Long Range Projections of Alternative Energy Futures
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30:25
Computeranimation
Transkript: Englisch(automatisch erzeugt)
00:16
It is a great honor to be invited to address this gathering.
00:23
And also, it is a very fine development that different professions which together are needed in collaboration in order to face up to the many problems
00:41
that modern technology and modern society has presented us with. So I am glad for two reasons, the second being to be allowed to participate in interdisciplinary activity.
01:05
I am worried that our universities are not designed and organized to make it easy to find these collaborations. But outside universities, there are other such opportunities.
01:22
And in particular, the Tagungen in Lindau have that character. Now, my topic then is long-range projections of alternative energy futures, which is one particular study in the field of energy modeling
01:45
itself, a development of the last 10 to 12 years. I forgot to ask the chairman to let me know when I'm five minutes before the end of my talk. So please tell me when I have only five minutes left.
02:03
The development of energy modeling took place in the United States, in Europe, Mexico, India, and other countries. The aim of that technique is to visualize alternative energy futures.
02:23
The nature of the problem makes one need to draw on various fields of knowledge and actually some speculation. Technological knowledge to draw on physics, chemistry,
02:41
biology, engineering, behavioral to draw on economics in regard to the behavior of consumers and of producers faced with the market, and the resource availability problems in which we need to turn to geologists and mining
03:03
engineerings. There is, in this type of work, a speculative element. And that is inevitable in models that look far ahead into the future. For that reason, the conclusions reached have the following logical form.
03:23
If such and such, then so and so. And the ifs must be emphasized. If you find that someone reports on a model study and those were my conclusions and that person only
03:41
gives the thens and not the ifs, then that is unsatisfactory. Now, I would like then to use one recent modeling study in which I was involved that illustrates the type
04:03
of work along these lines. There was in the United States a very substantial and widely ramifying study of energy futures and energy presence called by the Committee on Nuclear and Alternative Energy
04:27
Systems, a committee set up by a combination of the National Academy of Sciences and the National Academy of Engineering. There was an overview committee that was responsible for the ultimate publication,
04:44
a very substantial book that has come out of that work. There were also panels to provide analytical work into the mill, so to say, of the deliberation of the overview committee. And I was chairman of a panel called Modeling Resource Group.
05:05
The word resource in that sentence is human resources, resources of expertise. The assignment of that group was to compare the answers
05:23
given to the same set of questions by three different models that were already available before the work was started. My emphasis in this report is on the methods and on the kinds of questions that can be answered.
05:45
And therefore, the ifs that we did use, and we had several alternative ifs side by side, should be revised as time goes on. And any results, if I may use that word, of this particular study would have to be revised
06:06
as the ifs are revised. Now, can we dim the top light a bit enough now for the year? I have to switch this on.
06:20
This diagram is, in a way, a layout of the study. We did consider three groups of variables. The driving variables, the realization variables,
06:42
excuse me, the word realization was used for something that is not subject to policy decisions. It is there already. Or it is caused by circumstances and decisions that the energy-related policies do not
07:04
have an effect on or a sizable effect on. Now, we had there the GNP growth rate as one, you may also say, exogenous variable.
07:21
And that was estimated on the basis of population extension, labor force participation, and such factors at 3.2 per annum from the beginning year of the study, which was 1975, up to 2010.
07:41
Then another realization value was cost levels of energy technologies. At that point, we did not have the subsequent experience. And so we had the following figures in terms of dollars of 1975. The figures are for capital cost of electricity generation.
08:05
For coal fire generation, we had $520 of 1975 per kilowatt electric. Light water reactor, the number goes up to 650. Advanced converter reactor, 715.
08:23
Fast breeder reactor, 810. Again, dollars of 1975 per kilowatt electric. And solar central station, 1,730 in the same unit. Now, these numbers have all gone up since then.
08:40
So I report on the study as made at that time without trying to bring up to date any numbers. We also had resource stock availability numbers on there for oil and gas. It was in the United States a quantity of 1,720 quads,
09:07
where one quad is 10 to the 15th BTU. And this was oil and gas at the cost of extraction up to $2 of 1975 per million BTU.
09:22
For uranium, it was 3.7 10 to the 6th tons of U3O8 at a cost of extraction not exceeding $30 in that same unit. Now, then it says there on the right,
09:43
demand elasticity with regard to price and with regard to income. It turned out, toward the end of the study, that was an extremely important parameter. And I will come back later to its precise definition.
