Tomorrow’s Energy Today

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

2. Motivation Electrons run our lives.

10. ??? Availability Sustainability Affordability

11. Introduction A Tool for the Future

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

14. John Hofmeister Citizens for Affordable Energy Mission to educate citizens and government about pragmatic, non-partisan affordable energy solutions • Former President of Shell • Chief Executive of CFAE 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. Model of the US Energy Industry • Best-case, average-case, and worst-case 50-year plans for the energy industry • Simulator • Public Web Interface • Cloud Storage • General Purpose Modeling Specification

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

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

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

21. 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 the same. • Average Case • Average peak demand increases. • Best Case • Average peak demand decreases. Plan - Consumers

22. 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 Plan - Producers

23. 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% Plan - Infrastructure

24. Energy Model Representing an intertwined system.

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. Sub Add Add 8 3 Mult Add Function Module Model 5 Model Cont.

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

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

31. Five Modules • Consumer • Producer • Infrastructure • Environment • Price Our Model

32. Consumer Module

33. Consumer Demand Curve

34. Producer Module

35. Computes desired capacity percentage using current price and operating cost. • Supply desired calculated as capacity percent times capacity. • Releases carbon equal to supply times carbon output rate. Energy Source Module

36. Environment Module

37. Infrastructure Module

38. Price Module

39. Computes a change percentage using supply and demand. • Calculated desired price using current price and percentage. • Changes price by the 1/delay of the difference between desired price and current price. Price Lambda

40. Simulator A Tool for Policy

41. Load pre-constructed models and plans. • Make edits to models and plans dynamically. • Save new models and plans for later use. • 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 • 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. Conclusion A Stepping Stone for Policy Decisions

50. 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