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Orthoniobates of rare-earth elements are a promising group of materials attractive for the design of nanocomposite hydrogen separation membranes owing to a perspective type of proton conductivity, good mechanical properties, and high stability in H2O- and CO2-containing atmospheres. In general, the promising method involves the synthesis of nanocomposites with transition metals (Cu, Ni, and Cu-Ni alloys) and their oxides with high electronic conductivity. For the first time, lanthanum orthoniobates and nanocomposites with NiCu and NiCo nanoparticles were synthesized using alcohol solutions of salts of the corresponding metals by the solvothermal method in a flow reactor in a supercritical isopropanol medium. This method made it possible to obtain single-phase La0.99Ca0.01NbO4–δ oxide. The introduction of doping titanium cations did not allow obtaining a single-phase La0.99Ca0.01Nb0.98Ti0.02O4–δ sample, as impurities in lanthanum methaniobate and La2Ti2O7 were found. Calcined powders and gastight pellets of orthoniobates and nanocomposites were characterized by X-ray diffraction analysis as well as scanning and transmission electron microscopy. Transport characteristics were investigated by the Van der Pauw technique, varying measurement temperatures in a wet H2 atmosphere. The oxygen mobility was estimated by the oxygen isotope heteroexchange with C18O2.

The purpose of this work is to provide theoretical framework and experimental supporting evidence for a crucial role of structural transitions in the ensemble of defects at the meso-level (microshears and microcracks), as one of the mechanisms of plastic strain localization in metals under high-rate loading. The investigation of the sample response to dynamic loading was carried out on the split Hopkinson pressure bar and in a series of target penetration tests. To identify the characteristic stages of strain localization, the thermodynamics of the deformation process was investigated "in-situ" by recording the temperature fields using a high-speed infrared camera CEDIP Silver 450M. The temperature measured in the localization zone does not confirm the generally accepted concept of the strain localization mechanism as the mechanism governed by a thermoplastic instability. The samples stored after the experiment were subjected to microstructural analysis, using an optical interferometer-profilometer and a scanning electron microscope. The structural analysis revealed a correlated behavior of the ensemble of defects, which can be classified as a structural transition providing strain localization. The data of experimental studies, the examination of the structure of deformed samples, as well as the data of numerical modeling taking into account the kinetics of accumulation of microdefects in the material suggest that one of the mechanisms of plastic strain localization at high loading rates is associated with the jump-like processes in the defect structure of a material.

Real-time knowledge about the energy being exchanged sustains energy efficiency applications and services. The event-based data-saving approach to the measurements of electric energy has emerged recently with conceptual and practical implications, also thanks to the manufacturing of a new technological solution. This paper explains the fundamental underlying concepts that have led to these improvements through real-case examples. This work borrows from ontology the distinction between the concepts of endurants and perdurants, associating these concepts to the quantities involved in the energy metering process. In the new event-based computational framework, energy metering is interpreted by detecting average power and accumulated energy variations, as well as highlighting the importance of the information provided by the rate of change of energy and by the rate of events gathered from meters.

Climate change dramatically impacts the structure of energy business by adding renewables. In traditional energy networks, the balance between the demand for- and the offer of- power is managed by increasing the amount of commodity or by shedding loads. Customer-centered grid brings new paradigm about changing the economic behavior of small- and medium- scaled energy users instead of varying the amounts of commodity that is called flexibility. Flexible cooperative behavior of many actors participating in liberalized intraday market reduces pollutants because it optimizes renewable energy. However, it has implications on power markets in terms of prices and has technology implications nation-wide. This article discusses a generational change that moves decision making from few control rooms to the democratic neighborhood of the web. The objective is to present a changed socio-economic context and attract the attention of researcher to new challenges. The main result is a dynamic equilibrium that exists between the reward offered by the utilities to their customers and the advantage obtained by the utilities from such a flexible behavior. The article main conclusion is on the role of new market product called demand-side flexibility in the transformation of power markets towards ecological sustainability. Key words: Demand-side flexibility, energy market, intraday trading.

