Review of speed estimation algorithms for three- phase induction motor.

In the field of evolving industrial automation, there is a growing need for refined sensorless speed estimation techniques for induction drives to cater the demands of various applications. In this paper, the sensorless speed estimation algorithms for induction motor drives are investigated and reviewed detailly for real-time industrial usages. The main objective of this paper is to classify sensorless techniques by highlighting the characteristics, merits and drawbacks of each sensorless speed estimation techniques of induction motor drives. Different techniques like Rotor slot harmonics, Signal Injection, and Machine model based system have the benefits of sensorless motor drives involving lower costs, higher reliability, simpler hardware complication, improved noise immunity, and lesser maintenance requirement. As a result of the advancement of current industrial automation, more improved sensorless estimation techniques are required to meet application demand. The various speed estimation techniques are distinguished based on criteria of steady state error, dynamic behavior, low speed operation, parameter sensitivity, noise sensitivity, complexity and computation time. This comparison allows to opt the best sensorless speed estimation technique for induction motor drive to be implemented based on a specific application. The results of comparison highlight the characteristics of each technique.

MPPT control of a solar pumping system based five-phase impedance source inverter fed induction motor.

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.

Design and analysis of photovoltaic/wind operations at MPPT for hydrogen production using a PEM electrolyzer: Towards innovations in green technology.

In recent times, renewable energy systems (RESs) such as Photovoltaic (PV) and wind turbine (WT) are being employed to produce hydrogen. This paper aims to compare the efficiency and performance of PV and WT as sources of RESs to power polymer electrolyte membrane electrolyzer (PEMEL) under different conditions. The study assessed the input/output power of PV and WT, the efficiency of the MPPT controller, the calculation of the green hydrogen production rate, and the efficiency of each system separately. The study analyzed variable irradiance from 600 to 1000 W/m2 for a PV system and a fixed temperature of 25°C, while for the WT system, it considered variable wind speed from 10 to 14 m/s and zero fixed pitch angle. The study demonstrated that the applied controllers were effective, fast, low computational, and highly accurate. The obtained results showed that WT produces twice the PEMEL capacity, while the PV system is designed to be equal to the PEMEL capacity. The study serves as a reference for designing PV or WT to feed an electrolyzer. The MATLAB program validated the proposed configurations with their control schemes.