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

1. 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 • Most of the commercially available electrolyzers run in current mode, according to a polarization characteristic. This characteristic can be represented as a sum of linear, logarithmic and exponential functions 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 • The PV cell are described by the I-V characteristics which equations are : 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