研究目的
To optimize the perturbation period (Tp) in maximum power point tracking (MPPT) algorithms for photovoltaic (PV) systems by identifying the online value of Tp using the dichotomous coordinate descent-recursive least squares (DCD-RLS) algorithm.
研究成果
The DCD-RLS algorithm effectively identifies the online value of the PV system settling time, leading to optimized perturbation period (Tp) in MPPT algorithms. This method is computationally efficient, suitable for online applications, and improves both the speed and accuracy of MPPT algorithms compared to previous works.
研究不足
The identification process temporarily halts the MPPT function, which could lead to missing the maximum power point (MPP) in variable weather conditions if the identification speed is not sufficiently high.
1:Experimental Design and Method Selection:
The study employs the DCD-RLS algorithm for online identification of the PV system settling time, using an IIR adaptive filter as the system model.
2:Sample Selection and Data Sources:
The PV system, including PV panels, a boost converter, and load, is simulated in PSIM and MATLAB/Simulink software.
3:List of Experimental Equipment and Materials:
Includes YL60P-17b PV panels, a boost converter, and a Texas Instruments TMS320F2812 DSP platform for implementation.
4:Experimental Procedures and Operational Workflow:
The MPPT algorithm is run with a non-optimized Tp, then the DCD-RLS identification is activated to optimize Tp based on the system settling time.
5:Data Analysis Methods:
The identified parameter from the DCD-RLS algorithm is used to calculate the system settling time, which is then used to update the optimized Tp in the MPPT algorithm.
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