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Simulink Modelling and Simulation of a Hydrogen Based Photovoltaic/Wind Energy System PowerPoint Presentation

Simulink Modelling and Simulation of a Hydrogen Based Photovoltaic/Wind Energy System

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Simulink Modelling and Simulation of a Hydrogen Based Photovoltaic/Wind Energy System

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Simulink Modelling and Simulation of a Hydrogen Based Photovoltaic/Wind Energy System

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I

Critical Loads

PV Array

R

Grid Connected Inverter

Wind Turbine

H

BUS DC, BATTERY BANK & POWER CONVERTERS

Electric Grid /Grid Simulator

AC Loads

Compressor

PEMFC

H2 Tank

Electrolyzer

Fig.1 Renewable energy system with hydrogen storage

Pw= power extracted from the wind (W)

= air density (kg/m3)

R= blades radius (m)

Cp= power (performance) coefficient

= tip speed ratio

= pitch angle of the rotor blades (°)

v= wind speed (m/s)

Simulink Modelling and Simulation of a Hydrogen Based Photovoltaic/Wind Energy System

Mamadou Lamine Doumbia, Kodjo Agbossou, and Évelyne Granger

Université du Québec à Trois-Rivières

Hydrogen Research Institute

Department of Electrical and Computer Engineering

Université du Québec à Trois-Rivières, C.P. 5003351 boul. des Forges Trois-Rivières (Québec) Canada G9A 5H7

Institut de recherche sur l’hydrogène

ABSTRACT– This paper presents a dynamic simulation model using Matlab/Simulink software to study the behavior of renewable energy systems with hydrogen storage (RESHS). The complete system model is developed by integrating individual sub-units of the photovoltaic arrays, wind turbine, batteries, electrolyzer, fuel cell and power conditioning units. The sub-models are valid for transient and steady state analysis as a function of voltage, current, and temperature. Such a global model is useful for optimal dimensioning and effective control design of the RESHSs. The state of charge control method was chosen to validate the developed simulation models. The results confirmed previous experimental measurements on the test bench.

IV.BATTERYMODEL

The battery model presents the relation between voltage, current and the battery state of charge Q.Two modes of operation are considered:

I.INTRODUCTION

For many years, the Hydrogen Research Institute (HRI) has developed a renewable photovoltaic/wind energy system based on hydrogen storage (Fig. 1). This system operates using state-of-charge (SOC) control method. The control system verifies the state of charge of the batteries and sends commands to the electrolyzer or the fuel cell via DC/DC converters to manage energy production/consumption in the system. In order to obtain more efficient control of the entire system, and particularly in order to be able to study how it should be connected to the electrical grid, the development of a general simulation model was undertaken. The main components (photovoltaic array, wind turbine, electrolyzer and fuel cell) of the system were each modelled and simulated, and then integrated into a global simulation model designed to function like the real system.Matlab/Simulink software was used for this purpose.

Discharge mode (I<0):

Charge mode (I>0):

I= battery current (A); V= battery voltage (V); C= battery capacity (Ah); Q=state ofcharge; T= time (h); R= internal resistance (Ω); M, g= coefficients.

In our model, the coefficients g, R, C and M are expressed as a function of the battery age.

- V.ELECTROLYZERMODEL

Eo= reversible potential (V); I= current (A); T= temperature (°C); b,m,R = coefficients that depend on temperature; n = constant.

For the Stuart Compagny’s electrolyzer at the HRI, the following polarization curve was found from the experimental data:

E0(T) = 32.5628–0.00677*T; R(T) = 0.0002089*T–0.00955; b(T) = 3.374–0.0194*T

- II.PHOTOVOLTAIC ARRAY MODEL

In the model, the temperature variation was found from the dissipated (heat) power:

Ptot= Total power consumed by the electrolyzer (W)

PH2= Power consumed to produce hydrogen (W)

MC = thermal capacity of the electrolyzer (J/K)

hA= thermal transfer coefficient (W/K)

Télec = electrolyzer temperature (K)

Tamb = ambienttemperature (K)

IL = photogenerated current (A)

I0= diode saturation current (A)

q = electronic charge (C)

V = solar cell terminal voltage (V)

RS = cell series resistance ()

n = diode quality factor

k = Boltzmann’s constant (J/K)

T = ambient temperature (K)

VI.FUEL CELL MODEL

This curve can be represented by a sum of linear, logarithmic and exponential functions:

;

G = cell irradiance W/m²

Gnom= rated cell irradiance (W/m²)

T = solar cell temperature (K)

T1, T2= two reference temperatures (K)

ISC(T1)= short circuit current at temp. T1 (A)

ISC(T2)= short circuit current at temp. T2 (A)

Eo= reversible potential (V); I = current (A); T= temperature (°C); n = constant;

b, R,m = coefficients that depend on the temperature.

In the model, the temperature variation was found from the dissipated (heat) power:

;

Ptot= Total power consumed by the fuel cell (W); Pélec= Electric power produced by the fuel cell (W)

MC = thermal capacity of the fuel cell (J/K); hA= thermal transfer coefficient (W/K)

Tpile = fuel cell temperature (K); Tamb = ambienttemperature (K)

III.WIND TURBINE MODEL

The wind turbine power can be calculated by the following equation.An algebraic relation between wind speed and mechanical power extracted is assumed.

VII.SIMULATION RESULTS

The complete system’s model is developed and simulated using Matlab/Simulink software.

Wind speed, temperature and irradiance

Wind turbine and photovoltaic array power

State of charge, electrolyzer power and fuel cell power

Fig.3 Results for January Month

Fig.2 Power versus wind speed plot for the Bergey BWC Excel 10 kW wind turbine

This work has been supported by the Natural Sciences and Engineering Research Council of Canada and the LTE Hydro-Québec,

Wind turbine and photovoltaic array power

Wind speed, temperature and irradiance

State of charge, electrolyzer power and fuel cell power

Fig. 4 Results for July Month