The World Energy Modeling Project
Posted by Nate Hagens on August 7, 2007 - 12:00am
Topic: Miscellaneous
Tags: complex systems, energy modeling, limits to growth, net energy analysis, systems analysis [list all tags]
The following is a guest post about the need for global energy systems modeling, by ASPO-USA co-founder Dick Lawrence. Mr. Lawrence has a degree in Physics from Rensselaer Polytechnic Institute. After a career at Digital Equipment and Intel he is focusing on the world energy model and starting a solar hot-water business in Massachusetts. In 1986 he read "Beyond Oil" (the original) which was his introduction to resource depletion, Hubbert's peak, and the power of computers to model the behavior of complex systems. In May 2004 he proposed a project to model global energy flow at the ASPO meeting in Berlin.
In the 1980s, Robert Kaufmann co-authored, with 3 others, a study of energy flow through the U.S. economy in Beyond Oil (last updated in 1992). That study was the inspiration for a proposal to model energy flow at the global level, first shown to ASPO members and attendees at the 2004 Berlin conference. After several years of presentations and proposal refinement, a project to model world energy flow is now underway. Modeling teams will develop the North America model (United States, Mexico, and Canada) over the summer of 2007, performing initial model runs in September. They will then expand the scope of the model to the global level, completing development by (approximately) mid-2008.
The World Energy Modeling Project
Energy is at the foundation of every aspect of our present globalized economy. Without adequate energy, the well-being of our still-growing world population, increasingly urbanized and industrialized, faces the prospect of reduced standards of living, declining access to food and clean water supplies, and contraction of global trade and GDP.
In the next decade and beyond, decisions will be made at national-policy (and, possibly, global) levels that have consequences to large segments of the Earth’s human population and to the world environment. These decisions will directly and indirectly impact energy and resource availability, human well-being, and the sustainability of the environment on which all economies ultimately depend.
Understanding the complex relationships between energy, the economy, human living standards, and national policy decisions is a difficult task. Well-informed observers often arrive at opposite conclusions, even when in possession of the same collection of facts. How can we cut through the morass of conflicting opinions and develop a better understanding of the consequences of policy decisions?
Increasingly, researchers turn to computer-based dynamic-systems modeling techniques when they are trying to understand complicated systems. 35 years ago, colleagues of Jay Forrester at MIT published the results of a study 35 years ago called Limits to Growth, which attempted to look at the global human population and its relationships to resources, food supply, pollution, and more.
In the 1980s, Robert Kaufmann co-authored, with 3 others, a study of energy flow through the U.S. economy in Beyond Oil (last updated in 1992). That study was the inspiration for our proposal to model energy flow at the global level, first shown to ASPO members and attendees at the 2004 Berlin conference.
After several years of presentations and proposal refinement, a project to model world energy flow is now underway. Following our presentation at ASPO-USA’s Boston conference in October 2006, we developed a Request for Proposals and distributed this to organizations and academic groups considered to have the resources and skill sets to implement such a model. After reviewing the proposals, ASPO-USA decided to merge the capabilities of two responders into a combined project team. ASPO-USA brought the two groups together in mid-May of 2007 and officially launched the project.
The two teams are:
• Millennium Institute – main model development, building on the foundation of their T21-USA model, which has substantial energy components;
• State University of New York – Environmental Science and Forestry (SUNY-ESF) – creation of the “energy core” of the model, including EROI database and feedback paths. ESF will also develop new graphical user interfaces.
The teams will develop the North America model (United States, Mexico, and Canada) over the summer of 2007, performing initial model runs in September. They will then expand the scope of the model to the global level, completing development by (approximately) mid-2008.
TARGETED RESULTS
We want the model to be capable of answering the following questions:
• Given the finite and future limited availability of fossil fuels, with growing supply-demand mismatch, what is the best use to which we can put remaining supplies of “cheap” oil and gas?
• How much of our present and near-term fossil-fuel supply should be diverted to developing sustainable / renewable energy resources in a way that minimizes negative impacts on food production, water supply, per-capita energy availability, and quality of life for residents in developed, developing and under-developed nations? What would be the consequences of delaying accelerated or “crash” programs by a decade? Two decades? (see “the Hirsch Report”)
• What are the net-energy consequences for a variety of likely mixes of energy sources (i.e. a specified mix of conventional fossil fuels, biofuels, nuclear, and renewable, for example)?
• How much can biofuels (ethanol, biodiesel) be reasonably expected to contribute to energy supply without negatively impacting food supply or prices?
• To what extent do limits on water availability restrict energy development from unconventional sources (both fossil-fuel based and renewable)?
• What is the CO2 emissions impact for likely future energy scenarios? (CO2 emissions will be tracked for all scenario runs).
• What is the energy cost and “carbon footprint” of CO2 sequestration proposals? Are they realistic?
• Is a “hydrogen economy” feasible? What are the net-energy and environmental implications of different approaches to hydrogen production? What would be the consequences of a “crash program” basing most transportation uses on hydrogen and fuel cells? How would that compare with an all-electric transportation scenario?