Recent developments in smart metering applications have led to the conceptualization and construction of a new type of energy meter, operating on the basis of event-driven principles. The event-driven metering concepts are applied to represent the information on the electrical load patterns, which have an integral value. This paper explains why these concepts are different from the ones used for event-based applications in other domains, discusses the principles used in the new type of electricity meter, presents the data formats structured in such a way to provide detailed knowledge representation, and shows a number of results on real-case applications. A specific index is defined in order to represent the effectiveness of the event-driven metering scheme illustrated to represent the details of the metered pattern, comparing the results with the ones that could be reached in the most favorable case through regular timer-driven metering. The presentation of specific applications based on real-life datasets highlights the advantages of the event-driven energy metering over the traditional timer-driven metering scheme.

Event-driven metering is an emergent paradigm enabling significant data compression enhancement with respect to the conventional time domain metering techniques. This paper first discusses the representation of energy-based data in low-voltage segments of smart grids by using a process-oriented approach, providing an original interpretation in terms of accumulated energy. This interpretation is used to construct an overall framework containing multiple options for representing energy-based data, encompassing uniform and nonuniform linear time finite elements. A specific representation of the information defined in the space of digital events is then presented under the established framework. An enhanced representation of energy-based data identified as digital events is introduced, leading to the formulation of the final event-based data gathering (EBDG) scheme. Dedicated tests are carried out on exemplificative data sets for residential customers, including a new challenging benchmark developed by using a fuzzy-controlled load for air conditioning. The results obtained validate the use of the EBDG scheme to mine the energy-varying processes occurring at the remote nodes of the distribution system. Finally, the approach leading to the EBDG scheme is discussed to show how it falls within the realm of Big Data and to highlight how the EBDG results can be used to enable analytic accounting of the energy consumed in the processes occurring in a given time interval.

The event-driven energy metering paradigm has been recently introduced to make the management of the metered data more effective while reducing the overall amount of data to be transmitted or stored. This paper addresses the specific advantages of reconstructing the results of the aggregation of a number of loads in order to obtain an effective representation of the load aggregation that maintains detailed information on the individual and aggregate power. Examples are provided on real data gathered from individual and aggregate residential users.

This paper discusses the conceptual and practical implications of adopting a new type of energy meter, based on the identification of events from measuring the power pattern and on sending information on the actual energy used in the time interval between two events. The event-driven metering (EDM) approach enables gathering data useful for setting up effective representations of the knowledge that can be extracted about the prosumers' energy usage during time. Specific comparisons between the EDM effectiveness in reconstructing the power patterns with respect to the classical time-driven metering at regular time intervals are introduced to show the remarkable advantages of the EDM approach. An enhanced average power pattern reconstruction mechanism is also presented, based on the direct reproduction of the average power at the fastest time step occurring before the event generation, and on averaging the power pattern for the remaining part of the corresponding time interval. The case study application is illustrated by using the highly variable power pattern of a residential user.

Since energy use is a type of consumer behavior reflecting the interests to maximize some objective function, the human being activities seen in energy terms might be used to create the social aggregations or groups. Electric energy generated from ecologic sources brings some unpredictability. Authors model the unpredictability of the distributed generation in order to create a tool for minimization. Authors propose the novel method to build real life smart micro grids in the distributed generation context characterized by zero emissions. The proposed tool becomes an instrument to create the social aggregation of users and negotiate locally the “social” energy in real time, strengthening and mastering a virtual neighborhood of the local community.

