A maximum power point tracking for photovoltaic-SPE system using a maximum current controller

Processes to produce hydrogen from solar photovoltaic (PV)-powered water electrolysis using solid polymer electrolysis (SPE) are reported. An alternative control of maximum power point tracking (MPPT) in the PV-SPE system based on the maximum current searching methods has been designed and implemented.Based on the characteristics of voltage–current and theoretical analysis of SPE, it can be shown that the tracking of the maximum current output of DC–DC converter in SPE side will track the MPPT of photovoltaic panel simultaneously.This method uses a proportional integrator controller to control the duty factor of DC–DC converter with pulse-width modulator (PWM).The MPPT performance and hydrogen production performance of this method have been evaluated and discussed based on the results of the experiment.     

Proton exchange membrane fuel cell-powered bidirectional DC motor control based on adaptive sliding-mode technique with neural network estimation

Proton exchange membrane fuel cell (PEMFC), according to its merits of high energy density, zero emission, and low noise, has been widely applied in industrial appliances. A full bridge converter is used to implement PEMFC-powered DC motor bidirectional rotation in this paper. For the sake of the regulations of DC motor angular velocity as well as bus voltage, an adaptive backstepping sliding-mode control (ABSMC) technique integrated with Chebyshev neural network (CNN) is proposed. Based on the equivalent-circuit method, the control-oriented model of the PEMFC-powered motor system is structured. By constructing Lyapunov function, the adaptive laws and control laws can be obtained to achieve bus voltage and angular velocity regulations simultaneously. Moreover, the proposed neural network is applied to estimate the uncertainties of the system through orthogonal basis Chebyshev polynomials. To highlight the advantages of proposed technique, a proportional-integral (PI) control was introduced subsequently and two controllers were compared via numerical simulations. The simulation results demonstrate that CNN estimation method in conjunction with backstepping sliding-mode shows fast and accurate response even though the existence of system uncertainties and external disturbances.     

A control scheme with performance prediction for a PV fed water pumping system

This paper focuses on modeling and performance predetermination of a photovoltaic (PV) system with a boost converter fed permanent magnet direct current (PMDC) motor-centrifugal pump load, taking the converter losses into account. Sizing is done based on the maximum power generated by the PV array at the average irradiation. Hence optimum sizing of the PV array for the given irradiation at the geographical location of interest is obtained using the predetermined values. The analysis presented here involves systems employing maximum power point tracking (MPPT) as they are more efficient than directly coupled systems. However, the voltage and power of the motor might rise above rated values for irradiations greater than the average when employing MPPT, hence a control scheme has been proposed to protect the PMDC motor from being damaged during these conditions. This control scheme appropriately chooses the optimum operating point of the system, ensuring long-term sustained operation. The numerical simulation of the system is performed in Matlab/Simulink and is validated with experimental results obtained from a 180 V, 0.5 hp PMDC motor coupled to a centrifugal pump. The operation of the system with the proposed control scheme is verified by varying the irradiation levels and the relevant results are presented.