• Can we substitute energy products based on tar sands, shale oil and coal (CTL) for conventional liquid fuels? If so, how long would these resources actually last at different growth rates?
• What is the interaction of energy supply, demand, and price – how will energy price respond to supply-demand mismatch for world supplies of oil and natural gas? What’s the elasticity of demand as energy prices go into new (higher) territory?
• As wealth flows into energy-exporting nations from energy importers, standards of living and demand for products and energy rises in the exporting countries. What are the consequences for availability of energy supply, and energy costs, for importing nations?
These are, of course, preliminary questions. Over time, new questions will be put to the model. A comprehensive and well-tested model will be able to answer new questions as they arise with only minimal modifications, if any.
The model incorporates complex relationships between energy, the economy, agriculture, industry, transportation, and the environment, including tracking CO2 emissions for all scenarios. Like the groundbreaking Limits to Growth more than three decades earlier, its results are not predictions of future events, but provide insight into the consequences of economic and energy policy decisions. The model is a policy-making tool that permits investigators to better understand the impacts of regulation, financial investment and incentives, and energy policy, and to analyze the consequences of developing various future mixes of energy source.
In addition, varying estimates of fossil fuel supply may constitute different scenarios – for example, using ASPO’s estimate of recoverable oil and gas, vs. those of USGS/EIA, are two scenarios we can run to explore the consequences of those supply estimates – are fossil resources in “Scenario X” sufficient to enable investment in renewable sources while simultaneously supplying the exploding energy needs of a growing global consumer society? Or does competition between investment in future energy supply and “everything else” force difficult decisions about how to ration energy and economic capital?
During a scenario run, decisions are made which influence the outcome. The results will be collected and analyzed to understand which decisions yield preferred outcomes. We intend to disseminate the results of model runs to a broad audience of academics, energy researchers, the public, companies in the energy industry, and (most importantly) to policy-makers at all levels of government.
Recent studies, like “The Hirsch Report” commissioned by U.S. DOE, and released in early 2005, warn of potentially serious consequences if we fail to respond in time to the threat of depletion of fossil fuel supplies. A model of world energy flow will permit a more detailed investigation of these scenarios and what energy policy decisions, and timing of implementation, will best reduce the impact of depletion.
Climate change is obviously a critical topic now getting enormous media and political attention. While it will not attempt to model the complex relationships between anthropogenic CO2 emissions, climate, and the human economy, the model will monitor CO2 emissions for all scenarios. The consequences of those emissions – temperature changes, regional and global weather changes, agricultural impacts – may be factored into some scenarios. In those cases the necessary data will be imported from results of dedicated climate-change models. Those impacts will then, via various feedback paths, affect other portions of the model – for example, modifying agricultural output as a consequence of changing long-term weather and rainfall patterns.
The model will account for and track flows of energy and materials based on physical laws (i.e. energy and matter cannot be created from nothing). It will access a database of EROI (energy return on energy invested) for all forms of energy – conventional, renewable, and unconventional. The model will show what is possible, given known constraints on energy availability, material resources, and financial capital.
We will develop the world energy model as an “open source” project – anyone with Internet access will be able to run the model and view the results of scenario runs.
One goal of the project is to develop a simple game-like user interface that makes the model accessible to those without experience in modeling complex systems. Others with more expertise will be able to go into the model, understand how it works (“transparency” is another goal), and develop their own scenarios. Model users from around the world will be able to communicate with each other using a web site dedicated to model discussion, modification, and operation.
There will be a presentation of the results of preliminary scenario runs at ASPO-USA conference, Houston, in October.
Public announcement of the predecessor to T21-North America was on Monday, July 16th at New America Foundation in Washington DC. TOD readers can view the presentations including my discussion of the motives for modeling world energy flow here and clicking on the embedded YouTube link.
References
The Limits to Growth –Donnela Meadows, Dennis Meadows et al – Universe Books 1972
Beyond the Limits – Donnela Meadows, Dennis Meadows, Jørgen Randers – Chelsea Green Publishing Co. 1992 – ISBN 0-930031-55-5
Beyond Oil – Gever, Kaufmann, Skole, Vorosmarty - Carrying Capacity, Inc. 1986
ISBN 0-88730-075-8(PB)
Peaking of World Oil Production: Impacts, Mitigation, & Risk Management – Robert Hirsch, Roger Bezdek, Robert Wendling – February 2005; available online at:
http://www.netl.doe.gov/publications/others/pdf/Oil_Peaking_NETL.pdf
This is spectacular! One more great reason to be in Houston October 17-20th at the Hilton Americas!
Bob Ebersole
Interesting, but there appear to be many unanswered questions. For instance you say the model will include decisions during the run that affect outcomes, but not where these will come from. It also appears as if this doesn't include any of the political and economic aspects that significantly affect energy usage and outcome.
As a for instance, the price of oil affects real world usage in a highly non linear way, but the price has to rise to a level to effect demand destruction sufficient to bring supply and demand into equilibrium at all times. Therefore sensible modelling of energy and energy choices is determined intimately by game theory, historic expectations, market uncertainty, general economic situations, etc.
