999 resultados para unbalanced Feistel network
Resumo:
从可证明安全的角度研究使用压缩函数的非平衡Feistel结构(UFN-C)的安全性,证明了k+1轮UFN-C是伪随机的,k+2轮UFN-C是超伪随机的;进一步地,探讨了UFN-C的有效构造,降低了Naor和Reingold在1999年文章中类似结构对伪随机函数个数的要求.最后,针对一类具体的UFN-C--SMs4,分析其广义形式SMS4-like结构的伪随机性和超伪随机性,为设计与使用该类结构的分组密码提供了可证明安全的理论依据.
Resumo:
The objective of this report is to study distributed (decentralized) three phase optimal power flow (OPF) problem in unbalanced power distribution networks. A full three phase representation of the distribution networks is considered to account for the highly unbalance state of the distribution networks. All distribution network’s series/shunt components, and load types/combinations had been modeled on commercial version of General Algebraic Modeling System (GAMS), the high-level modeling system for mathematical programming and optimization. The OPF problem has been successfully implemented and solved in a centralized approach and distributed approach, where the objective is to minimize the active power losses in the entire system. The study was implemented on the IEEE-37 Node Test Feeder. A detailed discussion of all problem sides and aspects starting from the basics has been provided in this study. Full simulation results have been provided at the end of the report.
Resumo:
A new technique is presented for automatically identifying the phase connection of domestic customers. Voltage information from a reference three phase house is correlated with voltage information from other customer electricity meters on the same network to determine the highest probability phase connection. The techniques are purely based upon a time series of electrical voltage measurements taken by the household smart meters and no additional equipment is required. The method is demonstrated using real smart meter datasets to correctly identify the phase connections of 75 consumers on a low voltage distribution feeder.
Resumo:
This paper presents an Artificial Neural Network (ANN) approach for locating faults in distribution systems. Different from the traditional Fault Section Estimation methods, the proposed approach uses only limited measurements. Faults are located according to the impedances of their path using a Feed Forward Neural Networks (FFNN). Various practical situations in distribution systems, such as protective devices placed only at the substation, limited measurements available, various types of faults viz., three-phase, line (a, b, c) to ground, line to line (a-b, b-c, c-a) and line to line to ground (a-b-g, b-c-g, c-a-g) faults and a wide range of varying short circuit levels at substation, are considered for studies. A typical IEEE 34 bus practical distribution system with unbalanced loads and with three- and single- phase laterals and a 69 node test feeder with different configurations are considered for studies. The results presented show that the proposed approach of fault location gives close to accurate results in terms of the estimated fault location.
Resumo:
Low voltage distribution networks feature a high degree of load unbalance and the addition of rooftop photovoltaic is driving further unbalances in the network. Single phase consumers are distributed across the phases but even if the consumer distribution was well balanced when the network was constructed changes will occur over time. Distribution transformer losses are increased by unbalanced loadings. The estimation of transformer losses is a necessary part of the routine upgrading and replacement of transformers and the identification of the phase connections of households allows a precise estimation of the phase loadings and total transformer loss. This paper presents a new technique and preliminary test results for a method of automatically identifying the phase of each customer by correlating voltage information from the utility's transformer system with voltage information from customer smart meters. The techniques are novel as they are purely based upon a time series of electrical voltage measurements taken at the household and at the distribution transformer. Experimental results using a combination of electrical power and current of the real smart meter datasets demonstrate the performance of our techniques.
Resumo:
This paper proposes a coordinated control of the rotor and grid side converters (RSC & GSC) of doubly-fed induction generator (DFIG) based wind generation systems under unbalanced voltage conditions. System behaviors and operations of the RSC and GSC under unbalanced voltage are illustrated. To provide enhanced operation, the RSC is controlled to eliminate the torque oscillations at double supply frequency under unbalanced stator supply. The oscillation of the stator output active power is then cancelled by the active power output from the GSC, to ensure constant active power output from the overall DFIG generation system. To provide the required positive and negative sequence currents control for the RSC and GSC, a current control strategy containing a main controller and an auxiliary controller is analyzed. The main controller is implemented in the positive (dq)+ frame without involving positive/negative sequence decomposition whereas the auxiliary controller is implemented in the negative sequence (dq)? frame with negative sequence current extracted. Simulation results using EMTDC/PSCAD are presented for a 2MW DFIG wind generation system to validate the proposed control scheme and to show the enhanced system operation during unbalanced voltage supply.
Resumo:
This paper investigates the control and operation of doubly-fed induction generator (DFIG) and fixed-speed induction generator (FSIG) based wind farms under unbalanced grid conditions. A DFIG system model suitable for analyzing unbalanced operation is developed, and used to assess the impact of an unbalanced supply on DFIG and FSIG operation. Unbalanced voltage at DFIG and FSIG terminals can cause unequal heating on the stator windings, extra mechanical stresses and output power fluctuations. These problems are particularly serious for the FSIG-based wind farm without a power electronic interface to the grid. To improve the stability of a wind energy system containing both DFIG and FSIG based wind farms during network unbalance, a control strategy of unbalanced voltage compensation by the DFIG systems is proposed. The DFIG system compensation ability and the impact of transmission network impedance are illustrated. The simulation results implemented in Matlab/Simulink show that the proposed DFIG control system improves not only its own performance, but also the stability of the FSIG system with the same grid connection point during network unbalance.
Resumo:
This paper assesses the impact of the location and configuration of Battery Energy Storage Systems (BESS) on Low-Voltage (LV) feeders. BESS are now being deployed on LV networks by Distribution Network Operators (DNOs) as an alternative to conventional reinforcement (e.g. upgrading cables and transformers) in response to increased electricity demand from new technologies such as electric vehicles. By storing energy during periods of low demand and then releasing that energy at times of high demand, the peak demand of a given LV substation on the grid can be reduced therefore mitigating or at least delaying the need for replacement and upgrade. However, existing research into this application of BESS tends to evaluate the aggregated impact of such systems at the substation level and does not systematically consider the impact of the location and configuration of BESS on the voltage profiles, losses and utilisation within a given feeder. In this paper, four configurations of BESS are considered: single-phase, unlinked three-phase, linked three-phase without storage for phase-balancing only, and linked three-phase with storage. These four configurations are then assessed based on models of two real LV networks. In each case, the impact of the BESS is systematically evaluated at every node in the LV network using Matlab linked with OpenDSS. The location and configuration of a BESS is shown to be critical when seeking the best overall network impact or when considering specific impacts on voltage, losses, or utilisation separately. Furthermore, the paper also demonstrates that phase-balancing without energy storage can provide much of the gains on unbalanced networks compared to systems with energy storage.
Resumo:
This article deals with classification problems involving unequal probabilities in each class and discusses metrics to systems that use multilayer perceptrons neural networks (MLP) for the task of classifying new patterns. In addition we propose three new pruning methods that were compared to other seven existing methods in the literature for MLP networks. All pruning algorithms presented in this paper have been modified by the authors to do pruning of neurons, in order to produce fully connected MLP networks but being small in its intermediary layer. Experiments were carried out involving the E. coli unbalanced classification problem and ten pruning methods. The proposed methods had obtained good results, actually, better results than another pruning methods previously defined at the MLP neural network area. (C) 2014 Elsevier Ltd. All rights reserved.
Resumo:
A six inputs and three outputs structure which can be used to obtain six simultaneous beams with a triangular array of 3 elements is presented. The beam forming network is obtained combining balanced and unbalanced hybrid couplers and allows to obtain six main beams with sixty degrees of separation in azimuth direction. Simulations and measurements showing the performance of the array and other detailed results are presented