Fossil Fuel Production with Supply and Demand Interactions

Steve Mohr has published his Thesis at the University of Newcastle, Australia:
Projection of world fossil fuel production with supply and demand interactions

Abstract

Historically, fossil fuels have been vital for our global energy needs. However climate change is prompting renewed interest in the role of fossil fuel production for our energy needs. In order to appropriately plan for our future energy needs, a new detailed model of fossil fuel supply is required. It is critical to know if fossil fuels will still be able to supply most of our energy requirements and meet the ever increasing energy demand in the future. Answering these questions is critical in order to identify potential periods of energy shortages; so that alternative energy resources can be utilised in a timely way. The aim of this study was to develop a model to predict fossil fuel production for the long term based on historical production data, projected demand, and assumed ultimately recoverable reserves for coal, gas and oil. Climate change is an important issue confronting society, and it is hoped that the work contained in this thesis will aid climate change modeling by focusing attention to realistic fossil fuel production projections. Fossil fuels are currently an essential component in the global economy and the growth of the human population. The fossil fuel production projections from this study suggest that many of the IPCC fossil fuel projections appear overly optimistic. Based on the assumed URR values, it is predicted that global fossil fuel production will peak before 2030. For this reason, it is imperative that appropriate action be taken as early as possible to mitigate the effects of fossil fuel decline, to avoid energy shortages in the near future.

Conclusions (excerpt)

The combined supply and demand model includes the capability that demand and production could be influenced by each other, i.e. if production could not meet demand then future demand for that energy source was reduced. In this study, three options were considered. Firstly, the STATIC option resulted in demand and production acting independently of each other at all times. Secondly, the DYNAMIC option allowed both total demand and total production to change from the STATIC situation when there was a difference between the two. Finally, the INDEPENDENTLY DYNAMIC option was an extension to the DYNAMIC situation, but treated each fuel source individually when applying the supply and demand interaction, with both demand and production being able to vary.

The model requires estimates of Ultimately Recoverable Resources (URR) for coal, gas and oil. Following a critical review of the literature, included in this study, three cases were adopted. CASE 1 and CASE 3 being lowest and highest recent estimates, respectively, and CASE 2 being author’s best guess based on the information available. The URR values for CASE 2 were, total (60,800 EJ), coal (19,350 EJ), gas (17,680 EJ) and oil (23,780 EJ).

Oil: For CASE 2, peak production year remained almost constant at 2011-12 for STATIC, DYNAMIC and INDEPENDENTLY DYNAMIC options, with peak production varying only marginally between 179–188 EJ/y. Similarly, for CASE 1, peak production year was the same at 2005 for all three supply and demand interaction options. For CASE 3, peak production year varied only slightly at 2019, 2011 and 2016 for STATIC, DYNAMIC and INDEPENDENTLY DYNAMIC options, respectively. The important outcome was that for all scenarios the maximum peak year was 2019.

Combined fossil fuels: For CASE 2, peak production year remained almost constant at 2016–18 for STATIC, DYNAMIC and INDEPENDENTLY DYNAMIC options, with peak production varying only marginally between 509–525 EJ/y. Similarly, for CASE 1, peak production year was essentially same at 2012–13 for all three supply and demand interaction options. For CASE 3, peak production year varied from 2021 to 2029 across the three supply and demand options. In all scenarios it was found that natural gas offers the biggest future potential, and not coal.

[via Energy Bulletin]

World3 in Modelica: System Dynamics Models

World3 in Modelica: Creating System Dynamics Models in the Modelica Framework

This paper and presentation by F. E. Cellier introduces a new release of the System-Dynamics library of Modelica and shows how it is being used by discussing a fairly large application code: Meadows’ World3 model.

Meadows’ only talked in Limits to Growth about the results obtained with the model. The model itself, originally coded in Dynamo, was described in a separate book.

Meadows’ World3 model has seen two major upgrades since its original inception, one in 1992, i.e. after 20 years, and the second in 2002, i.e., after 30 years. The World3 application code contained in SystemDynamics 2.0 implements the 2002 version of the World3 model. In the code, we offer not only the basic model, but also all 10 scenarios that Meadows and co-workers are talking about in Limits to Growth: The 30-Year Update.

Future Research

What future additions are in the works? In today’s world of dwindling fossil fuel reserves, it becomes important to track how much energy we are actually using. Whereas classical System Dynamics is designed to track material flows, it does not track energy flows. This is a major drawback of the methodology.

For this reason, a second version of the System Dynamics library has also been released as a sublibrary of BondLib, our bond graph library. In that version, all material flows are represented internally by bond graphs. A bond graph naturally tracks energy flows. Each energy flow, in that version of the library, is represented as the product of a specific enthalpy and a mass flow. Hence we can track material flows and energy flows simultaneously.

When I drive my car from home to work, I am not only spending energy in the form of the gas that my car consumes. Some energy was also spent in producing the car, and more energy will be spent in discarding it at the end of its lifecycle and in recovering those materials from it that can be recycled.

The accumulated energy that accounts for all of those indirect uses of energy is called emergy. The specific enthalpy can be used to encode in the model the specific emergy, i.e., the emergy per unit of mass.

I plan on porting examples of emergy modeling, as described in the publications by Howard Odum, over to the bond graph implementation of the System Dynamics library, but this work has not yet been completed.


Check out the full paper and presentation by Prof. Dr. François E. Cellier here.

Online World Simulation

This online Simgua World simulation predicts the macro-level development and change of the entire world. There are six main sectors in it: a food system, a population system, a pollution system, a nonrenewable resource system, and an industrial system.

You may experiment with several variables of the model including the initial level of nonrenewable resources, the start year for the implementation of a high-tech improvement policy, and the delay between technology development and its implementation.

You may download the model to control many more variables. This world simulation is based on the World3 model developed by the Club of Rome. This model was used in the original Limits to Growth publication in 1972.

Simgua is a next-generation, no-nonsense modeling application that helps you develop powerful models and simulations.

The Limits to Growth and Beyond Growth

The Limits to Growth is a famous 1972 book modeling the consequences of a rapidly growing world population and finite resource supplies, commissioned by the Club of Rome. Its authors were Donella H. Meadows, Dennis L. Meadows, Jørgen Randers, and William W. Behrens III. The book used the World3 model to simulate[1] the consequence of interactions between the Earth's and human systems.

Five variables were examined in the original model, on the assumptions that exponential growth accurately described their patterns of increase, and that the ability of technology to increase the availability of resources grows only linearly. These variables are: world population, industrialization, pollution, food production and resource depletion. The authors intended to explore the possibility of a sustainable feedback pattern that would be achieved by altering growth trends among the five variables.

The most recent updated version was published on June 1, 2004 by Chelsea Green Publishing Company and Earthscan under the name Limits to Growth: The 30-Year Update. Donnella Meadows, Jørgen Randers, and Dennis Meadows have updated and expanded the original version. They had previously published Beyond the Limits in 1993 as a 20 year update on the original material.

In 2008 Graham Turner at the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Australia published a paper called "A Comparison of `The Limits to Growth` with Thirty Years of Reality". It examined the past thirty years of reality with the predictions made in 1972 and found that changes in industrial production, food production and pollution are all in line with the book's predictions of economic and societal collapse in the 21st century.

"For the first 30 years of the model, the world has been tracking along an unsustainable trajectory," Turner concludes. Herman Daly of the University of Maryland says these results show that we "must get off the growth path of business as usual, and move to a steady state economy", stopping population growth, resource depletion, and pollution.