In short, the question involves many interrelated complex adaptive systems, and game playing, but I can't see signs that all the required elements are there to make the such a model reflect reality. Such a model may say that 'tar sands' are the answer, without recognising that scaling timelines are insufficient for the expected complex decline rate slope - and the political fallout.
You might be able to tell I've considered this whole modelling area, and I'm not convinced you can get where you want to get from here with that approach. I'd love to hear your thoughts.
Gary
Im going to keep the post near the top for a few days so that the members of the Modeling Project can respond to questions.
For my part, I agree that modeling energy requires to some extent modeling human nature, which is of course difficult. How will geopolitical events impact/trump geology? How will the coming credit swoon impact oil and gas investments? How will efficiency and or conservation impact energy usage, etc?
However, at current trajectory, we rely on the market to answer important questions like these - this modeling effort, and others like it are an important step in the right direction of viewing the market as part of a large system, with energy being a central variable.
I'd agree going global is the right direction to take, it's the only time you really reach a truly closed system. I'd also agree that starting from a resources and a physical limits constraint is right (we're not likely to change these).
However I'd contend that as we hit peak/demand<>supply crossover the system enters a new phase and becomes highly complex, non-linear, and possibly out of control entirely. Taking nice proportional behaviours as a basis seems troubling.
The oil cost example is an interesting one. We know that price will rise to push out demand. However we also know that the impact of price rises on demand is connected to what the price history is, what else money is being spent on, which countries have the least leeway. Throw in some exportland, some 'non renegotiable' wars and some planned economic warfare and its difficult to know of oil will be $70 or $700 in only one year's time. I can make an argument for either. That in itself casts all other relationships in the model into question (can't scale solar PV if the economy collapses).
I'd be happier to see such a model married up to a 'wargame' with some really sneaky players (which is something I've been thinking about). That might delineate the parameters of the gamespace.
You mean combining it with a Department of Defense wargame simulation, like this?
Well, that's nice marketing spin for an agent based sim, but I was thinking more of sneaky humans working out the tricks of the new game scenario - akin to this:
http://www.guardian.co.uk/g2/story/0,3604,786992,00.html
We all know that one of the expected behaviours of a post peak world is for producers to artificially constrict supply even further, to push up prices and maintain reserves even longer. What other behaviours are likely? Are alternatives strangled at birth to keep the lights on today? What's credible with realistic decision types?
After all, the Easter islanders could have turned the last trees into boats and escaped, rather than burn them for firewood and to create statutes.
I have also given thought to an agent based modeling approach to understand the behavioral response (or lack thereof) to peak oil.
Think for a minute about the major players (agents) in such a model--and what drives them. There are oil companies, who seek to maximize shareholder value. Higher prices generate short-term profits, but long-term value depends on the value of their reserves.
Then there are oil producing (net exporting) countries, who depend on oil revenues to maintain their economies. Their access to oil also gives them a bargaining chip in the world, but also makes them vulnerable to invasion by large, oil consuming countries (i.e. the next agent described).
Major oil consuming (net importing) countries have their own set of agendas. Their economies are / were built by cheap oil. Without cheap oil, their massive economies come to a screetching halt. Leaders in these countries may (or may not) understand the gravity of the energy situation, however, are personally motivated to stay in power. The need for votes may contrain what they are able or willing to do.
Then there are investors, who seek to maximize short and long term financial returns. However, their decisions are only as good as the information they are provided. In the case of oil, much of this information is provided by estimates and forecasts by major oil companies, oil exporters and oil consuming nations.
For each of the described agents (and there are more), several key question stand out. 1. Are each of these agents aware of the peak oil threat? 2. If so, what is their likely response based on what motivates them? 3. How do the combined responses work together to explain our current situation? 4. What are the likely scenarios going forward?
Simple rules, but complex outcomes to be sure!
Debbie
Edit - I left out one of the most important agents--John or Jane Q Public.
GaryP and others,
I will borrow a line from Meadows & Meadows in "Limits to Growth" since it's eminently applicable here: the results of these modeling efforts are NOT PREDICTIONS, but rather project the consequences of a specific combination of starting conditions and certain events that take place, or decisions that are made, in the course of a scenario run.
Clearly we can't, and will not attempt to, anticipate international political events and social movements. We can't model what George Bush or Vladamir Putin are thinking, and all that moves nations to make war or peace. Furthermore we can't predict breakthroughs in the development or price of enzymes for cellulosic ethanol, or anticipate a novel application of nanotech to boost solar PV efficiency or make its power price-competitive with hydroelectric or coal-based electrical power.
But, with real-world constraints and best-available EROI data built in, the model can tell us what is possible if we, as a nation or group of nations, decided on specific directions and policies and our progress is then bounded by those constraints. Do you want to pave the Mojave Desert with silicon solar cells? How much polysilicon will that take, how much silver for the contacts, and is there the physical and financial capital to accomplish that? If you propose to expand the output of tar sands to quadruple its present levels, what are the implications for water and natural gas in Canada? How much CO2 will be emitted? How fast can we really ramp up biofuels given the competition between fuel and food for hectares of farmland?
