wheat on 5 acres in 1890, and 100 bushels of wheat on 3 acres in 1987. For 1955 it was 100 bushels of wheat on 4 acres. Wheat is a C3 plant.
Of course not all the gain is from CO2. Improved seed, herbicides, insecticides and irrigation would have a major effect.
On the other hand ALL those gains can be attributed to fossil fuels from the fertilizers to the herbicides, insecticides and even the irrigation and seed breeding.
You do not have time for improving seed stock and hybridizing if you are in third world poverty conditions.
About 85% of plant species are C3 plants. They include the cereal grains such as wheat, rice, barley, oats. Also Peanuts, cotton, sugar beets, tobacco, spinach, soybeans and other beans, vegetables, fruit trees, nut trees, and most other trees. C3 plants have the most growth response to higher levels of CO2 and also require less water.
I have yet to see any down sides to CO 2 levels under 2000 ppm.
@Phil at 4:24 pm
Nice digging on that D4 formula references. I said it was wonky, but I agree with weird, too.
The dimensional analysis doesn’t make sense as written.
The Turbine capacity factor (D4) must be: (0.087V-P/D²) and dimensionless because P X 8750 is already kwh/yr. Yet P/D² is a weird kw/m² cross-sectional energy density.
Furthermore, the power is proposed to be linear with mean windspeed in a Rayleigh distribution. Yet with Turbine power typically a function of V^3 for a steady velocity. One expects an exponent on mean velocity greater than 1, at least until the Capacity factor asymptotically approaches 1. That upper limit of 1.0 is also missing from the formula. The function is a blunder. Historical operating conditions aren’t even half of what he proposes.
Stephen Rasey said at 9:56 pm:
That’s because it is a fit of a linear function to the more or less linear portion of a non-linear function. You need to look at the link to Master’s book on page 391 or so. The derivation doesn’t look crazy to me, but I would look at it like I would look at the thermal efficiency of a Carnot cycle engine, when one is actually running a gasoline engine. Actual real world figures don’t come anywhere close to the ideal.
@Phil 10:51 pm
A better approximation for the Turbine Capacity Factor as a function of mean wind speed (given a Rayleigh distribution of speeds) would be of the form:
TCF = Fmax* [(V-vco1)(V-vco2)^2] / V^3
Where V is the mean wind speed, valid for V .GE. vco2 .GE. vco1
vco1, vco2 are curve fitting parameters functionally equivalent to wind speed cut offs for a given turbine design, replacing the P and D parameters.
Fmax is the maximum TCF allowable because as wind speeds increase, the probability of a high speed cutoff increases. At high V, d(TCF)/dv must go negative, so there has to be a max V where the formula can be applied, too.
I will admit to a fondness for curve fitting employing non-integer exponents. Geometric Programming lends itself to some neat optimization solutions if you condense posynomial terms into power functions with non-integer exponents. It is a clever approach to problems, but the dimension analysis of that approach yields nonsense. You have to compare it to the original function you attempting to simplify.
@ur momisugly Stephen Rasey
I am sorry for not replying sooner, as I have had to attend to other matters. Let me begin by retracting my previous comments about using theoretical numbers to estimate the number of turbines needed, especially the one about “ivory towers.” I have expressed myself thoughtlessly and inappropriately and, in addition to retracting the comments, I want to apologize for them, as they did not convey what I intended.
My thoughts were on the appropriateness of using theoretical figures to calculate the number of turbines needed, as opposed to using published numbers from actual experience. Specifically, Jacobson used a theoretical turbine capacity factor to calculate the number of turbines needed that is very different from the capacity factor that I calculated from the 2013 German report, which I assume represents actual experience. There is nothing wrong mathematically in the derivation of the theoretical capacity factor in Master’s book, it seems to me. It is no more incorrect than calculating the theoretical efficiency of an engine using the Carnot cycle.
What is incorrect is using this idealized and never achievable in real life number to calculate the capacity needed to replace existing fossil fuel and nuclear power plants. It is, at least, an error in judgement. Using the Carnot cycle efficiencies to estimate the fuel mileage of a real vehicle using an internal combustion engine, would yield wildly unrealistic numbers. The same is true of using Master’s theoretical capacity factors (specifically, ~42% to ~29%: D4 under the columns titled “low case” and “high case”) instead of the number I calculated from the 2013 German report (~16%). The difference would result in a number of turbines closer to 10 million than the 3.8 million he estimates in Table 4 here.
