Abstract
The concept of power tracking was at first applied to renewable power systems and especially those based on solar and wind to extract as much power as possible from them. Both types of power systems operate on the principle of converting either solar or wind into electricity. Thus, their output power is direct dependent on the solar radiation for solar power systems and on the wind speed for wind generators. To maintain efficient system operations, the output power of these power systems is optimized through maximum power tracking techniques. In the similar vein, fuel cell stacks display nonlinear output powers resulting from internal limitations and operating parameters such as tem-perature, hydrogen and oxygen partial pressures and humidity levels, etc., leading to a reduced system performance. It is critical to extract as much power as possible from the stack, thus, to prevent also an excessive fuel use. To ensure that, the power converter interfaced to the stack must be able to self-adjust its parameters continuously, hence modifying its voltage and current depending upon the maximum power point position. Diverse techniques are utilized to extract maximum power from the fuel-cell stack. In this paper, a fractional open circuit voltage and fuzzy rule based maximum power tracking techniques are considered and compared. The proposed system consists of a 50 kW Proton Exchange Membrane fuel cell interfaced to a DC-to-DC boost converter. The converter is designed to deliver 1.2 kV from 625 V input voltage. The simulation is carried out under Matlab/Simulink environment.
Highlights
Fuel cells (FCs) are expected to play a key role in the current and future power system model as they are potential candidates to replace fossil fuel-based power generators for clean electricity production
A switch mode power converter known as maximum power point tracker (MPPT) is interfaced between the FC and the load and operates such that the converter’s duty cycle is adjusted continuously, modifying the voltage and current depending upon the maximum power point position
This paper investigates two MPPT controllers; one based on Fuzzy inference system using Sugeno method and another one is adapted from Fractional Open Circuit Voltage technique, the objective is to compare both controllers’ performances in terms of their response characteristics
Summary
Fuel cells (FCs) are expected to play a key role in the current and future power system model as they are potential candidates to replace fossil fuel-based power generators for clean electricity production. Their operation is such that chemical energy from an electrolytic reaction is continuously converted into electricity in the form of direct current with water and heat as by-products [3]. In this electrolytic reaction, hydrogen serves as the main fuel or reactant while oxygen is the oxidant. It is critical to extract as much power as possible from the stack as at all the operating conditions, there is only one maximum power point in the power versus current (P-I) FC curve This allows preventing an excessive fuel use and avoiding low system efficiency.
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