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Efficiency of photovoltaic (PV) systems is decreased by mismatch losses resulting from uneven panel irradiation. Current compensation techniques that inject compensatory current and measure currents by periodic row short-circuiting are unavoidably blackout-causing. In this work, a novel current compensation technique is presented that dynamically measures and reacts to variations in irradiance using light sensors on each panel. The program compiles these data to determine the overall irradiance of each row and to precisely modify the injected current to sustain output without any interruptions to operation. The proposed approach lowers mismatch losses more effectively than traditional techniques, as demonstrated by MATLAB/Simulink simulations of seven shading patterns. Under center shading, the proposed approach raised system efficiency by 36%. These results indicate a move towards more flexible solar energy solutions by implying that sensor-driven data analytics can increase PV system operational efficiency and reliability.

The magnet-less switched reluctance motor (SRM) speed-torque characteristics are ideally suited for traction motor drive characteristics and its advantage to minimize the overall cost of on-road EVs. The main drawbacks are torque and flux ripple, which have produced high in low-speed operation. However, the emerging direct torque control (DTC) operated magnitude flux and torque estimation with voltage vectors (VVs) gives high torque ripples due to the selection of effective switching states and sector partition accuracy. On the other hand, the existing model predictive control (MPC) with multiple objective and optimization weighting factors produces high torque ripples due to the system dynamics and constraints. Therefore, existing DTC and MPC can result in high torque ripples. This paper proposed a finite set (FS)-MPC with a single cost function objective without weighting factor: the predicted torque considered to evaluate VVs to minimize the ripples further. The selected optimal VV minimizes the SRM drive torque and flux ripples in steady and dynamic state behaviour. The classical DTC and proposed model were developed, and simulation results were verified using MATLAB/Simulink. The proposed model operated in SRM drives experimental results to prove the effective minimization of torque and flux ripples compared to the existing DTC. [ABSTRACT FROM AUTHOR]

Summary: The switched reluctance motor (SRM) is a prominent electrical machine drive with low cost and good performance in different drive applications. This machine's main drawbacks are torque ripple and flux ripple. However, the existing SRM‐operated direct torque control (DTC) Voltage vectors (VVs) give high torque ripples due to improper sector division and minimum selection of VVs switching states. On the other hand, a two‐level hysteresis torque band can result in torque ripples. Therefore, this paper proposed DTC using 16 partitions, active small and large VVs, and a multilevel hysteresis torque band (MHTB) strategy to mitigate the torque ripple further. More active VVs (i.e., 16) are employed in the modified sector‐based switching tables, suppressing the torque ripples. The proposed strategy is verified and validated using MATLAB/Simulink. The detailed result discusses the response of torque, flux, and speed of SRM. The DTC‐operated SRM drive experimental results prove the effective minimization of torque ripples in the proposed DTC compared to the existing DTC. [ABSTRACT FROM AUTHOR]