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The electricity demand is increasing day by day. On the other side, fossil fuels are depleting at a higher rate. The abundantly available renewable energy sources like solar, wind, and fuel cells are becoming popular sources of energy. But due to the intermittent availability of these renewable energy sources, two or more energy sources are integrated together. Power electronic converters are used for integrating different energy sources. Various power electronic converter (PEC) topologies have been proposed and analyzed in detail to control maximum power point, voltage, frequency, and harmonic distortions. Each of these configurations will differ in its topology and operating principle. The objective of this paper is to present a comprehensive review of various aspects of PEC configurations available for integration of renewable energy sources by systematization into three groups (AC shunt coupled, DC shunt coupled, and hybrid coupled systems). Emphasis is also given to coordination power control, maximum power point, and grid integration challenges related to the hybrid energy system. Furthermore, a general, system modeling of solar, wind, and grid integration is presented here to give an overall picture of a hybrid renewable energy system. ©2020 Taylor & Francis Group, LLC.

Genome modifications are central components of the continuous arms race between viruses and their hosts. The archaeosine base (G+), which was thought to be found only in archaeal tRNAs, was recently detected in genomic DNA of Enterobacteria phage 9g and was proposed to protect phage DNA from a wide variety of restriction enzymes. In this study, we identify three additional 2′-deoxy-7-deazaguanine modifications, which are all intermediates of the same pathway, in viruses: 2′-deoxy-7-amido-7-deazaguanine (dADG), 2′-deoxy-7-cyano-7-deazaguanine (dPreQ0) and 2′-deoxy-7- aminomethyl-7-deazaguanine (dPreQ1). We identify 180 phages or archaeal viruses that encode at least one of the enzymes of this pathway with an overrepresentation (60%) of viruses potentially infecting pathogenic microbial hosts. Genetic studies with the Escherichia phage CAjan show that DpdA is essential to insert the 7-deazaguanine base in phage genomic DNA and that 2′-deoxy-7-deazaguanine modifications protect phage DNA from host restriction enzymes.

This paper proposes an artificial neural network (ANN) based maximum power point tracking (MPPT) control strategy for wind energy conversion system (WECS) implemented with a DC/DC converter. The proposed topology utilizes a radial basis function network (RBFN) based neural network control strategy to extract the maximum available power from the wind velocity. The results are compared with a classical Perturb and Observe (P&O) method and Back propagation network (BPN) method. In order to achieve a high voltage rating, the system is implemented with a quadratic boost converter and the performance of the converter is validated with a boost and single ended primary inductance converter (SEPIC). The performance of the MPPT technique along with a DC/DC converter is demonstrated using MATLAB/Simulink.

This paper proposes an artificial neural network (ANN) based maximum power point tracking (MPPT) control strategy for wind energy conversion system (WECS) implemented with a DC/DC converter. The proposed topology utilizes a radial basis function network (RBFN) based neural network control strategy to extract the maximum available power from the wind velocity. The results are compared with a classical Perturb and Observe (P&O) method and Back propagation network (BPN) method. In order to achieve a high voltage rating, the system is implemented with a quadratic boost converter and the performance of the converter is validated with a boost and single ended primary inductance converter (SEPIC). The performance of the MPPT technique along with a DC/DC converter is demonstrated using MATLAB/Simulink.

This paper proposes an artificial neural network (ANN) based maximum power point tracking (MPPT) control strategy for wind energy conversion system (WECS) implemented with a DC/DC converter. The proposed topology utilizes a radial basis function network (RBFN) based neural network control strategy to extract the maximum available power from the wind velocity. The results are compared with a classical Perturb and Observe (P&O) method and Back propagation network (BPN) method. In order to achieve a high voltage rating, the system is implemented with a quadratic boost converter and the performance of the converter is validated with a boost and single ended primary inductance converter (SEPIC). The performance of the MPPT technique along with a DC/DC converter is demonstrated using MATLAB/Simulink.

This paper proposes an artificial neural network (ANN) based maximum power point tracking (MPPT) control strategy for wind energy conversion system (WECS) implemented with a DC/DC converter. The proposed topology utilizes a radial basis function network (RBFN) based neural network control strategy to extract the maximum available power from the wind velocity. The results are compared with a classical Perturb and Observe (P&O) method and Back propagation network (BPN) method. In order to achieve a high voltage rating, the system is implemented with a quadratic boost converter and the performance of the converter is validated with a boost and single ended primary inductance converter (SEPIC). The performance of the MPPT technique along with a DC/DC converter is demonstrated using MATLAB/Simulink.

This paper proposes an artificial neural network (ANN) based maximum power point tracking (MPPT) control strategy for wind energy conversion system (WECS) implemented with a DC/DC converter. The proposed topology utilizes a radial basis function network (RBFN) based neural network control strategy to extract the maximum available power from the wind velocity. The results are compared with a classical Perturb and Observe (P&O) method and Back propagation network (BPN) method. In order to achieve a high voltage rating, the system is implemented with a quadratic boost converter and the performance of the converter is validated with a boost and single ended primary inductance converter (SEPIC). The performance of the MPPT technique along with a DC/DC converter is demonstrated using MATLAB/Simulink.