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

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. Introduction3 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

4. Introduction4 In Canada, utilization of renewable resources is less than 1 % (excluding hydroelectricity) Vast wind energy potential is mostly unexplored. Source: The Conference Board of CanadaSource: Natural Resources Canada

5. Introduction5 Emerging Technologies in Energy Engineering Wind and Solar energy technologies are the forerunners Hydrogen based energy conversion bears good potential Source: Worldwatch InstituteSource: Plug Power Inc., NY

6. Introduction6 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.

7. Introduction7 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

8. Introduction8 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

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. Pre-feasibility Study10 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.

11. Pre-feasibility Study11 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

12. Pre-feasibility Study12 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/m 2.

13. Pre-feasibility Study13 Components Wind turbine Solar array Fuel cell Diesel generator Electrolyzer Battery Power converter

14. Pre-feasibility Study14 Sensitivity Results At present, a wind/diesel/battery system is the most economic solution Solar energy in Newfoundland is not promising

15. Pre-feasibility Study15 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

16. Pre-feasibility Study16 Optimization Results Considering : wind speed = 6.64 m/s solar irradiation = 3.15 kWh/m 2 /d Diesel price = 0.35 $/L The optimum solutions are:

17. Pre-feasibility Study17 Wind-Fuel Cell System Optimization

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. Model Formulation19 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

20. Model Formulation20 Small WECS Power in the wind: Captured power: Power50 W ~ 10 KW Diameter1 ~ 7 m Hub-height~ 30 m Control/RegulationStall, Yaw, Pitch, Variable speed Over-speed ProtectionHorizontal/Vertical furling GeneratorDC, Permanent Magnet Alternator ApplicationStand-alone, Grid connections

21. Model Formulation21 Small WECS Model Formulation Wind Field Spatial Filter & Induction Lag PM DC Generator

22. Model Formulation22 Controller Design Control Problem I.Below rated wind speed: Extract maximum available power II.Near-rated wind speed:Maintain 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 I IIIII

23. Model Formulation23 Determination of Ref. Rotor Speed  Rotor torque is assumed available  Below rated reference rotor speed:  Near-rated conditions:  Over-rated reference rotor speed:

24. Model Formulation24 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)

25. Model Formulation25 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. Model Formulation26 Fuel Cell System  PEM fuel cell: Ballard MK5-E type  Empirical & physical expressions  Electrochemistry  Dynamic energy balance  Reactant flow  Air flow controller

27. Model Formulation27 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.

28. Model Formulation28 Fuel Cell Model Formulation Electrochemical Model  Cell voltage & Stack voltage:  Open circuit voltage:  Activation overvoltage:  Ohmic overvoltage

29. Model Formulation29 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

30. Model Formulation30 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

31. Model Formulation31 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. Model Formulation32 Electrolyzer  Alkaline Electrolyzer: PHOEBUS type  Empirical & physical expressions  Electrochemistry  Dynamic energy balance

33. Model Formulation33 Alkaline Electrolyzer  Aqueous KOH is used as electrolyte  Construction similar to fuel cell

34. Model Formulation34 Electrolyzer Model Formulation Electrochemical Model  Cell voltage:  Faraday efficiency:  Hydrogen production: Thermal Model

35. Model Formulation35 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

36. Model Formulation36 Power Converter Models  WECS Buck-Boost Converter  Inverter, Filter & R-L Load  Fuel Cell Boost Converter

37. Model Formulation37 System Integration Wind-fuel cell system interconnection Power flow control

38. 38 MATLAB-Simulink ® Simulation

39. Simulation39  Simulation time = 15 seconds  Constant temperature in fuel cell & electrolyzer assumed  Step changes in Wind speed Load resistance Hydrogen pressure Simulation

40. Results40 Results System response with random wind

41. Results41 WECS performance (step response)

42. Results42 Power balance (step response)

43. Results43 Fuel cell performance (step response)

44. Results44 Electrolyzer performance (step response)

45. Results45 Power converter performance (step response)

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. 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 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. 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 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. 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 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 Questions/Comments For your attention & presence