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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.

This article presents a research work on contrasting the Manipulation of Demand figures via IoT networks (MadIoT). MadIoT is a new example of large-scale coordinated attacks on the power grid that targets high-wattage electric appliances. By altering the concentration in time of switching on-off certain number of appliances, the stability of the energy distribution network as a whole it can be compromised. An issue is the fact that no individual consumer can detect MadIoT autonomously. Current energy business scenario uses interval-energy meters capillary deployed to remote users. Current meters operate in the timescale of minutes, which makes undetectable the MadIoT attacks. The authors propose using next-generation event-based real-time demand-oriented meters in order to collect true data about the timing of switching on-off devices. The above-mentioned big data stream enables newly introduced Security Agents to perform machine-reasoning over timing patterns against an unexpected probability density of events in certain neighborhood(s).

This article discusses information protection in the context of Event-based Energy Management Systems in consumer-centered Smart Grid with renewable energy. Authors consider hybrid real time smart metering scenario that provides both the measurement data to the Advanced Metering Infrastructure plus the real-time stream of compressive sensing events directed to the Supervisory Control And Data Acquisition system. The threat is represented by an attacker that injects packets aimed to mislead the Energy Management System. Authors introduce new Security Agent that establishes interoperability between the above-mentioned subsystems aimed to mitigate said treat. The proposed method bridges the Legacy approach and the Service Orientation.

An energy distribution network is a critical infrastructure that any compromise has an enormous impact on daily lives and the economy. The objective of this work is a computerized tool for distributed monitoring, dynamic re-configuration and control of DC distribution topology. This paper describes the double bar bus DC system exploiting the event-driven, service-oriented architecture, and real-time metering with nonuniform time sampling as an example of neighborhood optimization. We build a system with the capability to assess the resilience of and to rebuild better resilient grid partitions at run-time. The result is an intelligent system distributing loads between two buses dynamically in a way to keep self-sustainable and/or non-interruptible portion running at one bus by moving few other loads to the second bus. In standalone modality, the tool assesses the survivability of microgrid with high penetration of renewable energy. Running in cooperation with grid management tools, the same software can reconfigure optimally the local topology at run-time.

The event-driven electricity metering method makes visible both processes and their components. It enables the detection and better understanding of processes that vary energy flows. The newly obtained process knowledge is shared grid-wide using communication channels. The changes in energy exchanges (processes) originate new information flows in smart grid. We use internal metering data to obtain meta-information needed to reduce said data flows. The paper explains the use of an event-driven communication method in metering.

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.

This article presents an industrial application in which event-based smart meters supplies datasets feeding the Advanced Metering Infrastructure, legacy billing procedures, and Supervisory Control and Data Acquisition systems of smart grid. New generation hybrid meters interoperate by using the FI-WARE architectural framework personalized by FINESCE team in the context of Cloud-based Service-Oriented Architecture made available by the Future Internet Public-Private-Partnership. Authors illustrate an opportunity to make observable each node of the Low Voltage energy distribution topology by using new event-based real time toolkit. In this industrial use case, event-based meters fed billing subsystem at regular time intervals, and supplies statefull events in real-time to the control system. This way, both event-based and timer-based datasets are conveyed to the FI-WARE cloud first, that directs them to the respective recipients by using publish-subscribe features and Big Data tools.

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 geometrical numeric integration applied to coarse-grained cycle-precise event-driven measurements of electrical energy. The proposed simplectic method draws from Stormer-Verlet and leapfrog algorithms in order to provide operational intelligence tools to analyze the amounts of analytical energy data. The proposed tool is extremely quick. Being very simple in computational terms, it suites real-time usages. This work extends the event-driven measurement approaches.