PV generating sources are one of the most promising power generation systems in today’s power scenario. The inherent potential barrier that PV possesses with respect to irradiation and temperature is its nonlinear power output characteristics. An intelligent power tracking scheme, e.g., maximum power point tracking (MPPT), is mandatorily employed to increase the power delivery of a PV system. The MPPT schemes experiences severe setbacks when the PV is even shaded partially as PV exhibits multiple power peaks. Therefore, the search mechanism gets deceived and gets stuck with the local maxima. Hence, a rational search mechanism should be developed, which will find the global maxima for a partially shaded PV. The conventional techniques like fractional open circuit voltage (FOCV), hill climbing (HC) method, perturb and observe (P&O), etc., even in their modified versions, are not competent enough to track the global MPP (GMPP). Nature-inspired and bio-inspired MPPT techniques have been proposed by the researchers to optimize the power output of a PV system during partially shaded conditions (PSCs). This paper reviews, compares, and analyzes them. This article renders firsthand information to those in the field of research, who seek interest in the performance enhancement of PV system during inhomogeneous irradiation. Each algorithm has its own advantages and disadvantages in terms of convergence speed, coding complexity, hardware compatibility, stability, etc. Overall, the authors have presented the logic of each global search MPPT algorithms and its comparisons, and also have reviewed the performance enhancement of these techniques when these algorithms are hybridized.

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Harmonic Distortion in many of the industrial applications are occur primarily owing to the enormous utilization of loads with high non-linearity like power converters, speed varying drives and arc furnaces. The power semiconductor is used to achieve the variation in speed and conversion from one source to another. Mostly active filters and tuned filters are utilized to remove the harmonic included in the source current. The tuned passive filters and inductance inserted in the line reduces the harmonics but at the same time induces the resonances in most of the industrial applications. Due to this, harmonic distortion increases in the source current and voltage. This can be reduced by adding hybrid filter in the system with decreased rating of active filter in high power applications. This article deals with the various topology of hybrid filters. The working of the proposed filter design in variable inductance mode based on the pollution created in the source voltage and current is studied. In the proposed hybrid filter passive filter is tuned with seventh harmonic frequency and connected in series with active filters to reduce the harmonic distortion. DC link voltage and the active filter VA rating could be minimized. The control signal to the filter is derived from p-q theory and space vector pulse width modulation (SVPWM). The performance of the system under study is simulated and noted for the THD percentage before and after the filter is added to the system and the same model is experimented with reduced voltage level.

Low power distribution systems have severe power quality issues due to the non-linearity of several residential and industrial loads. The main power quality issue is the harmonics leading to the overheating of the transformers in the distribution systems. By employing passive filters, active filters, and custom power devices, the harmonics in the source current can be reduced. To overcome the drawbacks of conventional tuned filters and active power filters the modified shunt active power filter was introduced with the fuzzy logic controller. In this paper, an effective way of reducing the total harmonic distortion using three-phase three-wire shunt active filter is carried out and this has been investigated through three control methods namely synchronous reference frame theory, real and reactive power theory, and indirect reference current theory. The recognized control methods are implemented with the fuzzy controller to improve the performance of the induction motor drive. The hardware setup was implemented for the proposed fuzzy-based control technique to achieve better performance in terms of reduced total harmonic distortion and DC link voltage and improved speed performance of induction motor drive when compared to other control methods. Further power factor correction and better reactive power compensation are achieved by implementing hardware.

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Summary In this article, a hysteresis space vector modulation (HSVM) is developed for interleaved Vienna rectifier (IVR) fed 3‐level neutral point clamped inverter (NPCI) system. The minimized current ripple and improved output voltage is obtained using HSVM control technique. The output of IVR is fed with 3‐level NPCI, which provides continuous input source, balanced capacitor voltage and minimized common mode voltage. Hysteresis circular region‐based control method is implemented to minimize the current ripple in the rectifier side. The multicarrier sinusoidal pulse width modulation technique is used to control 3‐level NPC inverter, which provides reduced total harmonic distortion (THD), balanced capacitor voltage and improved output voltage. This proposed system outputs are verified using MATLAB simulink and FPGA processor for simulation and experimental results, respectively.

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Induction motors are popularly used in various applications because of the proposed modest construction, substantiated process, and limited size of specific power. The traditional AC traction drives are experimentally analyzed. There is a high circulating current due to the high Common-Mode Voltage (CMV). The high Circulating Bearing Current (CBC) is a major problem in conventional two-level voltage source inverter fed parallel-connected sensor-based induction motors for traction applications. A sensorless method is well known for shrinking costs and enhancing the reliability of an induction motor drive. The modified artificial neural network-based model reference adaptive system is designed to realize speed estimation methods for the sensorless drive. Four dissimilar multilevel inverter network topologies are being implemented to reduce CBC in the proposed sensorless traction motor drives. The multilevel inverter types are T-bridge, Neutral Point Clamped Inverter (NPC), cascaded H-bridge, and modified reduced switch topologies. The four methods are compared, and the best method has been identified in terms of 80% less CMV compared to the conventional one. The modified cascaded H-bridge inverter reduces the CBC of the proposed artificial neural network-based parallel connected induction motor; it is 50% compared to the conventional method. The CBC of the modified method is analyzed and associated with the traditional method. Finally, the parallel-connected induction motor traction drive hardware is implemented, and the performance is analyzed.