OwlSim: Revolutionizing National Energy Policies Through Technology
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Transcript of OwlSim: Revolutionizing National Energy Policies Through Technology
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OWLSIM: REVOLUTIONIZING NATIONAL ENERGY POLICIES THROUGH TECHNOLOGY
COMP 410 in Collaboration with Citizens for Affordable Energy
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Overview• Introduction • Simulation Framework• Energy Model and Plans• Advanced Features• Conclusion• Questions
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Overview• Introduction
• The Class: COMP 410• The Customer: Citizens for Affordable Energy• Project Motivation• The Mission• The Team
• Simulation Framework• Energy Model and Plans• Advanced Features• Conclusion• Questions
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The Class: COMP 410• “Software Engineering Methodology”• Design class satisfying computer science Bachelors of
Science degree capstone requirement• Warm-up project during first 3 weeks, then semester-long
project … with a real customer!• Student driven – no problem sets or lectures
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The Customer:Citizens for Affordable Energy
• CFAE is a national not-for-profit membership association• Goal is to educate citizens and policymakers about non-
partisan national energy solutions• Leadership
• John Hofmeister, Founder and CEO• Karen Hofmeister, Executive Director
• www.citizensforaffordableenergy.org
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Project Motivation• CFAE is concerned with the lack of a long-term national
energy policyCurrent policy may result in serious shortfalls in energy availability, affordability and sustainability
• CFAE wants a public software tool to simulate the long-term effects of national policies
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The Mission• Develop a simulation framework to predict the effects of
policies• Model U.S. electric power generation and distribution • Create plans corresponding to best, average, and worst
case scenarios • Make the results accessible to the public
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The Team• User Interface Team
• Jesus Cortez (Team Leader)• Robyn Moscowitz• Tung Nguyen• Narae Kim
• Simulation Team• Ashrith Pillarisetti (Team Leader)• Linge Dai• Mina Yao
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The Team• Modeling Team
• Irina Patrikeeva (Team Leader)• Elizabeth Fudge• Ace Emil
• Framework Team• Weibo He (Team Leader)• Jarred Payne• Yunming Zhang• Xiangjin Zou
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The Team• Robert Brockman II – Project Manager• James Morgensen – Architect • Daniel Podder – Integration Master• Elizabeth Fudge – Organization Master
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Overview• Introduction • Simulation Framework
• Theoretical Design• System Capabilities
• Energy Model and Plans• Advanced Features• Conclusion• Questions
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Theoretical Design• Modeling complex systems with mathematical functions• Functions represented as modular “circuit elements” with
inputs and outputs• Functional modules can be “composited”
• Encapsulate components of model• Allows composite modules with other modules inside.• Arbitrarily complicated models can be created
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System Capabilities
• Scalability & Elasticity• Scaling up and down according to loads• Possible Parallel and distributed simulation instances• Possible Load Balancing
• Flexibility• Supporting multiple Use Cases• Easy Maintenance, low cost
• Stability• Handling hardware failures• Handling software failures
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Overview• Introduction • Simulation Framework• Energy Model and Plans
• Model Implementation• Viewing the Results• Worst, Average and Best Case Scenarios
• Advanced Features• Conclusion• Questions
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Energy Model Implementation• Four main components drive the simulation
2. Infrastructure
3.Consumer
4. Environment
1. Producer
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The Model Details1. Producer simulates
• Production of electricity from:• Coal, Natural Gas, Nuclear,Hydroelectric, Wind, Solar, Geothermaland Other (fuel cells, hydrogen, etc.)
• Production of transportation fuel• Oil (petroleum) and Biofuels
• Inputs:• Electricity and fuel demand from Consumer• Electricity lost from Infrastructure
• Outputs:• Electricity and fuel price to Consumer• Electricity and fuel produced to Infrastructure• Pollution to Environment
2. Infrastructure
3.Consumer
4. Environment
1. Producer
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The Model Details2. InfrastructureSimulates transport of electricity and fuel
• Inputs: • electricity and fuel produced in Producer
• Outputs: • Pollution to Pollution module• Fuel transportation cost to Consumer• Electricity lost to Producer
2. Infrastructure
3.Consumer
4. Environment
1. Producer
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The Model Details3. Consumer• Inputs:
• Fuel transportation cost from Infrastructure• Electricity price from Producer
• Outputs:• Electricity and fuel demand to Producer• Pollution to Environment
2. Infrastructure
3.Consumer
4. Environment
1. Producer
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The Model Details4. EnvironmentCalculates the net pollution emitted during one time step• Inputs:
• Pollution from Producer• Pollution from Infrastructure• Pollution from Consumer
• Outputs:• Total pollution graph over time
2. Infrastructure
3.Consumer
4. Environment
1. Producer
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Simulation Design• The system starts at 2010 with a list of initial values
(assumptions)• Based on the assumptions the output of simulation will
change• User can provide events that change both initial values
and future parameters• Events are system parameters that affect a system at a
certain date for a specified period of time• Events allow to model technological progress, natural
disasters, and other events that affect energy system
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User Assumptions and Events• User has the ability to change many aspects of simulation• Example events
• How much electricity and fuel is produced from each source• Net electricity and pollution produced from each source• Power plants capacity• Electricity lost due to transmission • Cost of electricity production • Population growth rate
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Worst-Case Plan• Simulation runs with default values (2010 data)• No new power plants are built• Nothing is done to reduce pollution• Population and energy demand grows while supply
decreases due to decommission of old power plants
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Average-Case Plan• User builds new energy sources • Producing more electricity from cleaner renewable energy
reduces the gap between supply and demand• Environmental pollution is reduced• No technological breakthroughs (capacity and cost of
production do not drastically change)
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Best-Case Plan• Supply meets demand• Energy is produced from clean renewable sources at
affordable price• Pollution is reduced
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Comparison with Other Models• No complicated equations • Directly shows user changes• Easy to use and test various assumptions• Unbiased
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Overview• Introduction • Simulation Framework• Energy Model and Plans• Advanced Features
• Changing the Plans• Changing the Model• System Administration
• Conclusion• Questions
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Changing the Plans• User logs in using a Windows Live ID• User can edit a plan
• Change inputs to simulation• Adding, changing events
• User can save plan• Simulate model with modified plan
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Changing the Model• Allows completely customized models using XML format
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System Administration• Used by CFAE administrators • Adding Users• Changing Privileges
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Overview• Introduction • Simulation Framework• Energy Model and Plans• Advanced Features• Conclusion
• Implications for Energy Policy Development• Acknowledgements• Summary
• Q&As
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Implications for Energy Policy Development
• Ability to model new policies rapidly• Lots of flexibility• Common ground to model different policies with same
framework• Education of public• Public forum for discussion on energy policy
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Acknowledgements• CFAE
• John Hofmeister, Karen Hofmeister• Professors
• Dr. Stephen Wong, Dr. Scott Rixner• TAs
• Dennis Qian, Max Grossman, Milind Chabbi, Rahul Kumar• Oshman Engineering Design Kitchen staff• Microsoft
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Acknowledgements• Smalley Institute:
• Dr. Wade Adams• Dr. Carter Kittrell
• Dr. Richard Johnson• Steven Wolff• Others
• Jeffrey Bridge, Jeffrey Hokanson, Stamatios George Mastrogiannis
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Summary• Extensible framework for energy simulation• Publicly accessible web application• Graphical output• Modifiable assumptions• Pre-computed models • Three energy plans for the next 50 years
Questions?
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References• EIA etc.