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How much photovoltaics to provide 100 kilowatt hours per person per day?

November 8, 2015

Suppose you wanted to power the world at the level that each human being can enjoy the same level of energy abundance as the average American. And suppose we wanted to do it all with photovoltaic solar energy. What would it take?

There are an average of 250 kilowatt hours consumed per person per day in the United states. Maybe that seems like a lot to you because you occasionally look at your home electric bill and see less than 1000 kilowatt hours used in a entire month for a home that houses four people. That 1000 kilowatt hours for four people in a month works out to only about eight kilowatt hours per person per day. But that electric bill is a very poor indicator of how much energy is actually expended for your benefit. That is why claims that some energy source will power X number of homes is incredibly misleading.

Here is the reality.  According to Lawrence Livermore National Laboratory the United States consumes 98.3 quads of energy every year.


That works out to about 250 kilowatt hours per person per day

(98.3 quads/year) x (2.933 x 1011 kw-hr/quad) / (year / 365 days) / (3.2 x 106 people) = 247 kilowatt hours/person/day

Fortunately, this daunting amount of energy is also somewhat misleading.  Look at the right side of the graph from Lawrence Livermore.  Notice that the two final energy outputs on the right side of the graph are “Energy Services” and “Rejected Energy.”  “Energy Services” is energy that actually does some useful work.  “Rejected Energy” is energy that is lost, mostly in form of waste heat.  For example, if you burn a lump of coal in a steam generator and get a kilowatt of energy out in the form of electricity, but lose two kilowatts in the form of heat to the atmosphere, then you got one kilowatt hour of Energy Service but two kilowatt hours of Rejected Energy.  As you can see from the graph, only 40% of the energy that is input comes out the the system as Energy Services (38.9 quads / 98.3 quads).

One of the big advantages of solar photovoltaics is that you don’t lose 60% of your energy to heat.  Electric cars put far more of their stored electric energy into useful work (Energy Services) and far less into “Rejected Energy” than do blazing hot internal combustion engines.

Let’s make the assumption for now that every possible efficiency is applied, so that we only need to produce 40% of the 250 kilowatt hours per day per person, or 100 kilowatt hours per day per person.  Still a lot of energy, but more manageable than 250 kilowatt hours.

So, for 7 billion people we need 700 billion kilowatt hours per day (100 kilowatt hours per person x 7 billion people).  If we got all that energy from solar photovoltiacs, how much land would be required for solar arrays, how much would it cost?

Topaz Solar Farm

To get estimates of these values, we can look at some of the world’s biggest solar arrays.  Consider the Topaz Solar Farm in California.  It is one of the biggest and one of the newest in the world and in an area of very high solar insolation.  It is expected to generate 1,100 GWh of energy per year while occupying 25 km2 with a cost of $2.5 billion.  Therefore it would generate the energy consumed by about 30,000 people at 100 kWh per person per day.

(1100 GWh/year)x(1×106 kWh/GWh)x(year/365 days)/(100 kWh/person/day) = 30,136 people

From this it is clear that it would take about 6 million km2 of solar photovoltaics of the Topaz Solar Farm density to generate all the energy consumed by 7 billion adequately powered people.

(7×109 people) / (30,136 people/25 km2) = 5.8×106 km2

Keeping in mind that the Topaz Solar Farm cost $2.5 billion and yields enough energy for 30,136 people, then the cost for 7 billion people would be about $580 trillion.

(7×109 people) / (30,136 people/$2.5×109) = $5.8×1014 .

For the sake of comparison the, the gross domestic product of the United States is about $17 trillion, or less that 3% of that $580 trillion.  The gross product of the entire world  is about $78 trillion, or about 13% of that $580 trillion.  So, if every penny or mark or yen, etc. of world product for about 7.5 years were dedicated to this project, it could be accomplished.

