基于EP&O-MPC算法的光伏系统全局最大功率点跟踪
Global Maximum Power Point Tracking of Photovoltaic Systems Based on the EP&O-MPC Algorithm
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摘要: 针对光伏系统受环境工况影响出现多个最大功率点、进而导致能量转换效率降低的技术难题,本文提出一种混合控制算法。该算法可有效避免系统陷入局部功率峰值,确保对全局最大功率峰值的精准跟踪。本文所提方法整合了改进型扰动观测和模型预测控制算法,通过参考电流计算实现对系统未来状态的预测;同时采用升压变换器实现对电压与电流的调控,动态调整以实现最优功率捕获,且通过省去电流传感器降低硬件成本。仿真结果表明,该方法在经济性与功率转换效率方面均优于传统控制方法。Abstract: This paper addresses the challenge of environmental conditions in photovoltaic systems, which create multiple maximum power points and reduce energy efficiency. It proposes a hybrid control algorithm that prevents settling at local peaks and ensures tracking of the global maximum peak. The approach integrates an enhanced perturb and observe-based model predictive control algorithm, which predicts future states using reference current calculations. A boost converter regulates voltage and current, dynamically adjusting for optimal power extraction while minimizing hardware costs by eliminating the output current sensor. Simulations and hardware tests confirm that this method outperforms traditional techniques in cost-effectiveness and power efficiency.
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