130,735 research outputs found
Microgrids-Based Approach for Voltage Control in Distribution Systems by an Efficient Sensitivity Analysis Method
No full textHigh levels of renewable energy sources (RESs) in distribution networks have led to complex operational needs. The management of the network in microgrids (MGs) allows the implementation of effective and innovative management strategies. We propose a hybrid control strategy to maintain voltage levels within the operational limits using the RESs reactive and active power outputs. The proposed regulation strategy considers different MGs that are managed by different owners, who contribute to regulating the voltage on the distribution systems. In order to obtain an effective regulation, each MG can collaborate with the others. In the first instance, voltage is regulated inside MG using available distributed generation resources in correspondence of the bus of over/undervoltage is detected (stage 1). Next, more MGs can contribute to alleviating the problem involving other distributed generation resources (stage 2). The control method is based on sensitivity analysis, which allows selecting the appropriate distributed resources: we propose also a new method of calculating the sensitivity coefficients for radial and meshed networks. We demonstrate the effectiveness and the robustness of the proposed voltage control scheme using comparisons and representative studies by extensive simulations on two test networks performed by the proposed methodology. The results demonstrate the effectiveness of the control actions and the used algorithm
An enterprise rights management system for on-the-field maintenance facilities
No full textOn-the-field maintenance of complex equipments, that may involve multiple subjects and stakeholders, is one of most challenging scenarios for Enterprise Rights Management (ERM). In this paper, we present an ERM system that guarantees the 'on-site' protection of information confidentiality. In particular, our system features local data encryption and minimal data transfers. A secure key management protocol is executed by the devices operating on-site and the remote manufacturer's support center and guarantees an efficient and dynamic enforcement of arbitrary data-provider-defined access policies. Operator identities are verified by means of strong multi-biometric verification schemes whilst protecting their biometries by means of cancelable biometries. To this end, we provide the first experimental evaluation of cancelable biometrics based on the fusion of face and voice biometries, that may be of independent interest
Voltage regulation in MV networks with dispersed generations by a neural-based multiobjective methodology
No full textThis paper puts forward the role of learning techniques in addressing the problem of an efficient and optimal centralized voltage control in distribution networks equipped with dispersed generation systems (DGSs). The proposed methodology employs a radial basis function network (RBFN) to identify the multidimensional nonlinear mapping between a vector of observable variables describing the network operating point and the optimal set points of the voltage regulating devices. The RBFN is trained by numerical data generated by solving the voltage regulation problem for a set of network operating points by a rigorous multiobjective solution methodology. The RBFN performance is continuously monitored by a supervisor process that notifies when there is the need of a more accurate solution of the voltage regulation problem if nonoptimal network operating conditions (expost monitoring) or excessive distances between the actual network state and the neuron's centres (ex ante monitoring) are detected. A more rigorous problem solution, if required, can be obtained by solving the voltage regulation problem by a conventional multiobjective optimization technique. This new solution, in conjunction with the corresponding input vector, is then adopted as a new train data sample to adapt the RBFN. This online training process allows RBFN to (i) adaptively learn the more representative domain space regions of the input/output mapping without needing a prior knowledge of a complete and representative training set, and (ii) manage effectively any time varying phenomena affecting this mapping. The results obtained by simulating the regulation policy in the case of a medium-voltage network are very promising. (c) 2007 Elsevier B.V. All rights reserved
Voltage regulation in MV networks with dispersed generations by a neural based multiobjective methodology
No full textExploiting the Temporal Dimension of Reconfigurable Intelligent Surfaces for Multiuser Downlink
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FIRME: Face and Iris Recognition for Mobile Engagement
No full textMobile devices, namely phones and tablets, have long gone "smart". Their growing use is both a cause and an effect of their technological advancement. Among the others, their increasing ability to store and exchange sensitive information, has caused interest in exploiting their vulnerabilities, and the opposite need to protect users and their data through secure protocols for access and identification on mobile platforms. Face and iris recognition are especially attractive, since they are sufficiently reliable, and just require the webcam normally equipping the involved devices. On the contrary, the alternative use of fingerprints requires a dedicated sensor. Moreover, some kinds of biometrics lend themselves to uses that go beyond security. Ambient intelligence services bound to the recognition of a user, as well as social applications, such as automatic photo tagging on social networks, can especially exploit face recognition. This paper describes FIRME (Face and Iris Recognition for Mobile Engagement) as a biometric application based on a multimodal recognition of face and iris, which is designed to be embedded in mobile devices. Both design and implementation of FIRME rely on a modular architecture, whose workflow includes separate and replaceable packages. The starting one handles image acquisition. From this point, different branches perform detection, segmentation, feature extraction, and matching for face and iris separately. As for face, an antispoofing step is also performed after segmentation. Finally, results from the two branches are fused. In order to address also security-critical applications, FIRME can perform continuous reidentification and best sample selection. To further address the possible limited resources of mobile devices, all algorithms are optimized to be low-demanding and computation-light. © 2014 Elsevier B.V. All rights reserved
Developing a Reciprocating Mechanism for the Emergency Implementation of a Mechanical Pulmonary Ventilator using an Integrated CAD-MBD Procedure
No full textFollowing the COVID-19 outbreak, the redesign of an emergency mechanical pulmonary ventilator that is cheap and easily portable became necessary in several contexts, such as emergency hotspots and environments with poor resources. To address this important issue, a general multibody approach is employed in this paper to develop a reciprocating mechanism suitable for retrofitting the existing manual mechanical ventilators through computer-aided engineering tools. By analyzing various basic articulated mechanisms typically found in engineering mechanics, a prototype is created and reproduced in a threedimensional environment using SOLIDWORKS's CAD software. Subsequently, a high-fidelity mechanical model is developed starting from the CAD geometry and employing the SIMSCAPE MULTIBODY software, an extension of the MATLAB family of programs that can effectively and efficiently perform kinematic and dynamic simulations of the mechanism of interest. As discussed in the paper, by carrying out numerous numerical experiments, the virtual simulations predict several fundamental medical parameters, such as the airflow introduced into patients, the respiratory rate, and the respiratory ratio
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