Variations in starting conditions are exemplified by (for example) comparing scenario runs using the ASPO estimates for oil and gas reserves and undiscovered, vs. EIA or CERA data.
Here's another way of looking at it: there's a lot of hype out there, and "world models" in the heads of John and Jane Q. Citizen, that convinces them that everything's going to be hunky-dory because John read about a new solar PV material that gets 42% efficiency in Popular Science. It's part and parcel of his world belief structure, which is non-numerical, vastly incomplete, and quite incapable of projecting the consequences (including all the "unintended" ones) of energy policy decisions. A world energy model should be able to do a better job in most respects, and should generate a collection of results that people can begin to agree on. It won't stop all the arguments, but it should at least focus them and help promote critical thinking.
The project must acknowledge that when we project substantial declines in flows of fossil fuels due to depletion, we're entering a supply / demand regime for which we have little history to compare with, and to develop relationships between energy supply, price, and elasticity of demand. Estimates of the linkage strengths between GDP and energy also become increasingly problematic as we move into uncharted energy-supply territory.
This is a big multi-year project. We will need additional funding to expand its scope to global (from North America), and we want to challenge the best minds in the business to look at what we're doing, and help us make it better. It won't answer every question, but I believe it will be a valuable tool for policy decisions and to educate ourselves about our energy choices.
We will launch a new site in the next week or two for comments and discussion dedicated to the energy model. I will work with Nate and others to make sure the links and other information are available to TheOilDrum readers.
Looking forward to all your comments!
- Dick Lawrence
ASPO-USA
That's not what "open source" means. Open source would mean that saavy users could get the source and hack it - add in whatever other parameters they wanted. Want to blow this wide open? Do that.
LTG3 kept talking about their model, sounding like it would be available somewhere. Maybe it is now, but it was not when I first got the book. Lost opportunity - not because I'd have done much with it - but someone much smarter than I would have.
GDP won't be helpful. You will have to develop a different benchmark. Maybe a "footprint" or a composite of resources, sinks and throughputs. GDP masks that - turning sinks into benefits (where prices go up) and ignoring resources (clean air and water). If you use GDP and dollars, you might find there is enough in all those hedge funds to pave the Sahara with solar cells. The EROEI of a hedge fund and derivative, global finance - that's going to be interesting.
cfm in Gray, ME
The World3 model is available on CD. I picked it up from Amazon.
Jon Freise
Analyze Not Fantasize -D. Meadows
I purchased the World3 model CD, but was rather disappointed. The main item is a program that lets you choose one of the 10 canned scenarios and run it. This lets you look at the scenarios in more detail (you can get various charts or all the raw numbers) and compare them.
But you can't alter the model at all. Given the complexity of the model, this is perhaps a reasonable choice. I doubt it is easy to alter just a few initial values and parameters in such a complex model in a way that makes sense, unless you understand the entire model and have had some training in this type of modeling.
You can look at the model, sort of. But all you get is a large picture of tons of circles and arrows, with indecipherable variable names like "del ind out pc 40". No legend for what the various pieces are, no explanation of what the boxes, circles, and arrows mean (beyond the variable names).
It does seem to be open source. If you have a spare $1899 you can get a copy of Stella, the simulation software the model runs on. (You can also get a free save-disabled trial version that expires in 30 days).
What would I like to see? More detailed explanations of: the model elements and how they fit together. Probably the LTG folks have papers in journals that go over all this stuff -- I admit I haven't searched for it yet.
I consider these modeling efforts to be critically important for high-level decision makers to "get it" that everything is interrelated and you can't just try to force one problem (energy for example) to go away and ignore the others.
But for these models to have the requisite credibility they MUST be open for scrutiny. I expect that experts in different fields will scrutinize how the model treats their field, and render an opinion on how realistic the model is in that sub-area (e.g. population, or agriculture, or energy).
And generalists (like many of us at TheOilDrum) who have some appreciation of modeling should be able to get into the details as well.
It sounds like Mr. Lawrence has these goals in mind:
I'm interested in the "more expertise" version. However, the game version could be important for spreading the word. Have you considered contacting Will Wright, the creator of The Sims videogame? He did a game called SimEarth in 1990.
Finally, here is a disclaimer paragraph from the LTG CDROM:
You can see their point. They don't want people altering their model and then claiming the results are "from the LTG World3 model". Openness has its consequences.
Don't try to predict the future. Get ready for it.
The Limits to Growth study was published with the intent of shaking the world and raise awareness about sustainability issues.
At the recent International System Dynamics conference (Boston Jul 29, Aug 3), Jay Forrester, Jorgen Sanders, and Dennis Meadows have repeated once again that their intent was to stimulate a discussion among different groups. They also admitted that they completely failed and could not reach their main goal (i.e. change policy making) because most of the people (mainly scientists and academia) kept undermining their study without trying to understand it.
Nowadays we can certainly do better, maybe without gaining much visibility, but assuring transparency and openness.
