2017
Autores
Santos, MS; Soares, JP; Abreu, PH; Araújo, H; Santos, JAM;
Publicação
Artificial Intelligence in Medicine - 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings
Abstract
2017
Autores
Lima dos Reis Marques, F; Floridia, C; Alves Almeida, T; Leonardi, AA; Fruett, F;
Publicação
2017 SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference (IMOC)
Abstract
2017
Autores
Rodrigues, LM; Montez, C; Vasques, F; Portugal, P;
Publicação
Communications in Computer and Information Science
Abstract
Energy consumption is a major concern in Wireless Sensor Networks (WSNs) since nodes are powered by batteries. Usually, batteries have low capacity and can not be replaced due to economic and/or logistical issues. In addition, batteries are complex devices as they depend on electrochemical reactions to generate energy. As a result, batteries exhibit non-linear behaviour over time, which makes difficult to estimate their lifetime. Analytical battery models are abstractions that allow estimating the battery lifetime through mathematical equations, taking into account important effects such as rate capacity and charge recovery. The recovery effect is very important since it enables charge gains in the battery after its electrochemical stabilization. Sleep scheduling approaches may take advantage of the recovery effect by adding sleep periods in the node activities in order to extend the network lifetime. This work aims to analyse the recovery effect within WSN context, particularly regarding low-power nodes. To do so, we use an analytical battery model for analysing the battery performance over time, during the node execution. © Springer International Publishing AG 2017.
2017
Autores
Moerman, Joshua; Sammartino, Matteo; Silva, Alexandra; Klin, Bartek; Szynwelski, Michal;
Publicação
Proceedings of the 44th ACM SIGPLAN Symposium on Principles of Programming Languages, POPL 2017, Paris, France, January 18-20, 2017
Abstract
2017
Autores
Mehrasa, M; Pouresmaeil, E; Zabihi, S; Catalao, JPS;
Publicação
IEEE TRANSACTIONS ON POWER DELIVERY
Abstract
A control technique is proposed in this paper for control of modular multilevel converters (MMC) in high-voltage direct current (HVDC) transmission systems. Six independent dynamical state variables are considered in the proposed control technique, including two ac currents, three circulating currents, and the dc-link voltage, for effectively attaining the switching state functions of MMCs, as well as for an accurate control of the circulating currents. Several analytical expressions are derived based on the reference values of the state variables for obtaining the MMC switching functions under steady state operating conditions. In addition, dynamic parts of the switching functions are accomplished by the direct Lyapunov method to guarantee stable operation of the proposed technique for control of MMCs in HVDC systems. Moreover, the capability curve of MMC is developed to validate maximum power injection from MMCs into the power grid and/or loads. The impacts of the variations of MMC output and dc-link currents on the stability of dc-link voltage are also evaluated in detail by small-signal analysis.
2017
Autores
Figueiredo, A;
Publicação
The Open Statistics & Probability Journal
Abstract
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