Multilevel Inverters are a new family of converters for dc-ac conversion for the medium and high voltage and power applications. In this paper, two new topologies for the staircase output voltage generations have been proposed with lesser number of switch requirement. The first topology requires three dc voltage sources and ten switches to synthesize 15 levels across the load. The extension of the first topology has been proposed as the second topology which consist of four dc voltage sources and 12 switches to achieve 25 levels at the output. Both topologies, apart from having lesser switch count exhibit the merits in terms of reduced voltage stresses across the switches. In addition, a detailed comparative study of both topologies has been presented in the paper to demonstrate the features of the proposed topologies. Finally, several experimental results have been included in the paper to validate the performances of the proposed topologies with different loading condition and dynamic changes in load and modulation indexes.

Multilevel inverters (MLI) since its inception have caught the attention of researchers for medium and high power application. However, there has always been a need for a topology with a lower number of device count for higher efficiency and reliability. A new single phase MLI topology has been proposed in this paper to reduce the number of switches in the circuit and obtain higher voltage level at the output. The basic unit of the proposed topology produces 13 level at the output with three dc voltage sources and eight switches. Three extention of the basic unit have been proposed in this paper. A detailed analysis of the proposed topology has been carried out to show the superiority of the proposed converter with respect to the other existing MLI topologies. Power loss analysis has been done using PLECS software, results in maximum efficiency of 98.5%. Nearest level control (NLC) pulse width modulation technique has been used to produce gate pulses for the switches to achieve better output voltage waveform. The various simulation results have been performed in the PLECS software and a laboratory setup has been used to shows the feasibility of the proposed MLI topology.

Inclusion of bypass diodes at the output terminal of the PV array mitigates the effect of partial shading (PS) but causes multiple peaks of power at the output. The conventional hill climbing and perturb and observe algorithms cannot track the optimal point during partial shading phenomena for multiple peaks corresponding to the different shading pattern on the Power-Voltage (P-V) curve. Fuzzy logic controller and artificial neural network-based methods for Maximum Power Point Tracking (MPPT) provide satisfactory results but at the cost of increased memory and computational burden. Recent work to incorporate exploration and exploitation phenomena of nature-inspired algorithms to track optimal power point have shown encouraging results by preventing convergence to local maxima and posing less burden on the processor. However, due to performance variation between different algorithms of this category newer algorithms with improved performances are still a requirement. In this paper, a novel most valuable player algorithm (MVPA) has been used to track the optimal operation point for extracting maximum power from a solar PV system. The algorithm's performance is compared with the commonly employed particle swarm optimization (PSO) and the recently proposed Jaya algorithm's modified form. It is observed that the proposed algorithm outperformed both the algorithms with a considerable improvement in terms of tracking speed, power tracking efficiency, robustness, faster decision for convergence after tracking the maximum power and lesser number of power fluctuations for different shading patterns.

In this paper, the Levenberg–Marquardt (LM), Bayesian regularization (BR), resilient backpropagation (RP), gradient descent momentum (GDM), Broyden–Fletcher–Goldfarb–Shanno (BFGS), and scaled conjugate gradient (SCG) algorithms constructed using artificial neural networks (ANN) are applied to the problem of MPPT energy harvesting in solar photovoltaic (PV) systems for the purpose of creating a comparative evaluation of the performance of the six distinct algorithms. The goal of this analysis is to determine which of the six algorithms has the best overall performance. In the study, the performance of managing the training dataset is compared across the algorithms. The maximum power point tracking energy harvesting system is created using the environment of MATLAB or Simulink, and the produced model is examined using the artificial neural network toolkit. A total of 1000 datasets of solar irradiance, temperature, and voltage were used to train the suggested model. The data are split into three categories: training, validation, and testing. Eighty percent of the total data is used for training the model, and the remaining twenty percent is divided equally for testing and validation. According to the results, the regression values of LM, RP, BR, and BFGS are 1, whereas the regression values for SCG and GDM are less than 1. The gradient values for LM, RP, BFGS, SCG, BR, and GDM are 7.983 × 10⁻⁶, 0.033415, 1.0211 × 10⁻⁷, 0.14161, 0.00010493, and 11.485, respectively. Similarly, the performance values for these algorithms are 2.0816 × 10⁻¹⁰, 2.8668 × 10⁻⁶, 9.98 × 10⁻¹⁷, 0.052985, 1.583 × 10⁻⁷, and 0.15378. Overall, the results demonstrate that the LM and BFGS algorithms exhibit superior performance in terms of gradient and overall performance. The RP and BR algorithms also perform well across various metrics, while the SCG and GDM algorithms show comparatively less effectiveness in addressing the proposed problem. These findings provide valuable insights into the relative performance of the six evaluated algorithms for MPPT energy harvesting in solar PV systems.

High gain dc-dc converters are used in several applications which include solar photovoltaic system, switch-mode power supplies and fuel cells. In this paper, an ultra-high gain dc-dc boost converter is proposed and analyzed in detail. The converter has a gain of six times as compared with the boost converter. The high gain is achieved by utilizing switched inductors and switched capacitors. A modified voltage multiplier cell (VMC) with switched inductors is proposed. The converter has a single switch which makes its operation easy. Moreover, the voltage across the switch, diodes and capacitors are less than the output voltage which increases the overall efficiency of the converter. The converter performance in steady-state is analyzed in detail and it is compared with other latest high gain converters. The working of the converter in non-ideal conditions is also discussed in detail. The loss analysis is done using PLECS software by incorporating the real models of switches and diodes from the datasheet. To confirm and validate the working of the proposed converter a hardware prototype of 200 W is developed in the laboratory. The converter achieves high gain at low duty ratios and its performance is found to be good in open and closed loop conditions.

High gain DC-DC converters are increasingly being used in solar PV and other renewable generation systems. Satisfactory steady-state and dynamic performance, along with higher efficiency, is a pre-requirement for selecting the converter for these applications. In this paper, a non-inverting high gain DC-DC boost converter has been proposed. The proposed converter has only one switch with continuous input current and reduced voltage stress across switching devices. The operating range of the duty cycle is wider, and it obtains a higher gain at a lower value of the duty cycle. Moreover, the converter has higher efficiency at a lower duty cycle while drawing a continuous input current. The continuous input current is a desirable feature of the dc-dc converter making it suitable for solar photovoltaic applications. The converter's operation has been discussed in detail and extended to include the real circuit parameters for a practical performance evaluation. The proposed converter has been compared with other similar recently proposed converters on various performance parameters. The loss analysis for the proposed converter has also been carried out. Finally, the simulation has been validated with results from the experimental prototype.