1. { Tomorrow’s Energy Today Final presentation - COMP 410 F12

2. { Electrons run our lives. Motivation

10. Availability Sustainability Affordability

11. { A Tool for the Future Introduction

12. {{ COMP 410  14 CS students  Semester-long senior design course  Completely student- run  Given problem statement  Not a project Hard at Work! Who are we?

14. {{ John Hofmeister  Former President of Shell  Chief Executive of CFAE Citizens for Affordable Energy  Mission to educate citizens and government about pragmatic, non- partisan affordable energy solutions Customer

15.  Develop a simulation framework capable of simulating the results of custom made energy plans for different energy models  Create a non-partisan plan for the U.S. energy system for the next 50 years  Availability, affordability and sustainability Problem Statement

16.  Verify the plan produces desired results on simulator  Make the plan and results readily available to the public to verify and edit Problem Statement

17. I. Model of the US Energy Industry II. Best-case, average-case, and worst- case 50-year plans for the energy industry III. Simulator I. Public Web Interface II. Cloud Storage III. General Purpose Modeling Specification

18. I. Our plans (best, worst and average cases) for the US electrical industry for the next 50 years. II. Our model of the US electrical industry. III. Demonstration of our plan and our model in the simulator. IV. Explanation of simulator. Contents

19. { Average, Best, and Worst Cases Plan for the Future

20. Plan Overview  Components  Assumptions  Data via the EIA (Energy Information Administration)  Events  Projections based on current data  Divided into four key sections  Consumers  Producers  Environment  Infrastructure

21. Plan - Consumers Assumptions  312,000,000 U.S. citizens  1.797 MWhr average peak demand per capita per month Events  All Cases  Population grows by.79% each year.  Worst Case  Average peak demand remains increase greatly.  Average Case  Average peak demand increases.  Best Case  Average peak demand decreases.

22. Plan - Producers Assumptions  8 sources of electricity  Coal, Petroleum, & Natural Gas  Nuclear  Geothermal, Hydroelectric, Wind & Solar  Each has:  Capacity (in MW)  Operating Cost (in $)  Carbon Output Rate (in lbs/kWh) Events  All Cases  Scheduled coal plant retirements.  Worst Case  Status quo  Average Case  Invest in natural gas  Best Case  Invest in natural gas, nuclear, and wind

23. Plan - Infrastructure Assumptions  Average of 7% lost in energy transport. Events  Worst Case  Status quo.  Average Case  2040, smart grid decreases losses to 4%  Best Case  2035, smart grid decreases losses to 1%

24. { Representing an intertwined system. Energy Model

25.  Model: A representation of the energy industry in terms of interconnected modules.  Module: An object which wraps a function and keeps track of values.  Function: A piece of code or math which takes a set of input values and computes a set of output values. Energy Model

26. Model Cont. Add Function Sub Mult Add ModuleModel Add 3 5 8

27.  “Characterized by interdependence, mutual interaction, information feedback, and circular causality.” - System Dynamics Society System Dynamics SocietySystem Dynamics Society  Abstraction of systems as a series of stocks and influential flows  Benefits:  Extensibility  Comparability System Dynamics

28. {{ Extensibility  Quickly and easily break down simple stocks/flows into more complex ones. Comparability  Determine differences in functionality between different models. SD Advantages

29. Producer Consumer Infrastructure Environment Price

30. {

31.  Five Modules  Consumer  Producer  Infrastructure  Environment  Price Our Model

32. Consumer Module

33. Consumer Demand Curve

34. Producer Module

35.  Desired percentage = F(current price, operating cost)  Supply = capacity * desired percentage  Carbon = supply * carbon output rate Energy Source Module

36. Environment Module

37. Infrastructure Module

38. Price Module

39.  Price change % = F(current price, supply, demand)  Change in price = (price change % * current price)/delay  Price = change in price + current price Price

40. { A Tool for Policy Simulator

41. Load pre-constructed models and plans. Load pre-constructed models and plans. Make edits to models and plans dynamically. Make edits to models and plans dynamically. Save new models and plans for later use. Save new models and plans for later use. Run a simulation and view results. Run a simulation and view results. Features

42. { (Look at the other screen! ) Demonstration

43. Architecture

44. The two main Design decisions: ASP.NET MVC4 ASP.NET MVC4 JsPlumb JsPlumb User Interface Architecture

45.  Goals  Connect Azure VMs for other subsystems.  Manage the process of spawning and killing Azure VMs.  Balance load across VMs.  Provide persistent storage. Network Subsystem

46. Network Architecture

47.  WCF  Abstracts lower-level networking away for simplicity.  With TCP, faster than CloudQueues.  SQL Database  Slower than Table Storage, but allows relational organization and querying. Design Decisions

48. Model Architecture

49. The Module Function

52. { A Stepping Stone for Policy Decisions Conclusion

53.  First-step to actually testing various models and plans for the electricity industry.  Use during policy discussions  General purpose modeling tool  No knowledge that a simulation has to do with a particular industry  Can represent any system of interconnected functions  Can be used in many situations, across industries and disciplines Analysis

54.  Improving on the model of the electricity industry  Multiple user levels  Redefine user interface, make more accessible, add features  Optimizing feature of load balancing on cloud (CPU Diagnostics) Future Work

55. Microsoft Microsoft Citizens for Affordable Energy Citizens for Affordable Energy John & Karen Hofmeister John & Karen Hofmeister School of Engineering School of Engineering CS Department CS Department COMP 410 Staff COMP 410 Staff Dr. Wong & Dr. Rixner Dr. Wong & Dr. Rixner Thank you!

56. Q & A