基于人工智能优化控制器的光伏系统最大功率跟踪比较

2020 International Conference for Emerging Technology (INCET) Pub Date : 2020-06-01 DOI:10.1109/incet49848.2020.9154109

Ayush Verma, S. Yadav, Ankita Arora, Kartikey Singh

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引用次数: 2

摘要

针对光伏系统最大功率点跟踪的比较研究，分析了基于人工智能的优化控制器的性能。人工神经网络(ANN)和粒子群优化(PSO)控制方法就是其中的两种控制方法，并在MATLAB-Simulink中使用天合光能TSM-250PD05.08进行了仿真。仿真结果从上升时间、沉降时间、达到最大功率点所需时间和效率等参数比较了这些方法的性能。研究发现，与人工神经网络相比，采用粒子群算法跟踪光伏系统的最大功率点具有更高的效率。

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Comparison of Maximum Power Tracking using Artificial Intelligence based optimization controller in Photovoltaic Systems

This paper analyzes performance of Artificial Intelligence based optimization controller for the comparative study of maximum power point tracking (MPPT) in PV Systems. Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) control methods are the two such techniques used, and are simulated in MATLAB-Simulink using Trina Solar TSM-250PD05.08. The simulation results suitably depict the performance of these methods on the basis of some parameters like their rise time, settling time, time taken to reach maximum power point and their efficiency. It is found that maximum power point is tracked in PV systems with greater efficiency using PSO as compared to ANN.

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2020 International Conference for Emerging Technology (INCET)

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