Yet, when it comes to the efficiencies of gasoline powered cars, he uses numbers that seem to me to be a whole lot more realistic than idealistic: A7: 16% (low case) and 18% (high case.) Thus, it would appear that he is inconsistent in a way that would make renewables more attractive. The 16% to 18% would reflect an engine thermal efficiency of ~20% to ~23% with a transmission efficiency of 80% (jacobson_hydrogen_cars_long2).
@Phil at 2/20 2:05pm
It takes class to retract some heated words about “ivory towers”…. especially when I think they were justifiable given the difference between their theoretical TCF and the practical field TCF. TCF is a key component in their calculations. If they are 2X higher than what we see in practice, it deserves more review.
I was uncomfortable with the power they delivered from the slow speed part of their curve. This might be a theoretical power available, but the slow speeds are not sufficient to connect to the grid. Perhaps the Turbine Capacity Factor needs to incorporate a Grid Connection Factor which is also a function of mean wind velocity, size of wind farm, and transmission capacity.
Maybe this GCF time their theoretical TCF is how we get to the practical field capacity factors.
@ur momisugly Stephen Rasey
You are too kind. Thanks. In one description, these big wind turbines were described as having as much going on in pumps, motors, heaters, instrumentation, etc. as a tug boat. That would mean that there is a base energy draw when you flick the “on” switch that should be fairly constant, whether the prop is turning or not. Yaw control motor current might vary with wind, but current for heaters for lubricating fluids would vary with the seasons. Computers should be fairly constant. Lubricating pumps should be fairly constant. Then there are mechanical failures. The most common, apparently, are electrical, but they are fairly easy to fix, supposedly. The biggie is transmission failure. That can be a months-long show stopper.
Their TCF varies, theoretically, with blade diameter. Although, one of my links criticized that, I don’t think Master is wrong. One thought, but I don’t have enough metadata, would be to try and correct the actual 2013 German figures for blade diameter to try and estimate a real world TCF for the bigger turbines being proposed, but that too would be somewhat theoretical. He may have a point about bigger turbines being a better investment, but that would depend on solving the engineering problems. They might have to start putting in elevators. 😉
In my experience, when things start getting this complex, it is too much to hope for to expect that it can run on automation alone. You may need a crew present on the wind farm, but that then adds labor cost. It becomes a never ending game of “now thats” Now that you have these huge machines, you need mechanics on site. Now that you have mechanics on site, you need a building. Etc. Etc. I just don’t think Jacobson understands the scalability issues.
@Phil at 10:54 pm
My problem is less with mechanical losses as it is with the slow-wind-speed phase and load matching to the grid. There is also the problem that at high wind speeds, you might not be able to transmit all the power. On reflection, while I think these are important factors missing from his equation, I don’t think they account for a 50% difference between theoretical and practical.
Another point we have glossed over…. The TCF function Master derives is from curve fitting of 0.1 MW to 1.5 MW turbines. But in The Solutions Project, they are using 5 MW turbines. So it is a leap in extrapolation.
Returning to P/D^2 as a “derived” intercept in the linearized curve fitting I view this a nothing more than convenient accident. The P/D^2 term doesn’t have a scaling constant. Heck, PI() isn’t involved.
Lastly, remember that the only payback Jacobson calculated was an energy payback. A monetary payback was ignored. All I did was use a rough industry rule of thumb of $2 million per nameplate MW. How close is that at 5 MW size? Lengthening turbine blades will quickly run into diminishing returns because costs rise as D^(1.2 to 2) and TCF rises as D^(-2) for the same power output.
@Stephen Fisher Rasey
Sorry, I have been busy elsewhere. You point about extrapolation is very good. I missed that. Also, your point about making the turbines bigger leading to diminishing returns is also very insightful.
See also:
Claim: Offshore Wind Turbines for ‘Taming Hurricanes’ (Univ. of Delaware)
WUWT Feb. 27, 2014
Jacobson is mentioned in the PR release, but does not appear to be a co-author.
I agree! It is possible, this transformation to 100% green energy….because there will be vitually nobody left in the states that go that way!