Simulation models usually are not open source because most of the people can easily misunderstand their results and simulate unrealistic scenarios that can undermine models' validity.
What we are doing with this model is to use full and extended variable names and provide tools (the user interface) that allow to review the main structure of the model at no cost.
A full documentation of the USA model is already available (about 500 pages) and will be updated in occasion of the release of the North America model.
In spite of all the effort we put in this project, I expect furious criticism from some reviewers of the model. Modelers speak different (modeling) languages, economists have their own concepts and theories, etc. Unless we use a common framework and we try to understand each other there will be no collaboration on interrelated but still diverse issues.
Best,
Andrea
Dear All,
My name is Andrea Bassi and I am one of the modelers working at this project. I will be constantly checking the discussion on this thread and will try to answer all questions. I may not be able to answer every single question or comment on every sentence, my apologies for that. Please fell free to write me an email if needed, though it would be good to keep the discussion on this forum to allow everyone to follow the discussion.
The tool chosen by ASPO-USA consist in an integrated model linking Society, Economy and Environment into one framework. The Millennium Institute has developed the T21 model over the past 24 years, in collaboration in the early phases with various professors and practitioners (e.g. MIT, Dartmouth College, Albany NY, etc.) More info at www.millennium-institute.org
T21 differs from optimization models in many ways, in fact it does not simply aim at optimizing the energy flow to minimize costs but is adds behavioral components (it looks both at the demand and supply side). The structure of the system analyzed is represented within a broad framework and causal relationship and feedback loops are the foundation of the methodology used. For this reason the model does not heavily rely on data and can capture transitions. A preliminary report on T21-USA is available at www.millennium-institute.org with an extensive explanation of the behavior of a few simulation runs.
The model is based on differential equations and it is characterized by nonlinearity, delays and a dynamic behavior created through the accumulation of flows into stocks (e.g. identified reserve -stock- oil recovery -flow- and cumulative production -stock-).
The structure of the model is built on causal relationships. Causality is the foundation of the model and correlation is one of its outputs.
Thanks to this approach, the model aims at representing reality by accounting for feedback loops (both reinforcing and balancing) observable in nature. Simulating new scenarios is also very easy and it takes about 10 seconds to simulate a 70 years period on a regular laptop (the USA model is available on MI’s website, no need to buy ay software to install it and run it). The model is transparent and we can always track changes and justify the behavior of the model.
Just to give you an idea of how the model works, population dynamics are generated by the accumulation of births, deaths, and migration into the stock of population (this stock is disaggregated into 82 age cohorts to calculate fertile women, labor force, social security and medicare beneficiaries, etc). Fertility (and births) is influenced by, among others, income, which together with emissions influences also mortality. Oil price, for instance, is influenced by the availability or oil reserves (both in the short term and in the longer term) in the US and the rest of the world (ROW), by demand/supply balance. Oil price has an impact on the economy, through total factor productivity, and on energy demand for electricity, oil and its substitutes.
T21 start simulating in 1980 and ends in 2050. The structure of the models aims at reproducing historical data until 2006 and then projecting future trends until 2050. Short-term oscillations are not the focus on this modeling exercise, we are looking at medium and longer term implications and project 5 to 10 years trends.
One of the goals of this project is to produce a policy tool able to inform policy making. For this reason a number of policy variables are included in the model and users can test their own assumptions and policies. The outcome of these changes will then be compared to the baseline scenario for the four main spheres of the model: Energy, Society, Economy and the Environment.
Since some of you mentioned games, we have been thinking of creating a game, SimCity-like, where users have to create their own future at the national and global level. The difference between the ASPO-USA model and a game, is basically the interface. SimCity and similar games are based on causality, the same foundation of the methodology used here. Users of T21-North America can simulate different assumptions and policies, we are working at a fully interactive interface (thanks to the ESF team for all the good work done so far!) and hopefully we will be able to work at a real videogame (most probably we will be working at a serious game).
Agent based is certainly an interesting methodology to do so, but it does not allow to understand where the behavior of the model comes from (please let me know if you would like to have a paper explaining the differences and similarities of system dynamics and agent based modeling). In fact, ABM builds on emergence, such an intriguing phenomena. On the other hand, our approach consist in transparency and full replicability, therefore we always want to know what facts generated a change with respect to the base scenario.
As Dick mentioned, we cannot forecast breakthrough in technology improvement of political crises. What we can do is to allow you to simulate such events in every given year of the simulation (2007 to 2050 –past events cannot be changes, but initial conditions such as total oil in place can be modified). Major improvements in oil recovery or energy efficiency (on top of what is simulated endogenously by the model) can be tested. In addition, in the T21-USA report you can find the simulation of the loss of 15% of world oil recoverable reserves (let’s say due a crisis in the Middle East). The consequences shown by the model are many: jump on oil price, higher exploration and recovery (due to the higher profitability of such investments), decline in GDP growth and energy demand, peak oil taking place earlier in time (with respect to the base case), faster transition towards renewable resources (a 5 years delay is considered to account for capacity and infrastructure building) and long term negative economic implications.
