Friday, September 21, 2018

Extended EROI


Some EROI authors have suggested that renewable sources of energy have much lower EROI ratios than generally believed. The reason is that published EROI figures do not include all of the energy investments which were incurred. There are many small energy investments which are difficult to count, for example, the energy investments for smelting aluminum used to build metal fences around a power plant. Those tiny energy investments are omitted from EROI analysis. As a result, the EROI ratio is overstated for renewable sources of energy.

There are many small energy investments for any source of electricity, which are too numerous and too minor to count. For example, the EROI of solar power (commonly quoted as 10) does not include the energy investments to replace truck tires which wear out during the delivery of solar panels to solar farms. Nor does it include the energy investment of the steel-making equipment used to manufacture the steel for parts for that truck. And there are thousands of other little uncounted energy investments, such as energy investments for fences around the power plant, roads to the plant, security cameras, replacement of transportation equipment, electricity used in the plant office, and so on. Any one of those energy investments might be quite small, but taken together, they can add up to a lot, because there are so many of them. When those little energy investments are added up, the EROI of renewable electricity will be reduced considerably.

Of course, the same holds true for all sources of energy. The EROI of coal-fired electricity, for example, does not include the energy investments of building roads to the coal power plant, building a railway to the coal power plant, replacing locomotives which have worn out delivering coal to the power plant, and so on. Those energy investments could be considerable and could greatly reduce the EROI of coal-fired electricity.

As a result, EROI is overstated for all sources of electricity. The only way to get an accurate EROI value is to include all the small uncounted energy investments, or at least try to estimate them.

Dr Charles Hall has referred to this as "extending the boundaries" of EROI analysis. Prior EROI analyses have not included indirect energy investments such as degradation of transportation equipment. It was considered outside the scope of the EROI analysis. As we extend the boundaries of EROI analysis, we include more and more energy investments that occurred further up the supply chain.

The purpose of this article is to extend the EROI boundaries all the way, and to include all energy investments for each source of energy, no matter how minor or indirect. This will be done for coal fired electricity, nuclear power, solar PV, and wind power. The result is a convergence of EROI values for different sources of electricity, as will be shown.

Method of estimating extended EROI

The great difficulty with extending EROI boundaries is that it becomes more and more difficult to gather the information needed, the further you extend the boundaries. The uncounted energy investments become more numerous and smaller. As an example, a coal-fired power plant requires a railroad connection. That railroad connection requires railroad ties, which are made out of wood, which were taken from a tree, which was chopped down using a chainsaw, which has a plastic gasoline tank, and the plastic was made out of oil, which was extracted by an oil well, and the oil well was made out of steel, taken from a blast furnace. How do we account for the energy investment for the degradation of the blast furnace, which is fully seven degrees removed from the top of the supply chain?

At some point, the energy investments are so far removed, and there are so many of them, and they are so little, that it becomes difficult to add them all up. It would be nearly impossible to track down all this information.

Hall and Prieto attempted to extend the EROI boundaries for a solar PV plant[1]. They accomplished this by adding up all the monetary costs for things like roads to the power plant, security cameras, fences, and so on. Prieto was a manager at a solar power plant, so he had access to the relevant accounting information and added up the prices for everything. Hall and Prieto then converted those prices to energy by means of a formula (6 megajoules per dollar, if I recall).

It was a good idea to estimate uncounted energy investments by looking at prices. That was a significant contribution of Hall's and Prieto's book.

However, it is not necessary to add up the prices of all these little things like roads to the plant, security cameras, and so on. All of those things are already included in the final levelized price of wholesale solar electricity. For that matter, all monetary expenditures, along the entire supply chain, no matter how minor or indirect, are already included in the final levelized price of solar electricity.

The price of something includes all the monetary costs, along the entire supply chain, to obtain that thing. Each supplier in the supply chain keeps track of all its monetary costs, and passes along all those expenses to the supplier above it in the chain. All companies keep careful track of money and pass along all of their expenses. There is an army of accountants, spread throughout the economy, who do this. They pass along all monetary costs, no matter how indirect. As a result, the final price of a thing, is a kind of summary of all prices paid to obtain it, throughout the entire supply chain.

Because of this, we can estimate the uncounted energy investments for a source of energy by just looking at the price of it. The price of electricity from solar PV, for example, includes the price of everything needed to obtain it.

