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OwlSim, developed in collaboration with Citizens for Affordable Energy, is a simulation framework that models U.S. electric power generation to predict national energy policy effects. The project aims to provide accessible plans for various scenarios, offering advanced features for public use.
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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 • Supports many simultaneous users • Scales with load • Basic use case • View model, plan, precomputed results • Authenticated use case • Edit plan, recompute results, save results • Expert Authenticated use case (if working) • System Administration use case (if working) • Publish results (if working)
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.