As any other model, T21 is a simplified representation of reality and it is not perfect (there is no such thing as a perfect model). This is still a work in progress and a preliminary North America version will be presented in Houston in October. Both the Millennium Institute and the ESF team are working hard to refine and improve the structure of the model and also collecting good data series.
To clarify a point on “open source”: anyone can have access to the source code of the model. In order to change it, you need to have Vensim (which has a very intuitive and user friendly interface) or be a good programmer in C. Dick was erroneously referring to the user version, which allows users to simulate various assumptions and policies without buying any software.
The model calculates carbon footprint and biocapacity. A large range of indicators can be used to “speak the language of different groups”.
John Freise and all, the World 3 model is also available for free for those who have Vensim for Ventana Systems. Let me know if you need more info on this.
Any reference or data that you think may be useful would be very helpful. We want to build an consistent model, able to identify unintended consequences and future paths of today’s choices. In order to do so we need to bring together very different schools of though and make them communicate with a single framework. We believe that T21 is such a tool, and will do our best to reach our goals.
We greatly appreciate your contribution and feedback, please keep posting and please asking questions. This is very helpful and will help us come up with a good model!
Andrea Bassi,
Millennium Institute
www.millennium-institute.org
OK, I'll throw one suggestion in here. Template a model of a prototype country, the various factors, interconnections within the country, etc. Then instantiate it for each country around the globe - with decision making on a per country basis and interconnections between individual country elements overlaid on top.
That way not only can you easily built the model from bottom up in an OO way to take account of the different situations of each country (reserves, fuel usage, sunlight, philosophy) - you can put a human in charge of each countries options and play an energy 'wargame' relatively easily.
You just to the point!
This is very similar to the project plan we are developing. The idea was to start with a North America model because the USA model was already being developed and because being an ASPO-USA project it would be nice to have a North America module well defined and hopefully used in the US.
The next step, Phase 2, include the creation of 5 additional regional models, aggregated and showing the big picture.
Phase 3 would consist in the creation of national models.
Both national and regional models are based on a starting framework and are then customized to represent specific country issues/characteristics.
The best outcome of the whole project would be to have students working from all over the world collecting data and updating the models year by year.
Hello Ms. Bassi,
Could you recommend any introductory textbooks in this field? (With math included please). Do you know of any detailed explanations of the World3 model? What kind of background is needed to work in this field?
BTW, for any TOD'ers who might want to learn more about computer models in general, check my website: http://www.myphysicslab.com. Contains simple physics simulations, interactive and real-time, with full math explanations and source code.
Don't try to predict the future. Get ready for it.
There are many books that can be useful to learn System Dynamics. The one I would recommend is certainly Business Dynamics (John D. Sterman).
This is considered to be THE book by most practicioners and professors. It contains an extensive explanation of the foundations of the methodology, it is well written and easy to follow.
There is no specific indication on the background. System Dynamics (SD) is a methodology, not a science, therefore it can be applied to a variety of fields. At the University of Bergen, Norway, where a full 2 years Master degree is offered, there are students coming from all over the world and with all educational backgrounds: economics, engineering, psychology, environmental science, sociology, etc.
SD aims at representing the structure of the system analyzed: this can be a supply chain, our brain, the economy, oil production, etc.
ps. It's Mr. Bassi (I am Italian)
I've checked the T-21 software available on your website (very nice work BTW):
You are predicting prices above $50 only after 2015 (it seems that your historical data stops in 2003-2004, already prices will probably average $70 for 2007):
World production will peak around 2022 at 36 Gb/year (~99 mbpd) which is assuming an URR around 2.8-3.0 Tb, the post peak decline seems also pretty steep:
Questions:
1. How did you model the different oil production sources (tar sands, shale oil, etc.)?
2. Can you produce error intervals?
Thank you for taking the time to look at the work already done on the USA model.
My answer to your questions follow:
1) Unconventional oil is not in the model yet, it will be included in the North America model, with tar sands in Canada mainly. Nevertheless, if you are aware of a good report or data series on production, reserves, and cost of unconventional oil, please forward it and I will try to add it before the presentation in October.
The graph you see is only showing conventional oil and liquid gas.
2) Every output of the model can be exported in MS Excel, therefore we can produce error interval. A large set of statistical tools are also available (e.g. R2)
A few comments on the graph for those who have not read the report:
a) Oil price is in real dollars (2000 is the base year). This is one of the reasons why the oil price seems lower in 2007 than it already is.
b) With T21 we project medium to longer term (5 to 10 years trends). As a consequence we look at the average price over a period longer than a year and we do not represent short term oscillations. Oil price already reached $70/bbl last year, but the average annual price in real terms was just a little above $50/barrel.
c)Historical data stop in 2007 (using the average of the first 6 months of the current year). Vertical lines in the graph show 5 years intervals.
d) We decided not to represent the oil price shock of the 80s. This is due to the fact that we want to represent the structure of the system analyzed and that shock was generated by exogenous decisions/events. Nevertheless shocks can be introduced to the model as we show towards the end of our report.
e) World oil production can change significantly when simulating different quantities of oil originally in place. Consequently URR changes as well. We ran a sensitivity analysis (Monte Carlo simulation) to show what would be the case of higher (USGS and Cambridge) or lower (ASPO) resource in place. More on this will be presented in the new report coming out in October.
f) the decline depends on technology (influenced by, among others, investment) and reserves available. The base run assumes that biofuels are available as needed, but with a 5-years delay for capacity building. This partially explains why production declines this quickly.