Thus, we can estimate the extended EROI of a source of electricity using the following algorithm:

  1. Obtain the levelized cost of electricity for a source (from Lazard[2], for example).
  2. Subtract the top-level interest expense, which is not an energy investment.
  3. Also subtract the money which was spent on obtaining energy for the counted energy investments. This can be done using published EROI figures. Those energy investments have already been counted, and we don't want to double-count them.
  4. What is left is the amount of money spent on everything else. We'll call this "miscellaneous expenses". It includes things like profits, salaries, taxes, interest paid on transportation equipment like trucks, and everything else, for every contractor and sub-contractor and supplier, up the entire supply chain. It also includes all money spent on obtaining energy, throughout the entire supply chain.
  5. We must estimate how much of this "miscellaneous" money was spent on energy, and how much was spent  on everything else, using a factor. We'll refer to that factor as the "uncounted energy investment factor".
  6. We must multiply the uncounted energy investment factor by the amount of money spent on miscellaneous expenses.
  7. We then add that "uncounted" energy investment to the energy investment from published EROI figures. After which, we can calculate an "extended EROI" by just performing the division again using the energy investment with extended boundaries.

Let's try extending the boundaries for a typical solar PV plant.  We'll assume that the levelized cost of wholesale electricity for solar PV is $0.05/kwh (as per Lazard), that 50% of that money is spent on interest (which is common for projects which involve almost the entire cost upfront and which last decades), and that the EROI of solar PV is 10. In which case, the amount of money for miscellaneous expenses for solar PV is $0.02/kwh (interest was $0.025, and counted energy investments were $0.05, and subtracting both of those leaves $0.02 remaining for miscellaneous expenses). Let's assume, as an initial estimate, that 10% of the miscellaneous expenses are payments for energy. We'll also assume that the price of the energy for investment is $0.01/megajoule.  With a conversion factor of 0.10, $0.002 of the wholesale price was spent on uncounted energy investments. At $0.01/megajoule, that translates into 0.2 megajoules, or 0.0556 kilowatt hours. Thus, the counted energy investments for solar PV were 0.1 kwhinvest/kwhdelivered (or 1/eroi), and the uncounted were 0.0556 kwhinvest/kwhdelivered, leading to a total extended energy investment of 0.1556 kwhinvest/kwhdelivered, or an extended EROI of 6.43 for solar PV.

If we perform the same procedure for various sources of energy, we obtain the following extended EROI ratios:

SourceExtended EROINotes
Coal5.29(assumes EROI of 20 after waste heat loss, $0.10/kwh, 40% interest)
Nuclear6.22(assumes EROI of 30, $0.10/kwh, and 50% interest)
Wind9.00(assumes EROI of 20, $0.04/kwh, and 40% interest)

Of course, the above figures are dependent upon an uncounted investment factor of 0.10. In other words, we assumed that 10% of miscellaneous expenses are devoted to buying energy products. However, the choice of 0.10 was little more than a guesstimate.

At this point, we could estimate an accurate uncounted factor by looking at the economy as a whole. We could examine a first-world economy which gets most of its electricity from coal-fired plants and try to estimate how much of its energy expenditure is devoted to the energy industry itself, then subtract the the energy investments which had already been counted.

I suspect that the factor of 0.10 was too high. If coal-fired plants, for example, consume 18.9% of the energy they produce, then this would have been obvious in Sankey diagrams of the US economy back in the 1970s and 1980s. As a result, let's use a different factor of 5%. In which case, the extended EROI ratios for different sources of electricity are:

SourceExtended EROI

We can use different estimates for the uncounted energy investment factor. With smaller factors, the EROI ratios of all sources of energy increase, and the ratios for coal and nuclear power increase by more.

Interpretation of Results

Right away, it is obvious that the extended EROI ratios for different sources of electricity are fairly close together. This is totally unsurprising. The monetary prices of those sources of electricity are also somewhat close together. Any conversion of money into energy would cause the EROI ratios for different sources of energy, of the same price, to converge.

Furthermore, the high-EROI sources of electricity (such as coal-fired electricity and nuclear power) are also moderately more expensive. This implies that the "uncounted" energy investments are higher for those sources of electricity than for renewables, using any consistent conversion of money into energy. As a result, extending EROI boundaries will reduce the EROI ratios for high-EROI sources of energy (such as coal and nuclear) the most. In turn, that will cause the EROI ratios of different sources of energy to converge even more strongly.

The result is no large difference between the extended EROI ratios of different sources of electricity.

