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This paper presents an optimization procedure that enables the optimal dispatching of distributed generators and storage systems in a medium-voltage islanded microgrid. The network is assumed to be supplied by programmable (dispatchable) and nonprogrammable generators (i.e. nondispatchable, such as renewable energy sources—based units). The optimization goal is to minimize the overall microgrid operating cost and the pollutants emission of the programmable generators, assuming that all of the power made available by the renewable generators (photovoltaic and wind systems) is either directly injected into the network or stored in order to be subsequently delivered according to the proposed storage units' management strategy. The optimization is carried out by a niching evolutionary algorithm (NEA) that is able to find multiple optima and the variation of the objective function in their neighborhood. NEAs allow overcoming the performance of standard algorithms used for optimal power-flow calculations in power systems by avoiding falling into local optima. The optimization procedure is performed on a test microgrid and verified by computer simulations. The numerical results show that the solutions can always improve the microgrid performances irrespective of the network operating conditions in all of the considered cases. [ABSTRACT FROM AUTHOR]

This paper presents an innovative generalized systematic approach and related analytical formulation to evaluate distribution system reliability in smart grids where islanded operation of microgrids helps to improve local and overall reliability. In order to do this, the analytical formulation involves the adequacy calculation of conventional and renewable distributed generators supplying microgrids by using probabilistic models. Adequacy is computed by means of a new general analytical expression which takes into account load shedding (user load disconnection) and curtailment (user load reduction) policies. [ABSTRACT FROM PUBLISHER]

Keen interest in the development and utilization of renewable distributed generation (DG) has been currently observed worldwide. The reliability impact of this highly variable energy source is an important aspect that needs to be assessed as renewable power penetration becomes increasingly significant. Distribution system adequacy assessment including wind-based and solar DG units during different modes of operation is described in this paper. Monte Carlo simulation (MCS) and analytical technique are used in this work with a novel utilization of the clearness index probability density function (pdf) to model the solar irradiance using MCS. The results show that there is no significant difference between the outcomes of the two proposed techniques; however, MCS requires much longer computational time. The effect of islanding appears in the improvement of the loss of load expectation (LOLE) and loss of energy expectation (LOEE). [ABSTRACT FROM PUBLISHER]

Long high critical current density Bi-2223/Ag tapes are required for the realization of cables and windings to be integrated in electric power devices. A cooperation agreement among CISE SpA, Europa Metalli and INFN, concerns the development of silver-sheathed multifilamentary Bi-2223/Ag tapes, over 100 meters long, produced by means of the Powder-In-Tube (PIT) technique. The Bi-2223/Ag tapes were thermomechanically processed and then wound into double pancakes by the React and Wind method. This article presents and discusses the electrical and magnetic characterization of the tapes, their degradation after winding as well as the performances of the pancakes tested after the final assembling. [ABSTRACT FROM PUBLISHER]

Proprioceptive feedback is a critical component of voluntary movement planning and execution. Neuroprosthetic technologies aiming at restoring movement must interact with it to restore accurate motor control. Optimization and design of such technologies depends on the availability of quantitative insights into the neural dynamics of proprioceptive afferents during functional movements. However, recording proprioceptive neural activity during unconstrained movements in clinically relevant animal models presents formidable challenges. In this work, we developed a computational framework to estimate the spatiotemporal patterns of proprioceptive inputs to the cervical spinal cord during three-dimensional arm movements in monkeys. We extended a biomechanical model of the monkey arm with ex-vivo measurements, and combined it with models of mammalian group-Ia, Ib and II afferent fibers. We then used experimental recordings of arm kinematics and muscle activity of two monkeys performing a reaching and grasping task to estimate muscle stretches and forces with computational biomechanics. Finally, we projected the simulated proprioceptive firing rates onto the cervical spinal roots, thus obtaining spatiotemporal maps of spinal proprioceptive inputs during voluntary movements. Estimated maps show complex and markedly distinct patterns of neural activity for each of the fiber populations spanning the spinal cord rostro-caudally. Our results indicate that reproducing the proprioceptive information flow to the cervical spinal cord requires complex spatio-temporal modulation of each spinal root. Our model can support the design of neuroprosthetic technologies as well as in-silico investigations of the primate sensorimotor system.

Rodent models are decisive for translational research in healthy and pathological conditions of motor function thanks to specific similarities with humans. Here, we present an upgraded version of the M-Platform, a robotic device previously designed to train mice during forelimb retraction tasks. This new version significantly extends its possibilities for murine experiments during motor tasks: 1) an actuation system for friction adjustment allows to automatically adapt pulling difficulty; 2) the device can be used both for training, with a retraction task, and for assessment, with an isometric task; and 3) the platform can be integrated with a neurophysiology systems to record simultaneous cortical neural activity. Results of the validation experiments with healthy mice confirmed that the M-Platform permits precise adjustments of friction during the task, thus allowing to change its difficulty and that these variations induce a different improvement in motor performance, after specific training sessions. Moreover, simultaneous and high quality (high signal-to-noise ratio) neural signals can be recorded from the rostral forelimb area (RFA) during task execution. With the novel features presented herein, the M-Platform may allow to investigate the outcome of a customized motor rehabilitation protocol after neural injury, to analyze task-related signals from brain regions interested by neuroplastic events and to perform optogenetic silencing or stimulation during experiments in transgenic mice.