A nice feature of the model is that you can test different assumptions and policies and create your own scenario in less than 20 seconds. I encourage you to play with the model and to look at our presentation (July 16, New America Foundation). This would help you understand how the model works and how you can get the best out of it.
Thank you again for taking the time to review our work, any comment or suggestion on how to improve it is highly welcome!
Best,
Andrea
I would dispute exogenous, particularly of a global model. The very relationships and behaviours you seek to model and understand are mediated by such decisions/events. I would go so far as to say if they are not in your model at a ground floor level, then your model will only demonstrate gradual, differential, processes. The important factors in the domain you are seeking to understand will be mediated by shocks and discontinuities.
As a 'for instance', a decision to implement a widescale coal-to-liquids programme will not be a differential effect, it will be driven by a shock event that changes the political and economic landscape. That shock event will in itself be driven by other events. Even though these are discrete events, the circumstances and timings will be tightly controlled so as to make it essentially non random.
Your model needs to deal with that.
A model cannot project a political transition or random events (unless the causes for such events can clearly be identified). What we can do is to be create a flexible model that can be easily modified beforehand (if users want to simulate various scenarios) or when such events happen.
Tipping points and minor shocks are still represented, but as you mentioned, are a result of other effects and not exogenous decisions.
In addition, if the shock has a short/medium term impact and the system follows long term trends, our approach results to be still valid.
When we refer to long term projections we want to show what are the long term implications of certain actions (e.g. policies that trigger long term change). It takes time for policies to be effective and we want to show general trends: which direction will the system take if we apply this policy?
Taking the example of the 80s, what are in your opinion the main causes for the price shock? Are they structural?
Mr. Lawrence wrote:
Let me paraphrase, and then give my objection. What you (and Dennis Meadows et al) mean to say is roughly:
"We aren't trying to make exact predictions of the future. We only want to show how everything is interrelated, and you can't go on forever at the current rate."
There are a couple problems here. I get it, that you don't want to be tied to specific predictions about specific events at specific dates. You aren't even trying to do that.
But if there is no predictive power, why should anyone pay attention at all?
Mr. Lawrence, you need to face it: these models DO make predictions! They are just very different sorts of predictions from what people are used to.
If, in the 1970s, LTG (Limits To Growth) did not present it's "standard run" showing collapse happening around 2050, then nobody would have ever heard of LTG.
I understand that there were all kinds of distortion in the press of the LTG results. Obviously you want to avoid that. But the best way to do so is to tackle this head-on.
The prediction that the "standard run" makes is this: if we continue with BAU (business as usual) then our future is collapse.
Meadows et al hurry to provide disclaimers. "We did not consider it (the standard run) to be the most probable future, and we certainly didn't present it as a prediction. It was just a place to start, a base for comparison." (p. 168 of LTG- 30 yr update)
I think this is a mistake. I understand the difficulty in communicating what these models do through the blunt instrument of the press. But please, don't water down your results in this way.
Of course, BAU is unlikely. It is likely that some of the measures that LTG describes will take place to some degree. And of course exact prediction is not possible.
I encourage you to find some other ways to say this. Maybe something like this: "The default collapse scenario is in no way a specific prediction about timing. But it is a general prediction, that if we continue BAU then we run up against limits and the consequences are severe. Most importantly, it is a tool for people to use to imagine the likely effects of policy changes."
Meadows et al boil it down to four bullet points following this sentence (p. 177 of LTG-30)
(emphasis is theirs). They go on to list the essential features of the model: growth is desired & tends to be exponential; there are limits to sources and sinks; signals are distorted, delayed or denied; limits are erodable when overstressed, and there are strong non-linearities.
If these points could become widely known it would be a good start to having a future.
Best wishes for your project. I eagerly look forward to seeing the results.
Don't try to predict the future. Get ready for it.
I agree with your argumentations, though there are some additional comments to make.
Modelers use to talk about "projections" and not "estimations" to acknowledge the limitations of their models. Also, in this specific case (global energy model) we look at medium to long term trends, that is why we will most probably not capture every single data point from 1980 to 2006. As a consequence, talking about estimations is not 100% correct.
At the same time, as you said, we do make projections for the future hoping that the results of the model can contribute to change some of today's policy making mechanisms.
A second though is about the use of a model. If we simulate a scenario and publish an article on it, most of the readers will assume that that scenario represents our point of view. The consequence is then straight forward: some like it and some others discard it, no discussion.
On the other hand, with T21 we want to let the users play their own scenarios and engage confrontation.