Of course, we may have chosen an uncounted factor which was still far too high, even after revising it downwards. In which case, extending EROI boundaries would make little difference for solar PV, and published figures are already fairly accurate. Using very small factors will result in less than a 10% adjustment of published figures for solar PV.

It is just not possible that solar PV has a drastically low extended EROI ratio while other sources of electricity have much higher extended EROI ratios. Solar PV is much cheaper than alternatives, so any attempt to extend boundaries will cause a strong convergence of EROI values. This implies one of two things. If extending boundaries makes little difference, then the EROI of solar PV was fairly accurate beforehand and is above 9. If extending boundaries makes a large difference, then the EROI ratios of other sources of electricity will be reduced by more, and all sources of electricity will have similarly low extended EROI ratios. There is no possible factor for uncounted energy investment which would yield a very low extended EROI for solar power and very high extended EROI ratios for other sources of electricity. The higher the factor, the more the extended EROI is reduced for coal and nuclear power compared to solar PV. Making assumptions of extremely high uncounted energy investments will result in lower extended EROI ratios for coal and nuclear power than for solar PV.

One other conclusion from the above figures is that coal-fired electricity has much higher "uncounted" energy investments than other sources of electricity. This is also totally unsurprising. It has frequently been pointed out that solar PV plants require fences and security cameras, which incur energy investments that had not been counted. That much is clearly true. However, coal-fired plants require a railroad connection with a mile-long train full of coal arriving every few days, for the entire lifetime of the plant. That imposes massive "uncounted" energy investments, including fuel usage by locomotives, degradation and replacement of locomotives and rail cars, wear on the national rail network, and so on. Those energy investments are massive and ongoing, and would obviously outweigh the trivial energy investments of installing cameras or fences once. Those much higher "uncounted" energy investments for coal-fired electricity are reflected in its higher price.

One final point bears mentioning. The extended EROI ratio of solar PV (indicated above) is considerably higher than that estimated by Hall and Prieto. Their analysis was useful, but it's years old. The field of solar PV moves quickly. Hall's and Prieto's estimate has fallen out of date.

Hall and Prieto estimated the extended EROI of a 1-megawatt solar plant. However, newer solar plants are much larger, frequently larger than 100 megawatts. There is an economy of scale when it comes to uncounted energy costs. Solar plants which are 100x larger do not require 100x as long of a road leading to the plant, or 100x as many employees, or 100x as long of a fence surrounding the plant, and so on (in fact, a solar plant which is 100x larger would require only 10x as long of a fence surrounding the plant, if we assume that all solar plants are laid out in a square shape, which implies a 90% reduction in energy investment for fences, per kilowatt-hour). As a result, Hall's and Prieto's analysis is out of date, and the actual extended EROI of solar PV would be significantly higher now, as indicated in the table above.

Summary and Conclusion

Extending EROI boundaries as far as possible, while also assuming high uncounted energy investments, causes the EROI values for different sources of electricity to converge strongly. The result is no large difference between EROI values for different sources of electricity. If we assume that uncounted energy investments are extremely low, then published figures for the EROI of solar PV are already fairly accurate.


[1] Spain's Photovoltaic Revolution, Charles Hall and Pedro Prieto, Springer, 2013

[2] Lazard Levelized Cost of Energy, version 11.0.

This article was originally published with a minor arithmetic error which was corrected several hours after the initial publication.

Wednesday, September 5, 2018

The Effect of Declining EROI on Industralized Countries

In the previous article, it was shown that any country can increase its energy supply exponentially with any EROI higher than 1. For example, with an EROI of 10, any investment of energy more than 1/10th of energy supply (or 1/eroi) will lead to exponential growth of energy obtained over time.

It was also shown in the previous article that a low EROI imposes a delay for civilization when accelerating exponential growth of energy obtained. For example, it was shown (using a simulation) that a low EROI of 10 imposed a delay of 6 years before a hypothetical civilization could accelerate growth from 0%/year to 4%/year.

However, some modern industrialized countries do not accelerate growth at all. In fact, they do not even grow their energy supply. Those countries are already fully industrialized. Once a country reaches a first-world standard of living, it voluntarily stops growing its energy supply. Citizens decide to spend any increase in their income on things like elaborate medical care, and not on setting their thermostats higher every year. This situation has already been reached in Japan and many places in Europe. It would have been reached in the USA, except the USA still has significant immigration.

What would happen to such a static country (in terms of energy supply) if it underwent a decline in EROI? Presumably, such a country wouldn't care about how fast it could grow its energy supply. It would care only about keeping the amount of net energy constant.

