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7/6/2009 © 2009 Energy-Redefined. All Rights Reserved. . 1 Gary Howorth Founder July 7 2009 Euro XXIII Bonn Germany The Simulation & Optimization of Technology to Address Climate Change
7/6/2009© 2009 Energy-Redefined. All Rights Reserved.
.1
Gary Howorth
Founder
July 7 2009 Euro XXIII Bonn Germany
The Simulation & Optimization of Technology to Address Climate Change
Abstract
Climate change when coupled with the interaction of politics is an incredibly complex system. Optimization or control of such a system using conventional techniques is difficult and fraught with a myriad of issues. The paper will consider a number of models that the author has explored in Industry to help frame key questions in the current climate debate. This has involved consideration of policy, technology and the modeling of carbon emissions. The author's current approach uses a combination of methods including complexity approaches. Initial results fromthe model will be presented.
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Some Thoughts from my Modelling
Carbon, Technology & Politics are inextricably linked – but how do we represent them?No one right model – got to be fit for purpose (speed vs accuracy)Models to represent reality but they are not reality !!Evolution of and volatility in prices/markets is an important driver of participant investment behavior• Actors are not homogenous – each
company will view the world differently• Non linear – more than one equilibrium
Key Factors but what are they?
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Getting Factor X right !!!
Network models
Multitude of Approaches but which One Should we use?
Integration
Value chains
Real options
Portfolio
Models
Valuations
Company behavior
timing and market impact
Evolution and trade movements
behavior
Trading
Technology/Coalitions
Data
State Space
Agent based models
System Dynamics
Networks
Market analysis
Market behavior
Cluster analysis
Market forecast Spot prices
Coalitions
A Technology & Carbon Model
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Oil PriceNat Gas Price
CoalElec PricesCorn PricesUranium etc
Emissions
Carbon legislation /rules regulations
Costs
Cash flows competition etc
Subsidies/Tax
GDP Ex Rates
Investments/Technology
SteelPower
OilChemicals
Paper & Pulp…..
Carbon marketStructure
Company Behavior
Politicians
Carbon prices
Weather
Jobs, leakage
Network effects
Adequately capture the non lineariities in
the macro system
Non Linearity's Everywhere – Just One Component
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Marginal Abatement Curve Cement
-40
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mm Tonnes of CO2 avoided$/
CO
2te
Industry and Behaviors affect MAC’s
Lower coal price & lower Clinker %
Company cash-flow constraint
With Powerjust cementsavings
Marginal Abatement Curve Cement
-40
-20
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mm Tonnes of CO2 avoided
$/C
O2t
e
0
5
10
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1 2 3 4 5 6 7 8 9
Years
Penc
e pe
r The
rm
Long Term EquilMean Reversion 1What HappenedMean Reversion 2
Long Term Equilibrium. What Supply and Demand
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Supply - Demand(1998 only)
-1000
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500
1000
1500
BG Power Generators Marketers
mm
scfd
Price Volatility +70% -50% Important to model individual companies positions
Market in Balance but …
Areas of Focus is Different for Each Company – Oil Industry Example
Shell
BP
Flaring
GTL
Type of Development Country
Heavy Oil
LNG
Will affect the way the company invests and the way it trades and ultimately the prices
Other TechnologiesConventional technology mainly about costs and production efficiencies
Focus of Technologists on incremental technologies
But technologies from outside the business could have a great effect
EOR
costs
Plug in Hybrids
Smart sensors
Batteries
Downholepower
“Platformless”
developments
Nano
Change in load curve –less installed capacity
Favoring Nuke
Reservoir simulations
BiotechNew fuels
Carbon conversion CCS IGCC’s CTL
with CCS
Quantum computing
Reservoir optimizations
New trading algorithms
Conventional
Wind Solar
New Materials
Syngas
Subsea and AUV’s
Ultra deepwater Arctic and other Frontier areas
Lower demand
Invest or Wait: The Effect of Network Effects.
Specific Sector Energy Technology Interactions
Inject funding – Size of sphere represents amount of effort/funds
Driven by politicians?
Where does that funding end up:
Impacts carbon markets
Impacts Technology network
Technological Interactions
Technologies
Interactions
Stimulus and funding applied here
Under certain conditions stimulus permeates and cascades to here
Evolution of the Network of Coalition of Interests ‐ Politics
National governmentsU.S. state governmentsCompanies and individualsOrganizations
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Degree, K
P(k)
Networks Interact and Change due to other Interactions
Technologies
Governments/Politics
Institutions/Coalitions
Corporate
Markets/Needs
Environment eg. Oil prices
Conclusions – Key Messages
Externalities – really important – eg Network effects – leakageLots of uncertainty in key data – Optimizing under uncertainty and multiple goalsPath is important – Evolution /Non linearitiesNetwork AdaptVolatility and market structure greatly affect business decisions and participant behavior – ie path and pricesCarbon Accounting – key issue – now in the hands of politicians
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There is a lot of work to do