Some points to consider

What would be the consequences of covering 6 million square kilometers of land with PV?  This would be like completely covering an area the combined size of Arizona, Nevada, Colorado, Wyoming, Oregon, Idaho, Utah, Kansas, Minnesota, Nebraska, South Dakota, North Dakota, Missouri, Oklahoma, Washington, Georgia, Michigan, Iowa, Illinois, Wisconsin, Florida, Arkansas, Alabama, North Carolina, New York, Mississippi, Pennsylvania, Louisiana, Tennessee, Ohio, Virginia, Kentucky, Indiana, Maine, South Carolina, West Virginia, Maryland, Vermont, New Hampshire, Massachusetts, New Jersey, Hawaii, Connecticut, Puerto Rico, Delaware, Rhode Island with solar panels.  Of course, this would be spread out over the about 100 million square kilometers of land at latitudes lower than about 50 degrees.

This plan would also require a distribution system that could move energy from daytime areas to nighttime areas, or at least a few days of storage for every person on the planet.  Such a distribution system is not feasible at this time, and the massive amount of storage is prohibitively expensive.

Two days of storage would be 200 kilowatt hours of stored energy per person.  Probably the best mass storage option today (2015) is with Tesla’s Powerwall, which stores 7 kilowatt hours, costs $3,000, and weights 220 pounds.  So we would need about $90,000 and about 6,600 pounds of storage for each of the 7 billion people.  That adds another $630 trillion to the cost.

These calculations serve simply to give a feel for what could be done with solar photovoltaics and what the limitations might be.  I am not suggesting that the world should be powered solely with PV.  With other energy sources in the mix less money and land would need to be devoted to PV (but more to those other sources).  For example, if you did the same calculations for wind, then you would find that about twice as much area  (about 12 million square kilometers) would have to be covered by wind farms to get the same amount of energy.  But at least you can grow corn are graze cattle below the turbines in a wind farm.

I have led you to water.  It is up to you to drink up your own conclusions about the viability of using solar energy to bring the world up to a reasonable level of energy consumption.


Kirk Sorensen – The Promise of Thorium in Meeting Future World Energy Demand

September 28, 2015

If you really care about future energy abundance, then you should watch this video from Kirk Sorensen.   I believe that Thorium offers the world truly fantastic possibilities…


Uh, Oh! Karl, et. al., is bad news for Stefan Rahmstorf’s sea level rise rate.

September 25, 2015

Conclusion first

When the 20th century GISS temperature is modified according to Tom Karl,, it causes the 21st century sea level predictions of Vermeer’s and Rahmstorf’s semi-empirical model to go down!


I have written extensively about “Global sea level linked to global temperature,” by Vermeer and Rahmstorf (which I will refer to as VR2009).

VR2009 was a widely cited claim of using historical 20th century sea level and temperature data to calculate parameters that could be used to build a model to predict 21st century sea level rise for various 21st century temperature scenarios.  I reproduced the VR2009 model based on their description.  My code was verified by reproducing the VR2009 results using the same inputs that they used.

I spent a lot of time pointing out some of the bizarre results of their model that surely disqualified it form being taken seriously, some of which can be seen here, here, and here.

I also spent a lot of time pointing out that the VR2009 choices of 20th century sea level data sources left much to be desired.  For example, they used the 2006 Church and White sea level data that was already outdated.  If they had used the revised Church and White data, then their resulting sea level rise predictions for the 21st century would have been much lower.

They happily modified Church’s and White’s outdated sea level data by subtracting a reservoir correction (Chao, et. al.), which made their 21st century predictions for sea level rise go up. But they made no attempt to estimate a groundwater depletion correction. It turns out, unsurprisingly, that the groundwater depletion is of the same magnitude as the reservoir correction (Wada, et. al.), and including it would have made their 21st century predictions go down.

Nevertheless, Rahmstorf would later claim that his modeling approach was “robust!”  That is, it would give essentially the same result for the 21st century given different sources of 20th century sea level data.

