研究目的
To propose an improved variable step size adaptive harmonic detection method that solves the conflict between convergence speed and steady-state accuracy in traditional adaptive harmonic detection methods, and to apply this method in a photovoltaic-active power filter (PV-APF) system to improve power quality.
研究成果
The improved variable step size adaptive harmonic detection algorithm achieves faster convergence speed and smaller steady-state error compared to traditional methods. Applied in the PV-APF system, it effectively improves power quality by reducing the total harmonic distortion to 2.09%. The algorithm's robustness and adaptability make it suitable for real-time harmonic detection and compensation in photovoltaic systems.
研究不足
The study focuses on the application of the improved algorithm in a PV-APF system under normal light conditions. The performance under varying light intensities or more complex harmonic conditions may require further investigation.
1:Experimental Design and Method Selection:
The study employs an improved variable step size adaptive harmonic detection algorithm based on the adaptive noise cancellation principle. The algorithm uses a sliding integrator to find the true tracking error and adjusts the step size using a new variable step size iterative formula based on the L2 norm.
2:Sample Selection and Data Sources:
The nonlinear load current is sampled and processed to detect harmonics. The grid voltage and load current are used as inputs for the harmonic detection algorithm.
3:List of Experimental Equipment and Materials:
The PV-APF system includes solar PV cells, a boost chopper circuit, a full bridge inverter circuit, harmonic detection modules, a ripple filter, and nonlinear loads. Simulation is performed using MATLAB/Simulink.
4:Experimental Procedures and Operational Workflow:
The algorithm is applied to the PV-APF system. The system's performance is evaluated under normal light conditions, and the harmonic detection algorithm's convergence speed and steady-state accuracy are compared with traditional methods.
5:Data Analysis Methods:
The performance of the improved algorithm is analyzed based on convergence speed, steady-state error, and total harmonic distortion (THD) of the system.
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