Faculty of Engineering, Electrical Engineering Department, Benha University, Banha, Cairo, Egypt.
Department of Electrical Power and Machines Engineering, Higher Institute of Engineering, El-Shorouk Academy, El-Shorouk City, Cairo, Egypt.
PLoS One. 2024 Jan 18;19(1):e0295365. doi: 10.1371/journal.pone.0295365. eCollection 2024.
This paper presents a control method for a system composed of a photovoltaic (PV) array, five-phase impedance source inverter, five-phase induction motor and centrifugal pump. This method is based on controlling the motor speed to control the pump power as the insolation level or temperature change to attain the maximum power extraction from the PV-array. The motor speed is controlled by using artificial neural network (ANN) which is trained to provide the desired inverter frequency and modulation index at any insolation level and temperature to attain the maximum PV operating power. The data of the neural network are based on the operation of the induction motor at constant air gap flux and perturb and observe method for maximum power point tracking. Simulation results are obtained using MATLAB Simulink to verify the proposed control method.
本文提出了一种由光伏(PV)阵列、五相阻抗源逆变器、五相感应电机和离心泵组成的系统的控制方法。该方法基于控制电机速度来控制泵功率,以根据光照水平或温度变化来实现从 PV 阵列中提取最大功率。电机速度通过使用人工神经网络(ANN)进行控制,该神经网络经过训练可在任何光照水平和温度下提供所需的逆变器频率和调制指数,以实现 PV 运行功率的最大化。神经网络的数据基于感应电机在恒气隙磁通下的运行和最大功率点跟踪的扰动观察法。使用 MATLAB Simulink 获得了仿真结果,以验证所提出的控制方法。