I R H Simulink Modelling and Simulation of a Hydrogen Based Photovoltaic/Wind Energy System Mamadou Lamine Doumbia, Kodjo Agbossou, and Évelyne Granger Hydrogen Research Institute Department of Electrical and Computer Engineering Université du Québec à Trois-Rivières, C.P boul. des Forges Trois-Rivières (Québec) Canada G9A 5H7 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. Université du Québec à Trois-Rivières Institut de recherche sur l’hydrogène 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. PV Array BUS DC, BATTERY BANK & POWER CONVERTERS Electrolyzer Compressor H2 Tank PEMFC Wind Turbine Electric Grid /Grid Simulator AC Loads Critical Loads Grid Connected Inverter Fig.1 Renewable energy system with hydrogen storage II.PHOTOVOLTAIC ARRAY MODEL The PV cell are described by the I-V characteristics which equations are : I L = photogenerated current (A) I 0 = diode saturation current (A) q = electronic charge (C) V = solar cell terminal voltage (V) R S = cell series resistance (  ) n = diode quality factor k = Boltzmann’s constant (J/K) T = ambient temperature (K) G = cell irradiance W/m² G nom = rated cell irradiance (W/m²) T = solar cell temperature (K) T 1, T 2 = two reference temperatures (K) I SC(T1) = short circuit current at temp. T 1 (A) I SC(T2) = short circuit current at temp. T 2 (A) 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. Fig.2 Power versus wind speed plot for the Bergey BWC Excel 10 kW wind turbine IV.BATTERY MODEL The battery model presents the relation between voltage, current and the battery state of charge Q. Two modes of operation are considered: Discharge mode (I<0): Charge mode (I>0): I= battery current (A); V= battery voltage (V); C= battery capacity (Ah); Q=state of charge; 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.ELECTROLYZER MODEL 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 E o = reversible potential (V); I= current (A); T= temperature (°C); b,m,R = coefficients that depend on temperature; n = constant. E 0 (T) = – *T; R(T) = *T– ; b(T) = 3.374–0.0194*T For the Stuart Compagny’s electrolyzer at the HRI, the following polarization curve was found from the experimental data: In the model, the temperature variation was found from the dissipated (heat) power: P tot = Total power consumed by the electrolyzer (W) P H2 = Power consumed to produce hydrogen (W) MC = thermal capacity of the electrolyzer (J/K) hA= thermal transfer coefficient (W/K) T élec = electrolyzer temperature (K) T amb = ambient temperature (K) VI.FUEL CELL MODEL This curve can be represented by a sum of linear, logarithmic and exponential functions: E o = 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: P tot = Total power consumed by the fuel cell (W); P élec = Electric power produced by the fuel cell (W) MC = thermal capacity of the fuel cell (J/K); hA= thermal transfer coefficient (W/K) T pile = fuel cell temperature (K); T amb = ambient temperature (K) ; ; VII.SIMULATION RESULTS Fig. 4 Results for July Month Wind turbine and photovoltaic array power Wind speed, temperature and irradiance State of charge, electrolyzer power and fuel cell power Fig.3 Results for January Month Wind turbine and photovoltaic array power Wind speed, temperature and irradiance State of charge, electrolyzer power and fuel cell power This work has been supported by the Natural Sciences and Engineering Research Council of Canada and the LTE Hydro-Québec, P w = power extracted from the wind (W) = air density (kg/m 3 ) R= blades radius (m) C p = power (performance) coefficient = tip speed ratio  = pitch angle of the rotor blades (°) v= wind speed (m/s) The complete system’s model is developed and simulated using Matlab/Simulink software.