We would like to build a non partisan, objective model and allow different users to discuss about their assumptions and suggested policies. This one of the reasons why, in my opinion, it is good to focus on projections, making sure that there is no misunderstanding about the results of the model.
If then ASPO-USA or any other organization wants to publish a scenario that represents their ideas, that can be done but as you said it has to be stated clearly.
Copied from a Drumbeat post:
My simplistic Export Land Model (ELM), for a hypothetical country, shows that from peak production and peak exports, only about 10% of future production would be exported, with consumption equal to 50% of production at peak. Starting from peak production/peak exports in the ELM, net exports during the peak year would represent about 18% of all remaining future net exports.
Regarding real data, my guess is that we are now consuming, worldwide on an annual basis, between 5% and 10% of all the oil that will ever be exported.
Note that the decline rate in net exports should accelerate with time.
http://www.theoildrum.com/node/2608
Russian Car Sales & Net Oil Exports
Posted by Khebab on June 9, 2007 - 8:46am
This a guest post by Jeffrey J. Brown (westexas)
Excerpt:
I would like to interact with the modelers on my proposals.
1) My -10% Plan (I understated the savings since my proposed infrastructure has Elasticity of Supply)
http://www.lightrailnow.org/features/f_lrt_2006-05a.htm
and a subset with more details
http://www.lightrailnow.org/features/f_lrt_2007-04a.htm
My own estimate is that after a 4 to 5 year "delay" just Electrified Rail can offset -1.5% oil use with a roughly 20 BTUs of oil to 1 BTU of electricity (18 to 1 is an equally good #). This is a modified BAU approach with modest declines in oil availability and investing about $70 billion/year.
If things get worse than that, "adjustments can be made" with USA 1897-1916 as a model of a low energy maximum effort response (ties of concrete or recycled plastic instead of wood). Lots of labor, little oil.
2) My unpublished efforts for designing a non-GHG North American electrical grid.
My eMail is in the link to my name.
Best Hopes,
Alan Drake
WT,
You're right that the Export Land hypothesis of your's and Khebab's is a simplistic explanation, and Ace's Import Land hypothesis is another simplistic hypothesis, although it's an important advance.
The problem is that any scientific theory makes assumptions before we gather data, it's a problem of perspective. It takes keen judgement just to know what data is essential to frame a question. And, on something as complex as this, the situation changes very rapidly as the data is gathered.
Here's an example. I think that Pemex's announcement that they will have no oil to export in seven years, and Venezuela's announcement that their exports will end in two years are perfect support that your Export Land Theory is correct. But, the 5% rate of decline that you used in your model is inaccurate, and the Pemex and PDVSA figures are not correct either. They are both dependent on internal consumption expansion, which will go on only if we avoid a depression, and accurate modeling of their field depletion rates, and country depletion rates, plus the changing economics as the sales price increases because shortages, or decreases because of recession/depression in the customer's economies.
In other words, it's so complex that the problem resembles modeling a hurricane landfall spot and intensity forecast as the storm is headed our way.
The geopolitical considerations color our perceptions too. We are very likely to lose all our Mideast bases if we leave Iraq, and its quite possible that no American company will be allowed to purchase Mideast oil. They may decide to sell all the remaining exports to the Chinese, who haven't interfered in their politics. If there is a very limited supply, the OPEC members could pick and choose their customers, just like the US did when we cut off exports to the Japanese and Germans before WWII.
Is the CIA and the military modeling that? They damn sure need to be. How can a model like the Export land hypothesis include that type of scenario, especially when the problem is happening in real time?
So any rate, as Oat Willie said, "Onward through the fog". I'm just glad we have fine minds like yours, Khebab's, Stuart's and Nate's working on various aspects of the problem. Meanwhile, the US congress and president dither away with no comprehension of the serious nature of the problem.
Bob Ebersole
Thank you westexas, for continuing to remind us of the terror of peak exports. Which is true, and a whole lot more scary than peak oil - or even peak net energy from oil.
"America is not a young land: it is old and dirty and evil before the settlers, before the Indians. The evil is there waiting." William S. Burroughs
I'm currently finishing a paper that I will present parts of at ASPO on a framework for alternative energy supply. We need to consider scale (scale encompasses what we refer to here as EROI, net energy, energy suplus, and energy gain in the Tainteresque sense, etc), flow rates (and scale times flow equals power), timing, environmental impacts, and energy quality. Quality is a very nuanced concept and includes such things as gravimetric density, volumetric density (precluding using hydrogen with current technology), geographic distribution, volatility and intermittency, and existing fixed societal infrastructure.
How many BTUs we have and how many we can get to market to provide energy services are important questions, but all BTUs are not created equal. A cheetah will expend energy to kill and eat an antelope, but would have a very low, probably sub-unity energy return when faced with a horse. A 2nd century tribesman in Saudi Arabia would have little use for refined gasoline but great use for a horse. If I had to ride a horse to visit my girlfriend, I'd never make it, but can make it in a few hours using liquid petroleum or gasahol, etc.
This Modeling Project is a great and important idea. But also a tall task. Its a shame that some arm of the government can't fund this venture with resources, both financial and human.