So, I also implemented the VR2009 technique using several different sources of sea level data, which should have given similar results, according to Rahmstorf’s claim of robustness.  In fact, they gave widely varying results, and every combination of sea level data, reservoir data, and groundwater depletion data that I tried gave lower results than VR2009’s chosen combination.

New Temperature Data!

The widely reported nearly two decade long pause in global warming was causing suicidal ideation among hard-core global warming alarmists.  Something had to be done to stop them from slitting their wrists with shards of glass from their shattered thermometers.

Just in the nick of time – revised temperature data!   Like all proper revisions of temperature data, this revision caused the reported temperature change of the 20th century to go up.

This was a result of a paper by Tom Karl, et. al. (Nature) based on very thin reasoning (see for example) that argued for such revision.  The folks at GISS (who provided VR2009’s temperature data) glommed onto Karl’s logic and subsequently revised their temperature data accordingly.  Other temperature data source like UAH and RSS did not.

Which means we must ask ourselves, what happens to 21st century sea level rise predictions based on the VR2009 model using the now modified GISS data?

VR2009 applied their model to six families of temperature scenarios for the 21st century form the IPCC’s 4th Assessment Report.  Let’s see what happens to each of those scenarios when we update the 20th century GISS temperature data.

The IPCC temperature scenarios that VR2009 used for prediction of 21st century sea level rise.

Case 1.

Sea level inputs are identical to what VR2009 used: Church’s and White’s sea level with the Chao reservoir correction.  The old GISS temperature data is replaced with the new GISS temperature data.  The table below shows that the new GISS data yields 21st century sea level rises that are about 17% less than when the old GISS data is used.

Old GISS vs New GISS

It is a shame that after Tom Karl went to all the trouble to increase the temperature rise of the 20th century it just makes VR2009’s model predict LOWER sea levels for the 21st century.  This must be a great disappointment to Vermeer and Rahmstorf, so you can be pretty sure they will never tell you this result. But I just did.

Case 2

As I pointed out previously, VR2009 chose to use outdated 2006 Church and White sea level data, instead of Church’s 2009 data.  They also neglected a groundwater depletion correction.  When these improvements are included the VR2009 model yields 21st century sea level rises that are only about 55% of VR2009.  When the new GISS temperature data is included in the mix this drops to about 45%.

New GISS CW2009 Chao Wada

Case 3.

Lest Vermeer or Rahmstorf argue that their large sea level rise rates are saved by another update of the Church and White data in 2011, I have include these results also.  The difference between 2009 and 2011 Church and White sea level data was small.  Here is how the 2011 Church and White sea level data version plays out in the VR2009 model. The resulting 21st century sea level rise predictions are only about 43% of the VR2009 predictions.

New GISS CW2011 Chao Wada

The trend continues.

It seems that no matter what combination of inputs that are used in the VR2009 model, the predicted sea level rise for the 21st century is always smaller than with VR2009’s choice of inputs.  I wonder what that implies?


Has anybody ever heard of Angela Landolt?

September 21, 2015

I received this comment from Angela Landolt on a recent post.  It looks fishy to me.  I blanked out the link to her survey.

I am a student at the Institute of Mass Communication and Media Research (IPMZ) University of Zurich. As part of my Master’s thesis, I am conducting a survey on how climate change bloggers’ perceive themselves and their role in the climate change debate.

If you blog about climate change, I would like to ask you to participate in my survey. Your contribution will help us to gain valuable insights into the field of climate change blogging.

Link to the survey:

The questionnaire will take about 7 minutes to fill out.
There are no right or wrong answers. I am interested in your personal opinion.
The study does not serve any commercial purpose. The data provided is solely for the purpose of scientific analysis and is evaluated anonymously.
The questionnaire can be filled out in English and German.
Please feel free to contact me if there are further questions or comments.

Angela Landolt B.A.


Angela, if you are interested in my thoughts on global warming, then feel free to read my blog.  I have taken a look at some examples of work of the “Institute of Mass Communication and Media Research” and it looks like silly psycho-babble to me.


