研究目的
To develop a hybrid control algorithm for the integration of solar photovoltaic systems in smart grid environments, focusing on power quality improvement, harmonics elimination, reactive power compensation, and load balancing.
研究成果
The proposed hybrid control algorithm effectively integrates solar PV systems with the grid, improving power quality, providing fast response under dynamic conditions, and reducing THD in grid currents. The algorithm outperforms conventional methods in terms of DC voltage regulation and harmonic compensation.
研究不足
The study focuses on a specific configuration of solar PV system integration and may not cover all possible grid conditions or larger scale implementations. The experimental validation is limited to a laboratory prototype.
1:Experimental Design and Method Selection:
The study employs a hybrid control algorithm combining I cos ? technique and quasi-Newton back-propagation neural network for grid integration of solar PV systems.
2:Sample Selection and Data Sources:
A 10-kW solar PV array is integrated with the grid under various conditions including linear and non-linear loads, and variable solar irradiance.
3:List of Experimental Equipment and Materials:
Includes a solar PV array, voltage source converter (VSC), ripple filter, and different types of loads.
4:Experimental Procedures and Operational Workflow:
The system's performance is tested under dynamic linear and non-linear loads, and variable solar irradiance conditions using MATLAB/Simulink simulations and a hardware prototype.
5:Data Analysis Methods:
Performance is evaluated based on DC voltage undershoot and overshoot, settling time, and THD in grid currents.
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