1. Dynamic Modeling, Simulation and Control of a
Small Wind-Fuel Cell Hybrid Energy System for
Graduate Student Seminar : Master of Engineering
1
Stand-Alone Applications
June 29, 2004
Mohammad Jahangir Khan
mjakhan@engr.mun.ca
Faculty of Engineering & Applied Science
Electrical Engineering

2. 2
Outline
 Introduction
• Renewable Energy, Hybrid & Stand-alone Power
Sources
• Emerging Technologies, Scope of Research
 Pre-feasibility Study
• Load, Resource, Technology Options
• Sensitivity & Optimization Results
 Model Formulation
• Wind Energy Conversion System, Fuel Cell System,
Electrolyzer, Power Converter
• System Integration
 Simulation
 Results
• Random Wind Variation
• Step Response
 Conclusion

3. Canada and the Global Energy Scenario
• At present, proportion of renewable energy in the global
energy mix is about 14 % only.
• Various environmental regulations and protocols aim at
increasing this ratio towards 50% by 2050.
Source: German Advisory Council on Global Change
Introduction 3

4. • In Canada, utilization of renewable resources is less than 1 %
(excluding hydroelectricity)
• Vast wind energy potential is mostly unexplored.
Source: The Conference Board of Canada Source: Natural Resources Canada
Introduction 4

5. Emerging Technologies in Energy Engineering
• Wind and Solar energy technologies are the forerunners
• Hydrogen based energy conversion bears good potential
Source: Worldwatch Institute Source: Plug Power Inc., NY
Introduction 5

6. Hybrid Energy Systems
in Stand-alone Applications
• Energy from a renewable source depends on environmental
Introduction 6
conditions
• In a Hybrid Energy System, a renewable source is combined with
energy storage and secondary power source(s).
• Mostly used in off-grid/remote applications
• Could be tied with a distributed power generation network.

7. Wind-Fuel Cell Hybrid Energy System
• A wind turbine works as a primary power source
• Availability of wind energy is of intermittent nature
• Excess energy could be used for hydrogen production by an
Introduction 7
electrolyzer
• During low winds, a fuel-cell delivers the electrical energy using
the stored hydrogen
• Radiated heat could be used for space heating
• Power converters and controllers are required to integrate the
system

8. Scope of Research
 Q1. Is a wind-fuel cell hybrid energy system feasible for a
given set of conditions?
• Pre-feasibility Study
• Site: St. John’s, Newfoundland.
 Q2. What are the alternatives for building and testing a
HES, provided component cost is very high and
technology risk is substantial?
• Computer aided modeling
• System integration and performance analysis through
Introduction 8
simulation

9. 9
Pre-feasibility Study
Investigation of technology options,
configurations and economics using:
• Electrical load profile
• Availability of renewable resources
• Cost of components (capital, O&M)
• Technology alternatives
• Economics & constraints
• HOMER (optimization software)

10. HOMER Implementation
• St. John’s, Newfoundland
• Renewable (wind/solar) & non-renewable
(Diesel generator) sources
• Conventional (Battery) & non-conventional
(Hydrogen) energy
Pre-feasibility Study 10
storage
• Sensitivity analysis with wind data,
solar irradiation, fuel cell cost & diesel
price.

11. Electrical Load
• A typical grid connected home may consume around
50 kWh/d (peak 15 kW)
• A HES is not suitable for such a large load
• Off-grid/remote homes should be designed with
energy conservation measures
• A house with 25 kWh/d (4.73 kW peak) is considered
• Actual data is scaled down
Source: Newfoundland Hydro
Pre-feasibility Study 11

12. Renewable Resources
• Hourly wind data for one year at
Pre-feasibility Study 12
St. John’s Airport.
• Average wind speed in St.
John’s is around 6.64 m/s.
• Hourly solar data for one year at
St. John’s Airport.
• Average solar irradiation in St.
John’s is around 3.15 kWh/d/m2.

13. Pre-feasibility Study 13
Components
• Wind turbine
• Solar array
• Fuel cell
• Diesel generator
• Electrolyzer
• Battery
• Power converter

14. Sensitivity Results
• At present, a wind/diesel/battery system is the most economic
Pre-feasibility Study 14
solution
• Solar energy in Newfoundland is not promising

15. • A wind/fuel cell/diesel/battery system would be feasible if the
fuel cell cost drops around 65%.
• A wind/fuel cell HES would be cost-effective if the fuel cell cost
decreases to 15% of its present value
Pre-feasibility Study 15

16. Optimization Results
Considering :
• wind speed = 6.64 m/s
• solar irradiation = 3.15 kWh/m2/d
• Diesel price = 0.35 $/L
The optimum solutions are:
Pre-feasibility Study 16

17. Wind-Fuel Cell System Optimization
Pre-feasibility Study 17

18. 18
Model Formulation
Models Developed for:
• Wind Turbine (7.5 kW): Bergey Excel-R
• PEM Fuel Cell (3.5 kW): Ballard MK5-E type
• Electrolyzer (7.5 kW): PHOEUBS type
• Power Converters (3.5 kW)
Approach:
• Empirical & physical relationships used
• Components are integrated into a complete
system through control and power electronic
interfaces
• Simulation done in MATLAB-Simulink®