Chinese Nuclear News

September 10, 2015

Chinese reactor to be built in UK

Selina SykesUK Daily Express (9/6/15)

David Cameron is adamant to get the project off the ground – which is at the core of the Government’s drive to replace Britain’s ageing fossil fuel plants with low-carbon alternatives.

The Chinese – who are currently have 26 nuclear power reactors in operation – are vital to Britain’s low-carbon initiative.

The Chinese design is expected to be capable of producing one gigawatt of electricity – enough to power 1m homes.

China to increase nuclear capacity to 58 GW by 2020

The Economic Times (9/9/15)

China aims to lift its operational nuclear power installed capacity to 58 million kilowatts by 2020, and those under construction will reach 30 million kilowatts.

The rapid economic growth of inland provinces means the area will need more power, and China should develop inland nuclear power projects to meet rising total and per capita energy consumption, according to a research report from Chinese Academy of Engineering.

Construction of the Xipu fast neutron reactor nuclear power demonstrative project in Fujian Province, east China, could start at the end of 2017.


Definition: Barber Event

May 9, 2015

A monumental climatic event is unfolding before our eyes this year.  The ramifications will affect entire human race, nay, the entire community of Gaia dwelling souls.

 David Barber, 21st Century Arctic Explorer, has been warning us for years, but too many of us have been blinded by our greed for oil and money.  The Arctic will go completely ice free this summer.  This will no doubt force polar bears into extinction and set off a globe spreading chain reaction of extinction and desolation.

This extraordinary occasion deserves its own geological name.  I propose we call it the “Barber Event.”

Here is what will happen to Arctic sea ice…

SSMI ice extent 150506 v3

Related Posts

Arctic sea ice gone by 2015? A challenge to David Barber.

2 to 1 odds for Prof. David Barber

10 to 1 odds for Prof. David Barber

Don’t Panic – The Arctic has survived warmer temperatures in the past

Arctic to be ice free within four months


Arctic to be ice free within four months

May 7, 2015

A milestone than many are dreading will arrive within the next four months.  The Arctic will be ice free, probably for the first time in the last 6000 or so years.  This event has been long predicted by the eminent Professor David Barber.  In 2008 the Winnipeg Free Press quoted Barber…

“We’ll always have ice in the winter time in the Arctic, but it will always be first-year ice,” Barber said on Friday.  “2015 is our estimate for summer free (of) ice.”

As Barber said, the Arctic will always have ice in the winter, but some winters may have more or less than others.  Data collected over time has allowed the calculation of the average ice extent for each day of the year.  Of course, that average is higher in the winter and lower in the summer.  The lowest average occurs in September after the long summer melt.  Deviations from this average are called the “anomaly.”

In September the average ice extent drops down to about 4.5 million square kilometers.  But in recent years the anomaly has been negative.  So, the ice extent in September has been less than 4.5 million square kilometers.

Barber made his prediction in 2008 after that the previous year’s anomaly had dropped to about 2.5 million square kilometers.  That is, after that year’s summer melt there was only about 2 million square kilometers of ice left.  The strange thing is, six out of seven years since Barber made his prediction the anomaly has been higher (i.e. there was a greater ice extent) after the summer melt than in 2007.  This might surprise you, because you would expect that anomaly to get lower and lower (more and more negative) as you approached the dreaded ice free summer.

One might think that this strange circumstance indicates that Barber was wrong about his prediction.  But that can’t be, because he is a SCIENTIST (SCIENTIST, Scientist, scientist, scientist).

So here is what we can expect the anomaly to do this year…

If Professor David Barber is right, then the Arctic ice extent anomaly will look something like this.

If Professor David Barber is right, then the 2015 Arctic ice extent anomaly will look something like this.

Barber could have made a lot of money (for his favorite charity) off of this prediction, because there was some blogging kook who gave him 10 to 1 odds that it wouldn’t happen.  But I am sure he felt it was much more important to remain the impartial SCIENTIST (SCIENTIST, Scientist, scientist, scientist). 


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