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OwlSim : Revolutionizing National Energy Policies Through Technology. COMP 410 in Collaboration with Citizens for Affordable Energy. Overview. Introduction Simulation Framework Energy Model and Plans Advanced Features Conclusion Questions. Overview. Introduction The Class: COMP 410
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OwlSim: Revolutionizing National Energy Policies Through Technology COMP 410 in Collaboration with Citizens for Affordable Energy
Overview • Introduction • Simulation Framework • Energy Model and Plans • Advanced Features • Conclusion • Questions
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
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
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
Project Motivation • CFAE is concerned with the lack of a long-term national energy policy Current 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
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
The Team • User Interface Team • Jesus Cortez, Team Leader • Robyn Moscowitz • Tung Nguyen • Narae Kim • Simulation Team • AshrithPillarisetti, Team Leader • Linge Dai • Mina Yao
The Team • Modeling Team • Irina Patrikeeva, Team Leader • Elizabeth Fudge • Ace Emil • Framework Team • Weibo He, Team Leader • Jarred Payne • Yunming Zhang • XiangjinZou
Management and Support • Robert Brockman II – Project Manager • James Morgensen – Architect • Daniel Podder – Integration Master • Elizabeth Fudge – Organization Master
Overview • Introduction • Simulation Framework • Theoretical Design • System Capabilities • Energy Model and Plans • Advanced Features • Conclusion • Questions
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
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
Overview • Introduction • Simulation Framework • Energy Model and Plans • Model Implementation • Viewing the Results • Worst, Average and Best Case Scenarios • Advanced Features • Conclusion • Questions
Model Implementation • Four main components drive the simulation • Producer Module • Consumer Module • Infrastructure Module • Environment Module
The Model Details • Producer simulates • Production of electricity from 8 sources • Coal • Natural Gas • Nuclear • Hydroelectric • Wind • Solar • Geothermal • Other (fuel cells, hydrogen, etc.) • Production of transportation fuel from 2 sources • Oil (petroleum) • Biofuels
The Model Details • Infrastructure module simulates • Transport of electricity and fuel • Exchanges the price with Producer module • Consumer module simulates • Electricity and fuel demand from consumers • Environmental module simulates • The net pollution emitted by Producer, infrastructure and consumer modules
Simulation Design • The system starts at 2010 with a list of initial values or assumptions • Based on the assumptions Producer calculates net production of electricity and fuel • User can provide events that change assumptions and affect the energy future generation
User Assumptions • User has the ability to change many aspects of simulation, including (but not limited to): • How much electricity and fuel is produced from each source • Net electricity and pollution produced from each source (by changing power plants capacity) • Electricity lost due to transmission • Cost of production from each source • Population growth rate
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
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)
Best-Case Plan • Supply meets demand • Energy is produced from clean renewable sources at affordable price • Pollution is reduced
Comparison with Other Models • No complicated equations • Directly shows user changes • Easy to use and test various assumptions • Unbiased
Overview • Introduction • Simulation Framework • Energy Model and Plans • Advanced Features • Changing the Plans • Changing the Model • System Administration • Conclusion • Questions
Changing the Plans • User logs in using a Windows Live ID • Edit plan • Change inputs to simulation • Adding, changing events • Save plan • Simulate model with modified plan
Changing the Model • Allows completely customized models using XML format
System Administration • Used by CFAE administrators • Adding Users • Changing Privileges
Overview • Introduction • Simulation Framework • Energy Model and Plans • Advanced Features • Conclusion • Implications for Energy Policy Development • Acknowledgements • Questions
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
Acknowledgements • CFAE • John Hofmeister, Karen Hofmeister • Professors • Dr. Stephen Wong, Dr. Scott Rixner • TAs • Dennis Qian, Max Grossman, MilindChabbi, Rahul Kumar • Oshman Engineering Design Kitchen staff • Microsoft
Acknowledgements • Smalley Institute: • Dr. Wade Adams • Dr. Carter Kittrell • Dr. Richard Johnson • Steven Wolff • Others • Jeffrey Bridge, Jeffrey Hokanson, Stamatios George Mastrogiannis
References • EIA etc.