A medium-frequency transformer with multiple secondary windings for grid connection through H-bridge voltage source converters

Although the power output of today's wind turbine has exceeded 7 MW, the voltage rating of the most common generator is below 700 V. A low-frequency transformer is commonly used to step-up the voltage to the grid voltage level, e.g. 11 kV or 33 kV. These heavy and bulky low-frequency transformers significantly increase the volume and weight of nacelle. To achieve a compact and light nacelle, a medium-voltage converter with series-connected H-bridge (SCHB) topology would be an attractive technology for future wind turbines. However, the SCHB converter requires multiple isolated and balanced DC sources, which makes the application not straightforward. As an alternative approach to generate multiple isolated and balanced sources a prototype transformer with six secondary windings, 1.26 kVA and 10 kHz, is designed and developed for 1 kV five levels SCHB multilevel converters. The experimental results show that the proposed system may be attractive in grid based renewable energy systems. © 2012 IEEJ Industry Appl Soc

FPGA-based control of modular multilevel converters: Modeling and experimental evaluation

© 2015 IEEE. In comparison with conventional two level converters, multilevel converters present lower switching losses, lower voltage stress on switching devices, lower common-mode voltages and better harmonic performance. Due to these remarkable features, nowadays the application of this technology covers a wide range, where high-quality voltages and currents are required. However, the multilevel converter requires a number of switching pulse width modulated (PWM) signals, which cannot be generated by using a single digital signal processor (DSP)/microcontroller because the available DSP at present only can provide about 12 PWM channels. In this instance, the field programmable gate array (FPGA) is the natural choice to develop the control circuit of multilevel converters. In addition, the most common software such as MATLAB/Simulink and Xilinx ISE Design Suite-based alternative design technique is used in this paper, which may reduce the developmental time and cost of the controller. The design and implementation of the switching controller, test platform, and experimental results are analyzed and discussed

A multilevel medium-voltage inverter for step-up-transformer-less grid connection of photovoltaic power plants

Recently, medium (0.1-5 MW) and large (>5 MW) scale photovoltaic (PV) power plants have attracted great attention, where medium-voltage grid connection (typically 6-36 kV) is essential for efficient power transmission and distribution. A power frequency transformer operated at 50 or 60 Hz is generally used to step up the traditional inverter's low output voltage (usually ≤400 V) to the medium-voltage level. Because of the heavy weight and large size of the power frequency transformer, the PV inverter system can be expensive and complex for installation and maintenance. As an alternative approach to achieve a compact and lightweight direct grid connection, this paper proposes a three-phase medium-voltage PV inverter system. The 11-kV and 33-kV PV inverter systems are designed. A scaled down three-phase 1.2-kV test rig has been constructed to validate the proposed PV inverter. The experimental results are analyzed and discussed, taking into account the switching schemes and filter circuits. The experimental results demonstrate the excellent feature of the proposed PV inverter system. © 2011-2012 IEEE

Optimal design of high-frequency magnetic links for power converters used in grid-connected renewable energy systems

© 2014 IEEE. Recently high-frequency common magnetic links with cores of advanced magnetic materials, such as nanocrystalline and amorphous materials, have been considered as viable candidates for the development of medium-voltage power converters. This offers a new route of step-up-transformer-less compact and lightweight direct grid integration of renewable generation systems. Most importantly, it minimizes the voltage imbalance and common mode issues of the converter systems. However, the electromagnetic design of high-frequency common magnetic links is a multiphysics problem and thereby affects the system efficiency and cost. In this paper, an optimization technique is proposed and verified by prototype magnetic links. The design optimization, implementation, test platform, and experimental test results are analyzed and discussed

Recent developments of MCViNE and its applications at SNS

MCViNE is an open source, object-oriented Monte Carlo neutron ray-tracing simulation software package. Its design allows for flexible, hierarchical representations of sophisticated instrument components such as detector systems, and samples with a variety of shapes and scattering kernels. Recently this flexible design has enabled several applications of MCViNE simulations at the Spallation Neutron Source (SNS) at Oak Ridge National Lab, including assisting design of neutron instruments at the second target station and design of novel sample environments, as well as studying effects of instrument resolution and multiple scattering. Here we provide an overview of the recent developments and new features of MCViNE since its initial introduction (Jiao et al 2016 Nucl. Instrum. Methods Phys. Res., Sect. A 810, 86–99), and some example applications

