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Dynamic Modeling, Simulation and Control of a Small Wind-Fuel Cell Hybrid Energy System for Stand-Alone Applications. Mohammad Jahangir Khan Faculty of Engineering & Applied Science Electrical Engineering. G raduate Student Seminar : Master of Engineering

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Dynamic Modeling, Simulation and Control of a Small Wind-Fuel Cell Hybrid Energy System for Stand-Alone Applications

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Dynamic Modeling, Simulation and Control of a Small Wind-Fuel Cell Hybrid Energy System for Stand-Alone Applications

Mohammad Jahangir Khan

Faculty of Engineering & Applied Science

Electrical Engineering

Graduate Student Seminar : Master of Engineering

June 29, 2004

  • 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
canada and the global energy scenario
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



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



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



Hybrid Energy Systems

in Stand-alone Applications

  • Energy from a renewable source depends on environmental 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.



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 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



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 simulation



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)

HOMER Implementation

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

Pre-feasibility Study


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


Renewable Resources

  • Hourly wind data for one year at 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.

Pre-feasibility Study



  • Wind turbine
  • Solar array
  • Fuel cell
  • Diesel generator
  • Electrolyzer
  • Battery
  • Power converter

Pre-feasibility Study


Sensitivity Results

  • At present, a wind/diesel/battery system is the most economic solution
  • Solar energy in Newfoundland is not promising

Pre-feasibility Study


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


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


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®

Wind Energy Conversion System (WECS)

  • Small wind turbine: BWC Excel-R type
  • Wind field
  • Rotor aerodynamics
    • Spatial Filter
    • Induction Lag
  • PM DC generator
  • Controller
    • Reference speed generator
    • Fuzzy logic controller

Model Formulation



50 W ~ 10 KW


1 ~ 7 m


~ 30 m


Stall, Yaw, Pitch, Variable speed

Over-speed Protection

Horizontal/Vertical furling


DC, Permanent Magnet Alternator


Stand-alone, Grid connections

Small WECS

Power in the wind:

Captured power:

Model Formulation


Small WECS Model Formulation

Wind Field

Spatial Filter & Induction Lag

PM DC Generator

Model Formulation


Controller Design

  • Control Problem
  • Below rated wind speed:Extract maximum available power
  • Near-rated wind speed:Maintain constant rated power
  • 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

Model Formulation


Determination of Ref. Rotor Speed

  • Rotor torque is assumed available
  • Below rated reference rotor speed:
  • Near-rated conditions:
  • Over-rated reference rotor speed:

Model Formulation


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



  • 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)

Model Formulation


Fuel Cell System

  • PEM fuel cell: Ballard MK5-E type
  • Empirical & physical expressions
  • Electrochemistry
  • Dynamic energy balance
  • Reactant flow
  • Air flow controller

Model Formulation


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.

Model Formulation


Fuel Cell Model Formulation

Electrochemical Model

  • Cell voltage & Stack voltage:
  • Open circuit voltage:
  • Activation overvoltage:
  • Ohmic overvoltage

Model Formulation


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

Model Formulation


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

Model Formulation



  • 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

Model Formulation



  • Alkaline Electrolyzer: PHOEBUS type
  • Empirical & physical expressions
  • Electrochemistry
  • Dynamic energy balance

Model Formulation


Alkaline Electrolyzer

  • Aqueous KOH is used as electrolyte
  • Construction similar to fuel cell

Model Formulation


Electrolyzer Model Formulation

Electrochemical Model

  • Cell voltage:
  • Faraday efficiency:
  • Hydrogen production:

Thermal Model

Model Formulation


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


Power Converter Models

  • WECS Buck-Boost Converter
  • Inverter, Filter & R-L Load
  • Fuel Cell Boost Converter

Model Formulation


System Integration

Power flow control

Wind-fuel cell system interconnection

Model Formulation



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




System response with random wind




  • 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


  • 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 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


  • 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 methods were found to be satisfactory.
  • Improvement in relevant technologies and reduction in component cost are the key to success of alternative energy solutions.

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 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


  • Faculty of Engineering & Applied Science, MUN.
  • School of Graduate Studies, MUN.
  • Environment Canada
  • Dr. M. T. Iqbal.
  • Drs. Quaicoe, Jeyasurya, Masek, and Rahman.

Thank You

For your attention & presence