Analysis of the Characteristics of Low Noise and Ultra Low Distortion IV Conversion Technology Based on Support Vector Machine Algorithm

As an important part of front-end signal processing, current-voltage (IV) conversion technology directly affects the performance and reliability of the whole system. The purpose of this study is to explore the method of IV conversion signal processing and feature detection with low noise and ultra-low distortion based on support vector machine (SVM) algorithm. According to the actual situation of photovoltaic power generation system, the IV conversion signal is processed and predicted by SVM algorithm to improve the accuracy and stability of current-voltage conversion. In the actual photovoltaic power generation system, an appropriate algorithm should be adopted to dynamically find out the maximum power point and make adaptive adjustment according to the changes of the external environment, so as to ensure the maximum power output of the system. Through the analysis of the experimental results, it can be found that the IV conversion model based on SVM has higher prediction accuracy and robustness than other algorithms, and can better understand and predict the dynamic behavior and performance of photovoltaic power generation system. This result fully proves the performance superiority of low noise and ultra-low distortion IV conversion technology based on SVM algorithm.