An Improved Slant Path Attenuation Prediction Method in Tropical Climates

An improved method for predicting slant path attenuation in tropical climates is presented in this paper. The proposed approach is based on rain intensity data R_0.01 (mm/h) from 37 tropical and equatorial stations; and is validated by using the measurement data from a few localities in tropical climates. The new method seems to accurately predict the slant path attenuation in tropical localities, and the comparative tests seem to show significant improvement in terms of the RMS of the relative error variable compared to the RMS obtained with the SAM, Crane, and ITU-R prediction models

Variational Inference for a Recommendation System in IoT Networks Based on Stein’s Identity

The recommendation services are critical for IoT since they provide interconnection between various devices and services. In order to make Internet searching convenient and useful, algorithms must be developed that overcome the shortcomings of existing online recommendation systems. Therefore, a novel Stein Variational Recommendation System algorithm (SVRS) is proposed, developed, implemented and tested in this paper in order to address the long-standing recommendation problem. With Stein’s identity, SVRS is able to calculate the feature vectors of users and ratings it has generated, as well as infer the preference for users who have not rated certain items. It has the advantages of low complexity, scalability, as well as providing insights into the formation of ratings. A set of experimental results revealed that SVRS performed better than other types of recommendation methods in root mean square error (RMSE) and mean absolute error (MAE)

A New Isolated Multi-Port Converter With Multi-Directional Power Flow Capabilities for Smart Electric Vehicle Charging Stations

© 2018 IEEE. If the batteries are charged by clean renewable energy sources, electric vehicles (EVs) can have zero gas emission, contributing greatly toward the preservation of the green environment. In a smart micro-grid, EVs together with other distributed energy storage units can be used to supply electricity to the loads during the peak hours so as to minimize the effects of the load shedding and improve the quality of electricity. To achieve these goals, an isolated hybrid multi-port converter is required to control the power flows and balance the energy among renewable energy sources, EVs, and the grid. In this paper, a new isolated multi-port converter is proposed, which can control the power flow in multiple directions. The converter is modeled in the matlab/Simulink software environment and this validates the technology with a laboratory prototype test platform. The modeling, implementation, and results are discussed comprehensively

An Amorphous Alloy Magnetic-Bus-Based SiC NPC Converter with Inherent Voltage Balancing for Grid-Connected Renewable Energy Systems

© 2002-2011 IEEE. This paper presents an amorphous alloy magnetic-bus-based neutral point clamped (NPC) converter for grid-connected renewable generation systems. In the proposed system, the amorphous alloy high-frequency high-power density multi-winding magnetic bus generates balanced dc supplies for the five-level (5L) NPC converter for high-quality power conversion. Compared to the traditional NPC converter topologies, the proposed magnetic-bus-based architecture does not require any control circuit for voltage balancing of the series connected capacitors. The magnetic bus inherently overcomes galvanic isolation issues and may reduce the size of the boosting inductor. In this paper, a finite control set model predictive control algorithm is derived to control the grid-connected 5L-NPC inverter for multilevel voltage synthesizing, while achieving the user-defined active and reactive power values. To verify the proposed concept, a simulation model is developed and analyzed in MATLAB/Simulink environment. To validate the technology, a scale d-down prototype test platform is developed in the laboratory with silicon carbide switching devices, which achieves high blocking voltage, low power dissipation, high switching frequency, and high-Temperature operation. Based on the simulation and the experimental results, it is expected that the proposed converter will have a great potential for widespread application in renewable generation systems including superconducting generator-based wind turbines

A Double-Layer Blockchain Based Trust Management Model for Secure Internet of Vehicles

The Internet of Vehicles (IoV) enables vehicles to share data that help vehicles perceive the surrounding environment. However, vehicles can spread false information to other IoV nodes; this incorrect information misleads vehicles and causes confusion in traffic, therefore, a vehicular trust model is needed to check the trustworthiness of the message. To eliminate the spread of false information and detect malicious nodes, we propose a double-layer blockchain trust management (DLBTM) mechanism to objectively and accurately evaluate the trustworthiness of vehicle messages. The double-layer blockchain consists of the vehicle blockchain and the RSU blockchain. We also quantify the evaluation behavior of vehicles to show the trust value of the vehicle’s historical behavior. Our DLBTM uses logistic regression to accurately compute the trust value of vehicles, and then predict the probability of vehicles providing satisfactory service to other nodes in the next stage. The simulation results show that our DLBTM can effectively identify malicious nodes, and over time, the system can recognize at least 90% of malicious nodes