A Cognitive Social IoT Approach for Smart Energy Management in a Real Environment

Energy usage inside buildings is a critical problem, especially considering high loads such as Heating, Ventilation and Air Conditioning (HVAC) systems: around 50% of the buildings’ energy demand resides in HVAC usage which causes a significant waste of energy resources due to improper uses. Usage awareness and efficient management have the potential to reduce related costs. However, strict saving policies may contrast with users’ comfort. In this sense, this paper proposes a multi-user multi-room smart energy management approach where a trade-off between the energy cost and the users’ thermal comfort is achieved. The proposed user-centric approach takes advantage of the novel paradigm of the Social Internet of Things to leverage a social consciousness and allow automated interactions between objects. Accordingly, the system automatically obtains the thermal profiles of both rooms and users. All these profiles are continuously updated based on the system experience and are then analysed through an optimization model to drive the selection of the most appropriate working times for HVACs. Experimental results in a real environment demonstrated the cognitive behaviour of the system which can adapt to users’ needs and ensure an acceptable comfort level while at the same time reducing energy costs compared to traditional usage

Identification of Test Structures for Reduced Order Modeling of the Squeeze Film Damping in Mems

In this study the dynamic behaviour of perforated microplates oscillating under the effect of squeeze film damping is analyzed. A numerical approach is adopted to predict the effects of damping and stiffness transferred from the surrounding ambient air to oscillating structures ; the effect of hole's cross section and plate's extension is observed. Results obtained by F.E.M. models are compared with experimental measurements performed by an optical interferometric microscope.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/EDA-Publishing

Comparison between piezoelectric and magnetic strategies for wearable energy harvesting

This paper introduces the design and fabrication of energy harvesters for the power generation from human body motion. Two alternative strategies are compared: piezoelectric and magnetic inductive. The generated energy is used to supply body sensors including accelerometers and temperature sensors and RF module. Two prototypes of the magnetic based generator and of the piezoelectric generator are built and tested with shaker at resonance condition and by dedicated bench reproducing joints rotation during walking. The experimental results show that the magnetic prototype can generate 0.7mW from human body motion, while the piezo harvester generates 0.22 and 0.33μW respectively for flexion and extension at angular velocity lower than 1rad/s and 45° amplitude

Chiral Properties of QCD Vacuum in Magnetars- A Nambu-Jona-Lasinio Model with Semi-Classical Approximation

The breaking of chiral symmetry of light quarks at zero temperature in presence of strong quantizing magnetic fiels is studied using Nambu-Jona-Lasinio (NJL) model with Thomas-Fermi type semi-classical formalism. It is found that the dynamically generated light quark mass can never become zero if the Landau levels are populated and the mass increases with the increase of magnetic field strength.Comment: REVTEX 11 Pages, One .eps figure (included

Resonate and fire dynamics in Complex Oscillation Based Test of analog filters

Recently, proposals have been made for enhancing the Oscillation Based Test (OBT) methodology by using non-plain oscillation regimes, leading to so called Complex Oscillation Based Test (COBT). Here we focus on a recently illustrated strategy for the testing of analog 2nd order filters, showing that the COBT dynamics is quite similar to that expressed by Resonate & Fire (R+F) neuron models. In this interpretation, the testing approach can be related to firing-rate measures. A brief description is given of the mathematical models necessary to achieve a precise characterization of firing times, showing how it can be used for testing purposes. A practical example with simulation data is also provided. © 2011 IEEE

Synthetic models of distribution networks based on open data and georeferenced information

Many planning and operation studies that aim at fully assessing and optimizing the performance of the distribution grids, in response to the current trends, cannot ignore grid limitations. Modelling the distribution system, by including the electrical characteristics of the network (e.g., topology) and end user behaviors, has become complex, but essential, for all conventional and emerging actors/players of power systems (i.e., system and market operators, regulators, new market parties as service providers, aggregators, researchers, etc.). This paper deals with a methodology that, starting from publicly available open data on the energy consumption of a region or wider area, is capable to obtain reasonable load and generation profiles for the network supplied by each primary substation in the region/area. Furthermore, by combining these profiles with territorial and socio-economic information, the proposed methodology is able to model the network in terms of lines, conductors, loads and generators. The results of this procedure are the synthetic networks of the real distribution networks, that do not correspond exactly to the actual networks, but can characterize them in a realistic way. Such models can be used for all the kind of optimization studies that need to check the grid limitations. Results derived from Italian test cases are presented and discussed