19. Wind Energy Conversion System (WECS)
 Small wind turbine: BWC Excel-R type
 Wind field
 Rotor aerodynamics
Model Formulation 19
• Spatial Filter
• Induction Lag
 PM DC generator
 Controller
• Reference speed generator
• Fuzzy logic controller

20. P = 1 r
P = C 1 r
Model Formulation 20
Small WECS
Power in the wind:
Captured power:
3
wind wt wind A V
2
3
a p wt eff A V
2
Power 50 W ~ 10 KW
Diameter 1 ~ 7 m
Hub-height ~ 30 m
Control/Regulation Stall, Yaw, Pitch, Variable speed
Over-speed Protection Horizontal/Vertical furling
Generator DC, Permanent Magnet Alternator
Application Stand-alone, Grid connections

21. Small WECS Model Formulation
Wind Field
V = V +
V
wind turb avg
V m ( t )
T
= 0.43795s +
1.4142
0.1918s 1.1598s 1.4142
eff
V
dI
V = E - L -
t _ wt a a R I
T T J d r
a l = + +
Model Formulation 21
dV
V
V
2
filt
wind
+ +
1
dt
turb wind
v
turb
= - +
Spatial Filter & Induction Lag
t
1
1
a s 1
i
filt
+
s 1
V
t
+
=
l a r T = kfI
w f a r E = k
a a
a
dt
w Bw
dt
PM DC Generator

22. Controller Design
Control Problem
I. Below rated wind speed: Extract
maximum available power
II. Near-rated wind speed:Maintain
I II III
Model Formulation 22
constant rated power
III. Over-rated wind speed : Decrease
rotor speed (shut-down)
Control method
 A PD-type fuzzy logic controller (FLC) is employ
 Reference rotor speed is estimated from rotor torque
 Difference in actual & ref. Speed is used to control the dump load

23. Determination of Ref. Rotor Speed
 Rotor torque is assumed available
 Below rated reference rotor speed:
Model Formulation 23
w = T =
ref k T
w a
'
a
T
k
 Near-rated conditions:
'
wref =wro
 Over-rated reference rotor speed:
P
a
max
T '
wref =

24. Design of Fuzzy Logic Controller
A PD type FLC is used for the whole range of wind variation
Variable Identification: Error & Rate of change of error
Fuzzification: Five Gaussian membership functions for all variables
Rules of inference: Fuzzy Associative Memory
Defuzzification: Centroid method (Mamdani)
Model Formulation 24

25. Model Formulation 25
Summary
 Dynamic model of a Small wind turbine (BWC Excel-R type)
 Wind field, Rotor aerodynamics, PM DC generator
 Controller (Reference speed generator, Fuzzy logic controller)
 Mechanical sensorless control (rotor torque assumed
estimable)

26. Fuel Cell System
 PEM fuel cell: Ballard MK5-E type
 Empirical & physical expressions
 Electrochemistry
 Dynamic energy balance
 Reactant flow
 Air flow controller
Model Formulation 26

27. PEM Fuel Cells
 Polymer membrane is sandwiched
between two electrodes,
containing a gas diffusion layer
(GDL) and a thin catalyst layer.
 The membrane-electrode assembly
(MEA) is pressed by two
conductive plates containing
channels to allow reactant flow.
H2
H2
H2
O2
O2
O2
2e- Load
Positive Ion
Negative Ion
Model Formulation 27
Conductive plates
Flow channels
Gas diffusion layer
Catalyst later
Electrolyte
Electric load
Anode Cathode
FuelI In
H2
H2O
1/2O2
H2O
Electrolyte
Oxidant in
Depleted Fuel Depleted oxidant

28. Fuel Cell Model Formulation
Electrochemical Model
 Cell voltage & Stack voltage:
cell Nernst act ohmic V = E +h +h
RT
Model Formulation 28
stack fc cell V = N V
 Open circuit voltage:
 Activation overvoltage:
act act V = -h
- V
act
I
=
dV
act fc
 Ohmic overvoltage
ENernst
Ract
Rint
Cdl
+
Vcell
-
Ifc
act dl
dl
R C
C
dt
ohmic fc int h = -I R
[ '
O
( ) 0 . 5 ] H
'fc
fc
-3
Nernst 2 2 ln p p
2F
E =1.229 - 8.5×10 (T -298.15 )+

29. Reactant Flow Model
 Performance depends on oxygen,
hydrogen & vapor pressure
 Anode & Cathode flow models
determine reactant pressures
 Ideal gas law equations and principles
of mole conservation are employed
= m -m ± I
nF
Model Formulation 29
dP
dt
V
RT
out
•
in
g •
•
mout = k(Pg - Pamb )