This article discusses about the information protection aspects in Lebesgue-based smart meters that provide real-time stream of compressive sensing data directed to the Advanced Metering Infrastructure (AMI). In smart grid scenario, Supervisory Control And Data Acquisition (SCADA) systems start using real time metering information. Lebesgue-based method achieves higher data compression rates than the Shannon-based approach by encoding facts in the Mutual Information (MI) or inter-sampling. Part of the TCP/IP data packets remains unencrypted. Stream analytics can uncover knowledge about real life events and their timing by making inference on top of the inter-sampling data. The Rate Of Information (RoI) can be derived from the information left in clear form. It can disclose periods of higher vulnerability of smart grid. In turn, undesirable exploits could be set up. This article presents the ongoing work about unconventional mechanisms applicable to the protection of Mutual Dependence (MD) between pairs of random variables in real-time smart metering scenario.

Event-driven energy metering has emerged recently with conceptual and practical implications, as well as with new manufactured technological solutions. This paper recalls the underlying concepts that have led to these improvements. The event-driven energy metering paradigm is addressed in terms of the definition of the major aspects leading to its interpretation, the type of information provided, and the prospects for its use. The characteristics of the approach are shown through specific application cases.

This paper presents the results obtained from a new type of electricity meter, constructed as the industrial application of event-driven metering concepts. The underlying concepts of event-driven metering are applied to gather information on the electrical load patterns. The data formats used are presented and the details of the knowledge representation referring to the results coming from event-driven metering are discussed. The event-driven metering approach is illustrated by using data gathered from real-life applications.

This article describes an approach in which the rehabilitative exercise prepared by health care professional (human) is encoded as formal knowledge and used by humanoid robot to assist patients in residential settings without involving other care actors. The authors are researching on the new cognitive capability enabling robots to judge about the correctness of the rehabilitative exercise performed by patients following the robot's indications. The proposed method uses the Dynamic Time Warping functionality comparing the correct sequence (encoded in the Knowledge Base) with the human actions being observed by the robot's eyes. The proposed approach is an enabler of better sustainable rehabilitative care services in remote residential settings because of lowering the need of human care.

Electric CAR Recharge Optimization Toolkit is an integrated system for modeling and optimization of Electric Vehicle recharge processes. It uses semantic technology to conceptualize, model, and optimize battery recharge processes occurring in smart grid. The new tool attempts the time shifting postponing the demand exceeding the available energy flows. It is useful for operational planning of saturated electricity grid when the electricity demand exceeds the available resources during some time slots.

In this paper, we propose a new efficient technique for forecasting the bandwidth of digital access links to the Internet. This technique can be used for calculating the throughput of access links in implementing electronic document management systems and in organizing information portals. The main idea is to estimate the bandwidth of digital access links to the Internet using the statistics of the service load. The main result is the derivation of analytical expressions to estimate the required bandwidth.

Since energy use is a type of consumer behavior reflecting the interests to maximize some objective function, the human being activities seen in energy terms might be used to create the social aggregations or groups. Electric energy generated from ecologic sources brings some unpredictability. Authors model the unpredictability of the distributed generation in order to create a tool for minimization. Authors propose the novel method to build real life smart micro grids in the distributed generation context characterized by zero emissions. The proposed tool becomes an instrument to create the social aggregation of users and negotiate locally the “social” energy in real time, strengthening and mastering a virtual neighborhood of the local community.

This work suggests an effective approach for information management in smart power grids based on the introduction of a suitable theory of digital energy. It shows a possible way to effectively manage energy dynamics in real life systems in real time. Power grids hold real time information flows already, but the control systems currently adopted use other information sources. We discuss the use of the information and semantic technologies in order to balance the loads in storage-less electric energy domain, and the changes brought by Future Internet and its entities.

The Event-Driven Metering (EDM) method for electricity enabled the detection and better understanding of variable energy-transforming processes from real life. This article generalizes the above-mentioned Lebesgue-based approach by translating it to the accounting of other energy vectors in the form of gases or liquids. Given the behavioral difference between the physical forms of vectors of energy, authors made an effort to keep newly proposed method compatible with the process knowledge being extracted and shared grid-wide by the EDM method previously declined to electricity. Authors exploit the symplectic properties deriving from the energy conservation law. Authors set up new compressive and sparse sensing method by moving from the point-like data to the segment-like entities remaining valid over longer finite time intervals.