一种鲁棒ANN-PID校正器的设计与实现,以改善高穿透光伏太阳能并网

Q3 Energy
D. Gueye, A. Ndiaye, Amadou Diao
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引用次数: 0

摘要

进入电网的光伏能量的最佳质量现在是个问题,这就是为什么本文专注于基于人工神经网络(ANN-PID)的鲁棒比例积分导数的设计和实现。该技术用于确保连接到电网的光伏太阳能系统(PVS)的升压转换器(BC)输出电压和三相逆变器(3PI)输出电流的调节。给出了直流母线和3-PI的数学模型。在Matlab/Simulink下的应用证明了神经调节器的有效性。与传统方法相比,所提出的方法呈现出DC链路电压参考的最佳跟随和3.16%的最大过冲。此外,尽管处于瞬态模式的时间很长,但所提出的方法保持了更好的鲁棒性,并确保了总谐波失真(THD)为0.96%的电流注入,而传统PID调节器的总谐波失真为2.18%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and implementation of a robust ANN-PID corrector to improve high penetrations photovoltaic solar energy connected to the grid
The best quality of PV energy into the grid is now problematic that is why this paper focuses on the design and implementation of a robust Proportional Integral Derivative based on Artificial Neural Network (ANN-PID). This technique used to ensure the regulation of the Boost Converter (BC) output voltage and the Three Phase Inverter (3 PI) output currents of a photovoltaic solar system (PVS) connected to the grid. The mathematical model of the DC bus and the 3-PI is presented. Applications under Matlab/Simulink justify the efficiency of the neural regulator. In comparison with the conventional one, the proposed method presents the best follow-up of the DC link voltage reference and a maximum overshoot of 3.16 %. In addition, despite the long time put in transient mode, the proposed method keeps better robustness and ensures an injection of current of a total harmonic distortion (THD) of 0.96 % against 2.18 % of the classical PID regulator.
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来源期刊
Journal of Energy Systems
Journal of Energy Systems Environmental Science-Management, Monitoring, Policy and Law
CiteScore
1.60
自引率
0.00%
发文量
29
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