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Wind energy is a valuable renewable resource, and advances in wind energy technology have made it more cost-effective. The future of wind-electric transformation will depend on improvements in power electronic devices. A bridge-less power factor corrected buck-boost conversion has been developed for the wind energy conversion system, and for each voltage level, the total harmonic distortion, current, and power factor have been computed using MATLAB/Simulink with sinusoidal pulse width modulation approach for inverter switches. The simulation findings demonstrate that the proposed Cascaded H-Bridge (CHB) with a single DC source can efficiently manage voltage, current, and power factor through fast discrete wavelet transform analysis and switch management. The CHB-Multilevel Inverter (MLI) logic employs intermediate output voltages and is connected in a series of multiple single-stage inverters. The presented method compares current and planned performances and does not require different DC supplies for grid utility, resulting in cost-effective wind turbine management. [ABSTRACT FROM AUTHOR]

In a grid connected photovoltaic (PV) system, the maximum power will be tracked by the conventional Perturb and Observe (P&O) algorithm. It generally produces high oscillations around maximum power point, and it fails to attain extreme power under prompt environmental conditions. To overcome these issues, this work proposes a deep neural network (DNN) based Maximum Power Point tracking (MPPT) algorithm and PR controller-based SMO for PV grid-connected system. The DNN consists of many algorithms in that here we use RNN in MPPT algorithm for tracking the maximum power. The Recurrent Neural Network (RNN) hidden layer has more number of layers. The deep network weight function is optimised by meta-heuristic-based Bald Eagle Search (BES) Optimisation. The proposed tracked RNN based Maximum Power Point (MPP) is passed through the DC/DC buck-boost converter. The inverter is tuned by Proportional Resonant (PR) controller, and it has two gain parameters like a proportional and integral gain. The PR controller gain parameters are tuned by the global optimisation algorithm of Spider Monkey Optimisation (SMO) to achieve better performance. [ABSTRACT FROM AUTHOR]

Highlights: [•] New offline MPPT method has been developed. [•] Both open circuit voltage and short circuit currents were considered. [•] Reference panel is used and PIC is used to locate MPPT. [•] Experiments were conducted to study the efficiency. [•] The maximum efficiency of the system was about 94%. [Copyright &y& Elsevier]

The strings of photovoltaic panels have a significantly reduced power output when mismatch between the panels occurs, as, e.g., caused by partial shading. With mismatch, either the panel-integrated diodes are bypassing the shaded panels if the string is operated at the current level of the unshaded panels, or some power of the unshaded panels is lost if the string current is reduced to the level of the shaded panels. With the implementation of dc-dc converters on panel level, the maximum available power can be extracted from each panel regardless of any mismatch. In this paper, different concepts of PV panel-integrated dc-dc converters are presented and their suitability for panel integration is evaluated. The buck-boost converter is identified as the most promising concept and an efficiency/power density ( η- ρ) Pareto optimization of this topology is shown. Based on the optimization results, two 275 W converter prototypes with either Silicon MOSFETs with a switching frequency of 100 kHz or gallium nitride FETs with a switching frequency of 400 kHz are designed for an input voltage range of 15 to 45 V and an output voltage range of 10 to 100 V. The theoretical considerations are verified by efficiency measurements which are compared to the characteristics of a commercial panel-integrated converter. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new technique used to design a robust controller that is not as high-order and complicated as the ones designed by conventional H∞ loop shaping method. To overcome the problem we proposed an algorithm called Genetic Algorithm (GA) based fixed-structure H∞ loop shaping control. In the approach, GA is adopted to solve the H∞ loop shaping design problem under a structure specified controller. The performance and robustness of the proposed controller are investigated in a buck-boost converter in comparison with the controller designed by conventional H∞ loop shaping. Results of simulations demonstrate the advantages of the proposed controller in terms of simple structure and robustness against plant perturbations and disturbances. Experiments are performed to verify the effectiveness of the proposed technique. [ABSTRACT FROM AUTHOR]