Abstract
A photovoltaic power supply with a simple structure and high tracking efficiency is needed in self-powered, wireless sensor networks. First, a maximum power point tracking (MPPT) algorithm, including the load current maximization-perturbation and observation (LCM-P&O) methods, with a fixed step size, is proposed by integrating the traditional load current maximization (LCM) method and perturbation and observation (P&O) method. By sampling the changes of load current and photovoltaic cell input current once the disturbance is applied, the pulse width modulation (PWM) regulation mode, i.e., increasing or reducing, can be determined in the next process. Then, the above algorithm is improved by using the variable step size strategy. By comparing the difference between the absolute value of the observed current value and the theoretical current value at the maximum power point of the photovoltaic cell with the set threshold value, the variable step size for perturbation is determined. MATLAB simulation results show that the LCM-P&O method, with a variable step size, has faster convergence speed and higher tracking accuracy. Finally, the two MPPT algorithms are tested and analyzed under constant voltage source input and indoor fluorescent lamp illumination through an actual circuit, respectively. The experimental results show that the LCM-P&O method with variable step size has a higher tracking efficiency, about 90%–92%, and has higher stability and lower power consumption.
Highlights
The traditional wireless sensor network (WSN) usually uses dry cells and other disposable storage for its energy supply
The existing perturbation and observation (P&O) maximum power point tracking (MPPT) algorithm improves the contradiction of tracking accuracy and tracking time by changing the step size, but does not consider the energy consumption
The experimental results show that the MPPT circuit can track the maximum power point of under static conditions fast and response speed under dynamic can beand useda in a the photovoltaic cell in and real atime, has good tracking precisionconditions; under staticit conditions fast kind of low-power system similar to WSN. it can be used in a kind of low-power system similar response speed under dynamic conditions; to WSN
Summary
The traditional wireless sensor network (WSN) usually uses dry cells and other disposable storage for its energy supply. The existing P&O MPPT algorithm improves the contradiction of tracking accuracy and tracking time by changing the step size, but does not consider the energy consumption This P&O method has some limitations in practical applications of photovoltaic power supply in WSN. The performance theonly circuit is analyzed by much.beThe maximum power point of the photovoltaic cellofcan be analyzed by sampling simulating the voltage of the photovoltaic cell with a constant voltage source and adjusting the the load current. The experimental results show that the MPPT circuit can track the maximum power point of under static conditions fast and response speed under dynamic can beand useda in a the photovoltaic cell in and real atime, has good tracking precisionconditions; under staticit conditions fast kind of low-power system similar to WSN. The experimental results show that the MPPT circuit can track the maximum power point of under static conditions fast and response speed under dynamic can beand useda in a the photovoltaic cell in and real atime, has good tracking precisionconditions; under staticit conditions fast kind of low-power system similar to WSN. it can be used in a kind of low-power system similar response speed under dynamic conditions; to WSN
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