In such a country, any decline in EROI could be handled by initiating growth again, at a rate which is sufficient to compensate for the decline in EROI. Doing so would keep net energy constant.

As a result, we must ask how much net energy must be sacrificed by an industrialized country in the short term, in order to initiate growth and offset declines in EROI. Any acceleration of exponential growth requires a temporary sacrifice of net energy, in order to initiate the growth. How much net energy must an industralized country sacrifice to initiate growth again, sufficient to compensate for a decline in EROI?

This phenomenon can be modelled using a simple python computer program--even simpler than the last one, because this program has only 24 lines of code, excluding comments. (This phenomenon cannot be modelled using a simple mathematical formula, because generations of solar panels overlap, which resists a simple mathematical description).

In this paper, a simple python program will be proposed which simulates energy re-investment for an industrialized country over time. The program will execute in a single loop and will simulate energy re-investment, over and over again, each year. As before, we will assume a country which obtains all its energy from solar panels.

The program will simulate a decline in EROI. We can assume that the decline in EROI is caused by mineral exhaustion over time. The country used to build fancy Gallium-Arsenide solar cells with 40% efficiency and very high EROI, but the Gallium is running out. As a result, the civilization must start building silicon solar cells instead, which use far more abundant materials but have much lower EROI. Furthermore, the country has already filled its only tiny desert region with solar cells, and must now use worse locations, implying lower EROI for solar cells. As a result, the country undergoes a constant decline in EROI over years. This decline in EROI will be modelled in our program by increasing the energy investment required by some constant factor each year.

At the same time, the program will model the modest exponential growth which must be re-started in order to compensate for the decline. These two factors will operate simultaneously. Declining EROI will decrease net energy obtained, but exponential growth will increase it.

As pointed out in the previous article, any acceleration of exponential growth requires a temporary sacrifice of net energy for other purposes. How much of its net energy must an industrailzed country sacrifice, and for how long, in order to initiate exponential growth and compensate for declines in EROI?

When I implemented and ran the program, I obtained the following results. I tinkered with the input parameters, and I found that growing the total amount of energy obtained by 0.7%/year for a country is sufficient to compensate for a decline in EROI from 50 down to 6, over 37 years. In turn, the country had to sacrifice a small fraction of 1% of its net energy for 2 years in order to initiate that growth. The output of the program was as follows:

Original net: 0.98

As is shown above, the country needed to sacrifice a small fraction of 1% of its net energy for two years in order to initiate the growth necessary to outrun declines in EROI. After which, a decline in EROI from 50 down to 6, over 37 years, imposed no decline in net energy for our modelled industralized country.

(After the 5th year in the table above, I decided to print only every other year, in order to keep the table smaller. Not much changes from one year to the next at that point.)

(The label "epbt" refers to Energy Payback Time; net refers to net energy obtained; and"FracOrigNet" refers to the amount of net energy obtained relative to the original, for example, 1.0 implies no loss or gain of net energy compared to originally).

Of course, you can tinker with the input parameters and reduce the final EROI to below 6, or decrease the number of years the simulation runs, or increase the growth rate (and also the temporary sacrifice). I picked these particular parameters because they were the most pessimistic parameters I could imagine which were not just ludicrous. It is extremely unlikely that EROI will decline from 50 to 6 over 36 years. The EROI of 6 is far lower than almost any published EROI figures of any common sources of generating electricity. Furthermore, actual declines in EROI for our global industrial civilization have been FAR more gradual than simulated here. As a result, the parameters I picked were a kind of "drastic worst-case scenario" and should be interpreted as such.

Still, such a rapid decline in EROI imposed only negligible consequences for an industrialized country. The effect upon net energy obtained was to reduce it by a small fraction of 1% for two years.

Of course, this does not mean that consumers must actually reduce their energy consumption by a fraction of 1% for those two years. All industrialized countries in the world already have overbuilt their electricity grids. Industrialized countries have enough electricity generation to provide for the highest anticipated electricity demand in an entire year. Most of the time, they have excess generation capacity which is shut down or curtailed. As a result, the sub-1% sacrifice would only be imposed during the few hours per year when demand is highest and the electricity grid is fully committed. The actual sacrifice would probably mean shutting down some aluminum smelter plants for a few additional hours per year, for two years, and running a few gas turbines for longer the rest of the time for those two years.

From the above, we can conclude that it's easily within the capability of any industrialized country to compensate for any plausible decline in EROI, with no significant loss of net energy.

