Green Energy Hub

Alan Thai, Jake Yeung, Arthur Yip

Walmart Green Student Challenge

A Novel Design to Address Energy Needs

Agenda

• Challenges

• Energy Hub Concept

• Design

• Financial Analysis

• Environmental Benefits

2

Growth in Renewables

3

Fluctuating Electricity Price

• March 2012 Average Price: $15/MWh

• 9 AM, March 11, 2012: -$128/MWh

4

Electric Grid Overload

Excess Supply

Electric Grid Instability

5

Energy Hub Design

Green

Energy Hub

• 100% Renewable Electricity

• Clean On-Site Fuel

6

$$$

• Improved Grid Stability

Green

Energy Hub H2

Inside an Energy Hub

7

Grid

Photovoltaics

Turbines LEDs

Chillers

H2

Electrolyzer Forklift Fuel

Solar

Wind Lighting

Refrigeration

Grid

Connection

Walmart’s Interest in Our Idea

8

Financial Incentives

• Ontario Feed-In Tariff (FIT): $135/MWh for

wind, $530/MWh for solar

• Grid Services worth up to $100 000/yr per

MW of load flexibility

• Savings from on-site hydrogen production

9

Methodology

• Technology Screening

• Modeling and Simulation

• Optimization of Design Parameters

• Financial and Environmental Analysis

Green Energy Hub Design

H2

Legend Ball

Valve

Check Valve

Pressure

Safety Valve

Vent

H2 Fueling Station

Distribution Centre

Electrolyzer

Electricity

H2

350 bar

Compressor

Wind

Solar

Grid

Hydrogen System

H2O

MATLAB Simulation

Loop for all hours in a year

Wind and solar data

Timescales:

All hours

All months

All seasons

Building load,

assuming no peak shifting

MATLAB Simulation

Horizontal-axis wind turbines Thin-film CdTe solar panels Alkaline electrolyzer

Seasonal Variation

Summer

6AM 12PM 6PM

-2000

-1000

0

1000

2000

3000

Time

Po

we

r (k

W)

6:00 12:00 18:00

3000

1000

-1000

2000

0

-2000

Time of Day Time of Day

Winter

6AM 12PM 6PM

-2000

-1000

0

1000

2000

3000

Hour of the day

Po

we

r (k

W)

6:00 12:00 18:00

3000

1000

-1000

2000

0

-2000

Pow

er

(kW

)

Energy Hub Response to Spikes

6AM 12PM 6PM

-2000

-1000

0

1000

2000

3000

Time

Po

we

r (k

W)

6:00 12:00 18:00

3000

1000

-1000

2000

0

-2000

6AM 12PM 6PM

-2000

-1000

0

1000

2000

3000

Time

Po

we

r (k

W)

Wind and Solar Power Spikes

Smoothing Fluctuations

6:00 12:00 18:00 Time of Day

3000

1000

-1000

2000

0

-2000

Pow

er

(kW

)

Optimization of Wind and Solar

Identification of optimal combination of wind and solar power to meet the goal of net 100% renewable power

Capacity (MW) Net Renewable (% of load)

Net Grid Reliance (% of load) Solar Wind

3 9 87% 30%

3 10.5 95% 28%

4 9 100% 28%

4 10.5 108% 25%

Optimization of Electrolyzer

Identification of optimum size of electrolyzer by potential value of savings from on-site H2 and revenue from grid service

Electrolyzer Model

Capacity (kW)

Capital Cost (CAD$)

Annual Return (CAD$)

IRR (%)

HySTAT-45 235 $ 800,000 $ 195,000 32%

HySTAT-60 312 $ 900,000 $ 216,000 32%

2 x HySTAT-45 470 $ 1,200,000 $ 260,000 27%

2 x HySTAT-60 624 $ 1,400,000 $ 303,000 27%

Final Design Specifications

18

Grid

Photovoltaics

Turbines LEDs

Chillers

Electrolyzer Forklift Fuel

Solar

Wind Lighting

Refrigeration

Grid

Connection

6 x 1.5 MW

4 MW

HySTAT-60

312 kW

Financial Analysis

Solar FIT Contract, $3.10 M

Wind FIT Contract, $1.33 M

Hydrogen System, $1.32 M

Grid Services, $1.27 M

0

50

100

150

0 5 10 15 20

$ M

illi

on

s (

CA

D)

Project lifetime (years)

Break-Even Analysis

Environmental Benefits

21

State-of-the-Art Facility

Green Energy

Hub 0

500

1000

1500

An

nu

al C

O2 E

mis

sio

ns

(to

nn

es C

O2/y

r)

CO₂ from Hydrogen Production

CO₂ from Building Operations

22

71% CO2

Reduction

Investing in the Future

Leadership in Energy

Green Energy Hub

Integration of technologies to address energy holistically

Future Work

• Investigation into alternative uses of spare hydrogen

capacity, including stationary fuel cell power, fuel

cell vehicles, and industrial usage of H2, O2, and

waste heat

• Detailed control system design to collect and

redistribute power depending on weather, price

signals, and operational needs

• Stochastic optimization of parameters to minimize

cost and maximize benefits such as environmental

impact reduction

23

Acknowledgements

• Kevin Brant

• Michel Archambault

• Greg Ponesse

• Dr. Michael Fowler

• Faraz Syed

• Dr. Marc Aucoin 24

25