Fuzzy Controller of a Small Wind-Fuel Cell Hybrid Energy System

Fuzzy Controller of a Small Wind-Fuel Cell Hybrid Energy System

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

Renewable Resources • Wind Power Resources Allocation & Application in He’nan • Author: • [Lu Minghua /Kang Yan/ Liu Guoshun]

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 • 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 • Power converters and controllers are required to integrate the system

Model Formulation • Models Developed for: • Wind Turbine • PEM Fuel Cell • Electrolyzer • Power Converters • Approach: • 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:WG-150 (Jiujiang Device) • Wind field • PM DC generator • Controller • Reference speed generator • Fuzzy logic controller

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 Small WECS Power in the wind: Captured power:

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

Alkaline Electrolyzer • Aqueous KOH is used as electrolyte • Construction similar to fuel cell Model Formulation

Fuel Cell Model Formulation Electrochemical Model • Cell voltage & Stack voltage: • Open circuit voltage: • Activation overvoltage: • Ohmic overvoltage Model Formulation

Power Electronic Converters • Variable DC output of the Wind turbine/Fuel cell is interfaced with a 180 V DC bus • Load voltage: 220 V, 50Hz • Steady state modeling of DC-DC converters • Simplified inverter model coupled with LC filter 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) II III I

Design of Fuzzy Logic Controller The controller is a 2 input, 2 output fuzzy controller with 7 membership functions for the inputs, and 7 for the outputs.

Fuzzification • The 7 membership functions were assigned the linguistic labels of Positive Large, Positive Medium, Positive Small, Zero, Negative Small, Negative Medium, and Negative Large.

fuzzification.m • function [ fuzzy ] = fuzzification( data, rules ) • % Define linguistics • plarge = 1; • pmedium = 2; • psmall = 3; • zero = 4; • nsmall = 5; • nmedium = 6; • nlarge = 7; • if data >= rules( plarge ) • fuzzy = plarge; • elseif data >= rules( pmedium ) • fuzzy = pmedium; • elseif data > rules( zero ) • fuzzy = psmall; • elseif data == rules( zero ) • fuzzy = zero; • elseif data <= rules( nlarge ) • fuzzy = nlarge; • elseif data <= rules( nmedium ) • fuzzy = nmedium; • elseif data <= rules( nsmall ) • fuzzy = nsmall; • elseif data < rules( zero ) • fuzzy = nsmall; • end;

Fuzzy Rule-base • The rule-base was implemented with a two input, two output system. All the inputs use the same linguistic modifier’s of positive large (pl), positive medium (pm), positive small (ps), zero (z), negative small (ns), negative medium (nm), and negative large (nl). Based on the linguistics, 49 rules were established and outputs were chosen based on the desired output for the system.

Defuzzification • function [ crisp ] = fuzzification( data, rules ) • crisp = rules( data );

System Integration Wind-fuel cell system interconnection

MATLAB-Simulink® Simulation

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

Results System response with random wind

Fuel cell performance (step response)

Power converter performance (step response)

Summary • High settle 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

REFERENCES • http://www.fuelcell-magazine.com/eprints/free/johnsonmattheyapril03.pdf • http://www.ecn.nl/bct/solupor.en.html • http://www.efcf.com/reports/E04.pdf • http://www.gatech.edu/news-room/release.php?id=618

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Fuzzy Controller of a Small Wind-Fuel Cell Hybrid Energy System