The source code for the python program is as follows:

# This is free and unencumbered software released into the public domain.
lifetime = 25
total = 1.0
initialEpbt = 0.5
epbtIncreaseFactor = 0.20
growthFactor = 0.007
yearsRun = 40
panelsYearly = []
initialNet = 1.0 - (initialEpbt / lifetime)

# Populate pre-existing panels
for year in range( 0, lifetime ):
  panelsYearly.append( total/lifetime )

# Run simulation
print ("Original net:", initialNet)
for year in range(0, yearsRun):
  epbt = initialEpbt * (1 + year * epbtIncreaseFactor)
  sumPanels = sum(panelsYearly)
  retiredYearly = panelsYearly.pop(0)
  yearlyToBeAdded = (sumPanels * growthFactor + retiredYearly)
  investment = (retiredYearly * epbt) + (sumPanels * growthFactor * epbt)
  net = sumPanels - investment
  print ("year:%i total:%f retired:%f epbt:%f net:%f frac_orig_net:%f eroi:%f"
% (year, sumPanels, retiredYearly, epbt, net, net/initialNet, lifetime/epbt)

Monday, September 3, 2018

EROI and economic growth


A great deal of literature has been devoted to calculating the EROI of various energy sources. However, little explanation has been offered for why we should care, or what effect a lower EROI would have on civilization. Why even bother tracking EROI?

Some authors have speculated that declining EROI would imply less net energy for other purposes in the economy. For example, a decline in EROI from 100 down to 10 might imply a 90% loss of net energy for civilization. However, that conclusion was incorrect. EROI does not determine the amount of net energy obtained by civilization as a whole. This is because our global industrial civilization has been increasing the amount of energy (and therefore the amount of energy for investment) exponentially over time, and this effect has greatly outpaced any decline in EROI. For example, increasing the amount of energy (and energy investment) by a factor of 1.33 would compensate for a decline in EROI from 1 billion down to 4, with no loss of net energy. (An increase in the amount of total energy by 1.33x would allow 1/4th (or 0.33 / 1.33) of total energy to be devoted to obtaining the energy, yielding a net energy factor of 1.0 (or 1.33-0.33), or no change). Since the amount of energy for investment can increase exponentially, increasing it by a factor of 1.33 is obviously within the capability of industrial civilization, thereby more than compensating for any plausible decline in EROI. As an example, it has been pointed out repeatedly that the EROI of oil has declined from 100 in 1930 to less than 10 now, but there hasn’t been a decline in vehicle traffic by 90% worldwide since 1930. Quite the opposite, vehicle travel has increased tremendously since that time, because the amount of oil has increased by a such a large factor that net energy from oil increased, despite massive declines in EROI.

Other possible effects of lower EROI would include greater land usage for solar farms, or higher costs of energy. However, those effects would be minor, as a matter of arithmetic, as long as EROI remains above some very low threshold. For example, a low EROI of 10 would imply that a solar farm would need to have ~11% greater land area, compared to a solar farm with an EROI of 1000, in order to obtain the same amount of net energy ( (1-1/1000) / (1-1/10) ~= 1.11)  . Prices for solar panels would also be higher by a similar amount (11%), all other things being equal. However, the price of solar panels has dropped rapidly in recent years and is far below the price of electricity from coal-fired plants. The lower EROI of solar panels would have little effect on price compared to recent declines in price for other reasons.

One effect of lower EROI, which has not been investigated, is the effect on growth. A lower EROI implies a larger upfront investment of energy. A larger upfront investment of energy requires a greater sacrifice of net energy now in order to obtain a desired level of exponential growth. It will take time before exponential growth compensates for the original sacrifice of net energy to initiate that growth. As a result, a lower EROI implies a temporary sacrifice when initiating or accelerating growth.

A simple mathematical example may demonstrate this point. Assume a civilization which gets all its energy from solar panels with an EROI of 10 and a lifetime of 10 years. Also assume that generations of solar panels do not overlap; new panels are kept in a dark warehouse until old ones expire, at which point, all the old panels are replaced at once with new ones. In which case, our hypothetical civilization must invest 10% of its gross energy (or 1/eroi) on building new panels just to replace those that expire, leaving 90% of all gross energy for all other purposes. If that civilization decided to embark upon exponential growth, and double the amount of energy it obtains in each generation of solar panels, then it must double the investment energy from 10% to 20%, leading to a reduction of energy for all other purposes from 90% to 80%. This reduction would persist for one generation of panels (10 years) until exponential growth overcame it. Thus, our hypothetical civilization must undergo a temporary reduction of net energy by ~10% for 10 years, in order to accelerate exponential growth from 0%/year to ~7%/year. This reduction by 10% of net energy is determined by EROI. If the civilization had solar panels with an EROI of 100, then only a 1% reduction in net energy would be required to accelerate growth by the same amount.

