298 research outputs found

    A web-based framework for fast synchronization of live video players

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    A delay-based aggregate rate control for P2P streaming systems

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    In this paper we consider mesh based P2P streaming systems focusing on the problem of regulating peer transmission rate to match the system demand while not overloading each peer upload link capacity. We propose Hose Rate Control (HRC), a novel scheme to control the speed at which peers offer chunks to other peers, ultimately controlling peer uplink capacity utilization. This is of critical importance for heterogeneous scenarios like the one faced in the Internet, where peer upload capacity is unknown and varies widely. HRC nicely adapts to the actual peer available upload bandwidth and system demand, so that Quality of Experience is greatly enhanced. To support our claims we present both simulations and actual experiments involving more than 1000 peers to assess performance in real scenarios. Results show that HRC consistently outperforms the Quality of Experience achieved by non-adaptive scheme

    Rotor Current Control Design for DFIG-based Wind Turbine Using PI, FLC and Fuzzy PI Controllers

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    Due to the rising demand for electricity with increasing world population, maximizing renewable energy capture through efficient control systems is gaining attention in literature. Wind energy, in particular, is considered the world’s fastest-growing energy source it is one of the most efficient, reliable and affordable renewable energy sources. Subsequently, well-designed control systems are required to maximize the benefits, represented by power capture, of wind turbines. In this thesis, a 2.0-MW Doubly-Fed Induction Generator (DFIG) wind turbine is presented along with new controllers designed to maximize the wind power capturer. The proposed designs mainly focus on controlling the DFIG rotor current in order to allow the system to operate at a certain current value that maximizes the energy capture at different wind speeds. The simulated model consists of a single two-mass wind turbine connected directly to the power grid. A general model consisting of aerodynamic, mechanical, electrical, and control systems are simulated using Matlab/Simulink. An indirect speed controller is designed to force the aerodynamic torque to follow the maximum power curve in response to wind variations, while a vector controller for current loops is designed to control the rotor side converter. The control system design techniques considered in this work are Proportional-Integral (PI), fuzzy logic, and fuzzy-PI controllers. The obtained results show that the fuzzy-PI controller meets the required specifications by exhibiting the best steady-state response, in terms of steady-state error and settling time, for some DFIG parameters such as rotor speed, rotor currents and electromagnetic torque. Although the fuzzy logic controller exhibits smaller peak overshoot and undershoot values when compared to the fuzzy-PI, the peak value difference is very small, which can be compensated using protection equipment such as circuit breakers and resistor banks. On the other hand, the PI controller shows the highest overshoot, undershoot and settling time values, while the fuzzy logic controller does not meet the requirements as it exhibits large, steady-state error values

    Neuro-Fuzzy Based High-Voltage DC Model to Optimize Frequency Stability of an Offshore Wind Farm

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    Lack of synchronization between high voltage DC systems linking offshore wind farms and the onshore grid is a natural consequence owing to the stochastic nature of wind energy. The poor synchronization results in increased system disturbances, grid contingencies, power loss, and frequency instability. Emphasizing frequency stability analysis, this research investigates a dynamic coordination control technique for a Double Fed Induction Generator (DFIG) consisting of OWFs integrated with a hybrid multi-terminal HVDC (MTDC) system. Line commutated converters (LCC) and voltage source converters (VSC) are used in the suggested control method in order to ensure frequency stability. The adaptive neuro-fuzzy inference approach is used to accurately predict wind speed in order to further improve frequency stability. The proposed HVDC system can integrate multiple distributed OWFs with the onshore grid system, and the control strategy is designed based on this concept. In order to ensure the transient stability of the HVDC system, the DFIG-based OWF is regulated by a rotor side controller (RSC) and a grid side controller (GSC) at the grid side using a STATCOM. The devised HVDC (MTDC) is simulated in MATLAB/SIMULINK, and the performance is evaluated in terms of different parameters, such as frequency, wind power, rotor and stator side current, torque, speed, and power. Experimental results are compared to a conventional optimal power flow (OPF) model to validate the performance.© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed
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