Design of PID Controller using Artificial Neural Network for Step-up Power Converter in Photovoltaic Systems

S. Gupta, J. K. Mohanta
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引用次数: 2

Abstract

The most attractive renewable energy resource that provides clean electricity via solar PV panels is solar irradiation received from the Sun. Solar energy is available mainly during the daytime, but solar photovoltaic (PV) panels can produce maximum power due to low efficiency. Hence, maximum power point tracking (MPPT) methods are used with solar PV systems. The interface required between solar PV panels and the load is a DC-DC converter, a power electronics device. This paper proposes a neural network-based PID controller for the boost converter. The well-known back prorogation neural network algorithm is used with PID structure to design a controller for the boost converter. The study is carried out with the help of MATLAB/Simulink software to show the test results. The simulations’ outcome shows the proposed controller’s efficacy when used with solar PV systems.
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基于人工神经网络的光伏系统升压变换器PID控制器设计
通过太阳能光伏板提供清洁电力的最具吸引力的可再生能源是来自太阳的太阳辐射。太阳能主要在白天可用,但太阳能光伏(PV)板由于效率低,可以产生最大的功率。因此,最大功率点跟踪(MPPT)方法被用于太阳能光伏系统。太阳能光伏板和负载之间所需的接口是一个DC-DC转换器,一个电力电子设备。本文提出了一种基于神经网络的升压变换器PID控制器。将著名的逆延神经网络算法与PID结构相结合,设计升压变换器的控制器。在MATLAB/Simulink软件的帮助下进行了研究,展示了测试结果。仿真结果表明了该控制器在太阳能光伏系统中的有效性。
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