10:04
It is a measure of the response of demand to a given increase of price and a given increase of income. I have a slide later that will indicate both the numbers used and the definitions of the concepts.
10:23
In any case, the three important models that we used differed in their price elasticities. And that was, in fact, helpful, because it indicated the importance of that parameter.
10:40
Now, the models that were used, we had three plus four, seven, no, six models, actually, in the study. But the only ones long enough looking into the future were DISOM, ITA, and Nordhaus, TAD. And I will refer to those in more detail later on.
11:08
Then we had policy variables. First of all, base case, which was going on pretty much with the developments as they are presently called for.
11:22
And that is called the base case. And then we had other cases that are obtained from the base case by policies that were in there because they were much under discussion at the time.
11:41
The nuclear moratoria was not then considered as a policy. Since then, something in that direction has taken place, not really as a policy, but as a result of mishaps and fears. So it is desirable to have this in the study,
12:08
regardless of whether or how such a containment might come about. It was defined nuclear moratorium in the case of applied to all nuclear reactors was one case.
12:25
Another case was to apply it not to the light water reactors already in service for quite some time. And it was so these two cases were distinguished.
12:44
Also, limits on the use of coal and oil shale coal because of the acid rain and oil shale as a result of water use and water deterioration as a result of use.
13:01
And in both cases, or in the case of all fossil fuels, there is also a long-range concern with the CO2 content of the atmosphere. So that's the reason why that is in there also. And these limits were defined, we
13:24
curves that would level off to an asymptote in case of coal and other curves in the case of shale oil. And the limits would be that at no point would the annual rate of production of coal or shale
13:42
oil exceed that curve. Now then, finally, we had a third category of variables that we called blend variables, which are called blend variables because they
14:01
combine the properties of realization variables and of policies. The discount rates, as we have found to our dismay in the United States, are also subject to policy.
14:20
But they are also, in the absence of specific determined policy, still are a reflection of the behavior of parties in the capital market of the economy.
14:40
And so that is a blend variable. But we ended up using 13% for pre-tax, decant rates applied to investment and pricing decisions of the energy producing business, forms, industry.
15:01
And 6% post-tax applied to the consumer's relative weight to future benefit, given to future benefits as compared with present benefits. For that, we had a 6% discount rate. Then there was a ceiling on quantity and price
15:22
of imports of fuels that I will not dwell on, and an estimate of the commercial availability, if wanted, of advanced converter reactors, fast breeder reactors, or solar electricity generation, all
15:43
assumed to be available at and from the year 2000, if that were to be aimed for. Then the ideas on the economic side were that optimization can be looked
16:09
at as a simulation of the behavior of competitive market systems. I like to put it this way. There is in the world neither perfect competition nor perfect planning.
16:21
But if there were, then they would be equivalent. The perfect planning would be guided by prices similar to those produced by perfect competition or producible by perfect competition as well, so that we have had this fictitious image
16:44
of efficiency in the use of resources. And it doesn't matter how it is obtained, assuming it can be obtained. It was meant to be actually an approximation of how our not quite perfect system of markets operates.
17:08
So you could say we used Adam Smith's invisible hand, but with foresight. Now then, the price and income elasticities of demand for energy.
17:22
I'm now ready to say some more about that. Here are the numbers that we in fact used. And now I also want to define the price elasticity that was the most important of the two.
17:41
Let x be the demand and p the price, the demand for energy and the price of energy in terms of some aggregates over the various forms of energy, just one number. Then the elasticity is defined as the derivative of the log of quantity demanded
18:03
with respect to the log of price in the market. And that is, as you see from the use of logs, a dimensionless quantity. Now, if policies that constrain energy supply are applied
18:29
strongly, then a high price increase is needed to constrain demand accordingly. And if the absolute, yes, I should have said the each,
18:47
normally, each price elasticity of demand is a negative number because as price goes up, quantity demanded goes down. Now, I go back to my sentence.
19:01
A high price increase is then needed to constrain demand accordingly. And if in absolute value, the elasticity is low, then less remains to spend on other goods. If the absolute value of the elasticity
19:21
is high, then only a smaller price increase results. And the amounts spent on other goods are less affected and the total of GMP, of gross national product, is less affected. This sort of simple, straightforward reasoning
19:43
indicates that eta, the price elasticity of demand, that negative number, is a very critical parameter. And I'd like to mention also, I will first
20:01
describe the elasticities that have been used in the study. Here, DSOM was a model developed at Brookhaven Laboratory and for reasons that were connected with the purpose of that model. It did not have consumers' response dependent on price.
