• Energy Research
• mechanical engineering close
• FR close
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Udgivelsesdato: MAY

In Modular Multilevel Converter (MMC) applications, the balancing of the capacitor voltages is one of the most important issues for achieving the proper behavior of the MMC. The Capacitor Voltage Balancing (CVB) control is usually based on classical sorting algorithms which consist of repetitive/recursive loops. This leads to an increase of the execution time when many Sub-Modules (SMs) are employed. When the execution time of the balancing is longer than the sampling period, the proper operation of the MMC cannot be ensured. Moreover, due to their inherent sequential operation, sorting algorithms are suitable for software implementation (microcontrollers or DSPs), but they are not appropriate for a hardware implementation. Instead, in this paper, Sorting Networks (SNs) are proposed due to their convenience for implementation in FPGA devices. The advantages and the main challenges of the Bitonic SN in MMC applications are discussed and different FPGA implementations are presented. Simulation results are provided in normal and faulty conditions. Moreover, a comparison with the widely used bubble sorting algorithm and max/min approach is made in terms of execution time and performance. Finally, hardware-in-the-loop results are shown to prove the effectiveness of the implemented SN.

In this paper, we describe GREENET (an early stage training network in enabling technologies for green radio), which is a new project recently funded by the European Commission under the auspices of the 2010 Marie Curie People Programme. Through the recruitment and personalized training of 17 Early Stage Researchers (ESRs), in GREENET we are committed to the development of new disruptive technologies to address all aspects of energy efficiency in wireless networks, from the user devices to the core network infrastructure, along with the ways the devices and equipment interact with one another. Novel techniques at the physical, link, and network layers to reduce the energy consumption and carbon footprint of 4G devices will be investigated, such as Spatial Modulation (SM) for Multiple-Input-Multiple-Output (MIMO) systems, Cooperative Automatic Repeat reQuest (C-ARQ) protocols, and Network Coding (NC) for lossy networks. Furthermore, cooperation and cognition paradigms will be exploited as additional assets to improve the energy efficiency of wireless networks with the challenging but indispensable constraint of optimizing the system capacity without degrading the user's Quality-of-Service (QoS). Peer Reviewed