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 Goal: educate citizens and policymakers about non-partisan national energy solutions National non-profit headed by – John Hofmeister, Founder and CEO – Karen Hofmeister, Executive Director

Project Motivation Problems: Lack of a long-term national energy policy Current policy may result in serious shortfalls in energy availability, affordability and sustainability Not a high-profile national policy issue CFAE believes we need a publicly accessible software tool to simulate the long-term effects of national policies *compress

The Mission Develop a simulation framework to predict the effects of policies Model U.S. electric power generation and distribution Create policies 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 – Ashrith Pillarisetti, 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 – Xiangjin Zou

The Team 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

Design Goals Ease of Use Flexibility, Extensibility Handle Arbitrary Complexity Scalability

Theoretical Design Modeling complex systems with interconnected mathematical functions – Separates the problem into interconnections and isolated functions (FIX WORDING) Functions represented as modular “circuit elements” with inputs and outputs (Diagram of a connected thing with functions, +) Functional modules can be “composited” – Encapsulate components of model – Allows composite modules with other modules inside. – Arbitrarily complicated models can be created

System Requirements 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

The Solution: Microsoft Azure Cloud system – Vast Compute services available – Scale up / scale down All of these issues are handled by Azure transparently

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 in model – Producer – Consumer – Infrastructure – Environment Feedback loop determines price, supply, demand, and pollution Reliable known values User can set TODO model parameters User can set uncertain values and create future events

Model Events User chooses events from a list – Create new power plant – Increase power plant capacity – Decrease pollution emission – TODO

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 Pros Cons – May not accurately represent reality

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, Milind Chabbi, 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

QUESTIONS

References EIA etc.