20:25
It just projected the curve of consumers' demand as a function of time into the future up to 2000. And for that reason, the price elasticity of demand
20:40
was really very small. The only sensitivity or response to price was still in the choice of the particular energy, technology, conversion, transport, or what a certain sensitivity to price came out before the energy reached the consumer.
21:02
Then the other two models were quite similar in structure. The energy technology assessment model of Allen Mann at Stanford University distinguished electric and non-electric demands.
21:24
And it came to an estimate of minus 0.25, so an absolute value of the elasticity of one fourth. The Nordhaus model had more subdivisions. One, residential and commercial users, two, industrial, three,
21:44
transportation for specific electric services that could only be done by electric power. And he came at an eta of minus 0.4. There was a study done subsequently
22:02
by the Energy Modeling Forum, an organization based on Stanford University but operating nationwide with a nationwide following and participants, of the elasticity values that had been produced by various studies, by econometric methods,
22:24
statistical methods, as against judgmental estimates. Now the modeling forum had found a range of minus 0.4 to minus 0.7 of those estimates obtained
22:45
by statistical and econometric methods. The minus 0.25 in the Mann model was labeled as a judgmental estimate.
23:05
But at the request of other members in the group, Allen Mann, who was himself a member of the committee of the modeling resource group, and so was Nordhaus, and so were two people from Brookhaven, Kenneth Hoffman
23:24
and William Marcuse, the group, the estimate that since the estimate was, although we didn't use that term at that time, had some judgmental aspects to it,
23:43
we asked Mann and he willingly did add a second minus 0.50. I have five minutes. Thank you. Then I will go and jump now to the results that came out
24:04
of the here. We have to look carefully at the definitions of what is on the axis.
24:21
I think I first must list the policies here. The policies were those that I had already enumerated, namely the base case and then the moratorium
24:43
only on advanced converter and breeder reactors, then the moratorium on all reactors, and then the coal and shale limits. Those were the first assumptions. And then certain combinations, the moratorium
25:02
on both the moratoria and the coal and shale limits. And of those, the following diagrams indicate what was found.
25:21
And let's now read carefully what is on these axes. Here we have e, the ratio of aggregate energy consumption in 2010 projected for policy i. That is the one of that list of five that refers.
25:45
And that ratio is set off here. So the more drastic the policy, the further the point corresponding to it will be down on this axis. The other is the ratio of cumulative discounted
26:02
GNP for 1975 to 2010 projected again for the same policy. And then which model? That is indicated by the particular symbol that is there to indicate the dot.
26:20
And here are the three DSM responses to policy. And that's the only one until we get there where there is a direct response to some constraining measures with regard
26:40
to consumption used. Therefore, we note then that all the other points somehow hug the vertical line. And that indicates that where the elasticities that
27:04
are no longer there on the screen are moderately high from minus 0.4 on, the points remain. And the effect on GNP of the constraints
27:22
on energy use are not severe. However, in this point here, this is the eta point at minus 0.25 price elasticity,
27:40
a constraint in quantity that has an effect this much. Then also the GNP is constrained. So here we see it very clearly before us from these measurements that it depends on the price elasticity of demand
28:00
in the model that is perceived, that is produced by the model. Now let me then just miscalculated my time somewhat. But let me just then indicate my summary of what
28:22
was learned from this study. First of all, the smallness of the effect on GNP, as long as you don't get below, let's say, minus 0.5 or minus 0.4 in the price elasticity,
28:45
and it is a matter of econometric work to improve the assurance that we can have in reading these estimates. But I do read, maybe a little ahead of myself,
29:00
that the principal conclusion that I draw is that there is some time left to overcome the problems of widespread concern with the safety of nuclear reactors, including the Frieder reactors. And this is important because if we mostly
29:22
rely on fossil fuels, we have to deal also with their side effects, the acid rain or the CO2 in the atmosphere, the acid rain mostly from coal, but the CO2 problem as much from oil and gas
29:43
if those are to be the mainstay. So I read out of this study. First of all, it's a first study of its kind, therefore provisional, and not to be dogmatic about. But second, also it indicates that there is enough time
30:02
to try out alternative methods of energy generation or rather the mix thereof we are not under the sort of demo class. Thank you.
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