This paper proposes a standalone single stage PV fed PMSM drive for water pumping. The proposed system aims at reducing the switching losses and overall cost by using reduced switch inverter (RSI). The proposed system comprises of a PMSM drive, fed by PV source through an inverter employing reduced number of switches. The inverter uses only four switches whereas the conventional VSI utilizes six switches. Field oriented control scheme is employed to control the PMSM drive. Perturb and Observe (P&O) MPPT technique is used to generate a speed reference to PMSM drive. Simulation studies for the proposed PV fed PMSM driven water pumping system are performed using MATLAB platform and it is also experimentally verified through FPGA controller based 400 W laboratory prototype PMSM drive and results demonstrates the efficacy of the system.

This paper presents a reference current generation scheme for improved dynamic performance of a doubly fed induction generator (DFIG) subjected to unbalanced grid voltage. The power and torque oscillations induced due to the unbalance in grid voltage are minimized using additional compensatory terms in the reference currents. The focus is on estimating the reference currents and control implementation without the need for dual vector control. Real and reactive power control is implemented in the positive d-q reference frame using stator flux-oriented vector control. The rotor-side converter (RSC) is controlled to enable effective reduction of oscillations in torque and active and reactive power. The dc-link voltage oscillation is minimized and the grid-side power factor is maintained unity using the grid-side converter (GSC). Unlike the previously reported techniques, the proposed scheme enables effective reduction of oscillations in torque, active, and reactive power, and the dc-link voltage, all in a single target. The performance of DFIG is investigated in consideration with the Indian Electricity Grid Code (IEGC). Numerical simulations are carried out in power system computer aided design/electromagnetic transients including direct current (PSCAD/EMTDC) for the laboratory 3-hp DFIG test setup. The results establish that the performance of DFIG is notably enhanced with the proposed scheme.

This paper proposes simple and robust electromagnetic torque based MRAS speed estimator with cascaded Pseudo Derivative Feedback (PDF) controller is proposed for sensorless SMPMSM drive to improve its performance at standstill and low speed regions. The proposed estimator is formed using instantaneous and estimated electromagnetic torque. Using small signal modelling, the stability and sensitivity analysis are performed. Results show that, the estimator is stable over a wide speed region (including low speed regions) and exhibits robustness against uncertainties in machine parameters. The proposed estimator is implemented for 1.5 kW laboratory prototype SMPMSM drive using FPGA ALTERA cyclone II. Experimental results demonstrate the efficacy of the proposed scheme under different test conditions viz. over a wide adjustable speed range which include different low speed regions and standstill i.e. 157 to -157 rad/s at different load conditions with uncertainty in machine parameters.

Agriculture and farming are the most important and basic industries that are very important to humanity and generate a considerable portion of any nation's GDP. For good agricultural and farming management, technological advancements and support are required. Smart agriculture (or) farming is a set of approaches that uses a variety of current information and communication technology to improve the production and quality of agricultural products with minimum human involvement and at a lower cost. Smart farming is mostly based on IoT technology, since there is a need to continually monitor numerous aspects in the agricultural field, such as water level, light, soil characteristics, plant development, and so on. Machine learning algorithms are used in smart farming to increase production and reduce the risk of crop damage. Data analytics has been shown through extensive study to improve the accuracy and predictability of smart agricultural systems. Data analytics is utilised in agricultural fields to make decisions and recommend acceptable crops for production. This study provides a comprehensive overview of the different methods and structures utilised in smart farming. It also provides a thorough analysis of different designs and recommends appropriate answers to today's smart farming problems.

A simple and implicit sensorless algorithm for estimating the rotor position and speed of the doubly fed induction machine is proposed in this study. Instead of computing the stator magnetic flux directly or indirectly, the stator flux vector components in the stationary reference frame are substituted with analytical equivalents in terms of measurable stator and rotor quantities. Thus, it is an implicit estimation process devoid of computing any flux terms and requires only the measured stator voltage and currents in stator and rotor windings apart from knowledge of the machine parameters. It is an open-loop scheme. However, it does not involve integration, recursive techniques, re-computations or programmable low-pass filters etc. Starting on the fly, accurate estimation near synchronous speed, immunity against variation in stator and rotor resistances or in the magnetising inductance are the principal advantages of the algorithm. Reduced complexity and the computational burden facilitate the easy implementation of the algorithm on a low-cost fixed point processor. Excellent agreement between the simulation and test results on a laboratory doubly fed induction motor validates the proposed estimation algorithm implemented for the vector control of a doubly fed induction motor. On the whole, the estimation algorithm is a new insight that holds promise in the area of sensorless control of the DFIM, whether used as a motor or as a generator.