Of course, reality is more complicated, for several reasons. First, generations of solar panels do actually overlap -- new panels are installed before all the old ones have expired. As a result, we cannot represent the compound growth with a simple exponential formula. Second, any real civilization obviously would not accelerate its growth from 0%/year to 7%/year overnight, because the sudden loss of net energy would be disruptive. Instead, any actual civilization would obviously ramp up growth more slowly, over a period of a few years, at least.

In this paper, a simple computer model is used to calculate the effect of EROI on growth of energy obtained. A simple python program is presented which repeatedly calculates re-investment of energy over time, and which ramps up growth slowly enough that net energy never falls below some threshold level.

The result is that even low EROI values (such as the EROI of 10 for solar panels) have only a modest effect on growth, as will be shown below.

The Model

The model is implemented as a simple python program which calculates energy re-investment over time. It executes in a single loop which calculates energy obtained and energy re-investment, over and over again, for each year. It takes input parameters such as EROI, target growth rate, and a minimum threshold for net energy. The minimum threshold parameter determines how low net energy can go (relative to the original value) before growth must be curtailed, in order to ramp up growth more slowly. When growth is curtailed (during the ramp-up period), all excess energy beyond the minimum threshold is re-invested for exponential growth.

When this program is run with an EROI of 10.0, a target growth rate of 4%/year, and a minimum threshold of 97%, we obtain the following results. The civilization requires six years of ramping up growth in order to reach the desired growth rate of 4%/year. During the ramp-up period, 3% of net energy is sacrificed in order to accelerate growth. During the ramp up period, all exponential growth is re-invested, according to the assumptions above. The output of the program is as follows:

Initial net:0.900000 minimumNetAmount:0.873000

As we can see, net energy must decline from 0.9 to 0.873, for six years, in order to initiate growth. After which, the civilization has enough surplus gross energy to grow at 4%/year with no further sacrifice.

The source code for the model is as follows:

# This is free and unencumbered software released into the public domain.

eroi = 10.0
lifetime = 25
targetGrowth = 1.04
minimumNetFactor = 0.97
total = 1.0
yearsRun = 30
#panelsYearly keeps track of the panels installed each year; one element
# per year. Each element refers to the amount of energy those panels
# will return EACH YEAR.
panelsYearly = []
oldSumPanels = 0.0
rampUpPeriod = True

# Populate pre-existing panels
for year in range(0,lifetime):

# Run simulation
originalNet = total - total/eroi
minimumNetAmount = sum(panelsYearly) * minimumNetFactor * originalNet
print("Initial net:%f minimumNetAmount:%f" % (originalNet, minimumNetAmount))
for year in range(0, yearsRun):
  sumPanels = sum(panelsYearly)
  retiredYearly = panelsYearly.pop(0)
  if (rampUpPeriod == True and oldSumPanels > 0
and sumPanels > oldSumPanels * targetGrowth):
    rampUpPeriod = False
    print("Stop ramping up")

  if (rampUpPeriod):
    investment = sumPanels - minimumNetAmount
    yearlyToBeAdded = (investment * eroi) / lifetime
    yearlyToBeAdded = sumPanels * targetGrowth - sumPanels + retiredYearly
    investment = (yearlyToBeAdded * lifetime) / eroi
  print ("year:%i total:%f retired:%f toBeAdded:%f net:%f" %
  (year, sumPanels, retiredYearly, yearlyToBeAdded, sumPanels-investment
  oldSumPanels = sumPanels


A decline in EROI worldwide down to 10 would impose a delay of 6 years when accelerating growth from 0% to 4% for the world economy as a whole.

Of course, the model above is simplified in some ways. The algorithm used to determine how to ramp up growth would almost certainly be more sophisticated in reality. In which case, the above model is sub-optimal. Results in reality would be slightly better.

Repeatedly throughout this paper, an EROI of 10 was assumed because that is the EROI of crystalline silicon photovoltaics, which has the lowest EROI of any common source of generating electricity. Still, such a low EROI imposed only a modest delay when accelerating growth. As a result, any plausible decline in EROI in the future would have only modest effects on growth.