30. Thermal Model
 Fuel cell voltage depends on stack temperature
 Stack temperature depends on load current, cooling, etc.
 Total power (from hydrogen) =
Electrical output + Cooling + Surface Loss + Stack Heating
 A first order model based on stack heat capacity is used
Total power
Surface heat loss
Cooling system
heat removal
C - - -
Model Formulation 30
Electric power
Stack heating
stack_ fc
•
'
fc
dT
t _ fc = Q
dt
C
loss _ fc
•
cool _ fc
•
tot _ fc fc
'
fc
dT
t _ fc = P P Q Q
dt

31. Model Formulation 31
Summary
 Dynamic model of a PEM fuel cell (Ballard MK5-E type)
 Electrochemical, thermal and reactant flow dynamics
included
 Model shows good match with test results

32. Electrolyzer
 Alkaline Electrolyzer: PHOEBUS type
 Empirical & physical expressions
 Electrochemistry
 Dynamic energy balance
Model Formulation 32

33. Alkaline Electrolyzer
 Aqueous KOH is used as electrolyte
 Construction similar to fuel cell
Model Formulation 33

34. Electrolyzer Model Formulation
Electrochemical Model
 Cell voltage:
ö
æ
U U r r T I s log t t / T t / T
elz
•
Q = Q + Q + Q
Model Formulation 34
1 2 elz
 Faraday efficiency:
I / A
+
F f
 Hydrogen production:
n N 2 =h
H F I
Thermal Model
÷ ÷ø
ç çè
+
+ +
+
+
= + I 1
A
A
elz
2
1 2 elz 3 elz
elz
elz
cell rev
( )
2
elz elz
( )2 2
1 elz elz
f I / A
h =
elz
elz
zF
·
stack_ elz
•
dT
elz
= Q
t _ elz dt
C
loss _ elz
•
cool _ elz
•
stack_ elz
•
gen _ elz

35. Power Electronic Converters
• Variable DC output of the Wind turbine/Fuel cell is
interfaced with a 200 V DC bus
• Load voltage: 120 V, 60Hz
• Steady state modeling of DC-DC converters
• Simplified inverter model coupled with LC filter
• PID controllers used
Model Formulation 35

36. Power Converter Models
 WECS Buck-Boost Converter
V
bus
D
 Inverter, Filter & R-L Load
 Fuel Cell Boost Converter
V
bus
1
1 D
Model Formulation 36
wt
wt
t _ wt
1 D
V
-
=
stack fc
V
-
=

37. Load
Power
Wind Power-Load Power
N Y
Model Formulation 37
System Integration
Start
Wind
Power
Positive
Excess
Power
Electrolzyer
Deficit
Power
Fuel Cell
End
Wind-fuel cell system interconnection
Power flow control

38. 38
MATLAB-Simulink® Simulation

39.  Simulation time = 15 seconds
 Constant temperature in fuel cell & electrolyzer assumed
 Step changes in
• Wind speed
• Load resistance
• Hydrogen pressure
Simulation 39
Simulation

40. Results System response with random wind
Results 40

41. WECS performance (step response)
Results 41

42. Power balance (step response)
Results 42

43. Fuel cell performance (step response)
Results 43

44. Electrolyzer performance (step response)
Results 44

45. Power converter performance (step response)
Results 45

46. 46
Summary
 Highest settling time for the wind turbine
 Controlled operation of the wind turbine, fuel cell,
electrolyzer and power converter found to be satisfactory
 Coordination of power flow within the system achieved

47. Contributions
 For a stand-alone residential load in St. John’s, consuming 25
kWh/d (4.73 kW peak) a pre-feasibility study is carried out.
 A mathematical model of wind-fuel cell energy system is
developed, simulated and presented. The wind turbine model
employs a concept of mechanical sensorless FLC.
 The PEM fuel cell model unifies the electrochemical, thermal and
47
reactant flow dynamics.
 A number of papers generated through this work. Explored fields
include:
• Wind resource assessment
• Fuel cell modeling
• Grid connected fuel cell systems
• Small wind turbine modeling

48. Conclusions
 A wind-fuel cell hybrid energy system would be cost
effective if the fuel cell cost reduces to 15% of its current
price. Cost of energy for such a system would be around
$0.427/kWh.
 Performance of the system components and control
48
methods were found to be satisfactory.
 Improvement in relevant technologies and reduction in
component cost are the key to success of alternative
energy solutions.

49. Further Work
 Development of a faster model for investigating variations in
system temperature and observing long term performance (daily-yearly).
 Inclusion of various auxiliary devices into the fuel cell and
49
electrolyzer system.
 Use of stand-by batteries
 Research into newer technologies such as, low speed wind
turbines, reversible fuel cell etc.
 Comprehensive study of relevant power electronics and controls

50. 50
Acknowledgement
 Faculty of Engineering & Applied Science, MUN.
 School of Graduate Studies, MUN.
 NSERC
 Environment Canada
 Dr. M. T. Iqbal.
 Drs. Quaicoe, Jeyasurya, Masek, and Rahman.
Thank You
For your attention & presence
Questions/Comments