tomorrow’s energy today

{

Tomorrow’s Energy Today

Final presentation - COMP 410 F12

{Electrons run our lives.

Motivation

???

Availability Sustainabili

ty Affordability

{A Tool for the Future

Introduction

{ {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?

{ {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

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

Verify the plan produces desired results on simulator

Make the plan and results readily available to the public to verify and edit

Problem Statement

I. Model of the US Energy Industry

II. Best-case, average-case, and worst-case 50-year plans for the energy industry

III. SimulatorI. Public Web InterfaceII. Cloud StorageIII. General Purpose Modeling

Specification

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

{Average, Best, and Worst Cases

Plan for the Future

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

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 the same.

Average Case Average peak

demand increases. Best Case

Average peak demand decreases.

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

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%

{Representing an intertwined system.

Energy Model

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

Model Cont.

Add

Function

Sub

MultAdd

Module

Model

Add3

5

8

“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

{ {Extensibility

Quickly and easily break down simple stocks/flows into more complex ones.

Comparability

Determine differences in functionality between different models.

SD Advantages

{

Five Modules Consumer Producer Infrastructure Environment Price

Our Model

Consumer Module

Consumer Demand Curve

Producer Module

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

Environment Module

Infrastructure Module

Price Module

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

{A Tool for Policy

Simulator

• 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

{(Look at the other screen! )

Demonstration

Architecture

The two main Design decisions:

• ASP.NET MVC4

• JsPlumb

User Interface Architecture

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

Network Architecture

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

Model Architecture

{A Stepping Stone for Policy Decisions

Conclusion

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

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

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

Thank you!

Q & A