Secondary Frequency and Voltage Control of Islanded Microgrids via Distributed Averaging

In this work we present new distributed controllers for secondary frequency and voltage control in islanded microgrids. Inspired by techniques from cooperative control, the proposed controllers use localized information and nearest-neighbor communication to collectively perform secondary control actions. The frequency controller rapidly regulates the microgrid frequency to its nominal value while maintaining active power sharing among the distributed generators. Tuning of the voltage controller provides a simple and intuitive trade-off between the conflicting goals of voltage regulation and reactive power sharing. Our designs require no knowledge of the microgrid topology, impedances or loads. The distributed architecture allows for flexibility and redundancy, and eliminates the need for a central microgrid controller. We provide a voltage stability analysis and present extensive experimental results validating our designs, verifying robust performance under communication failure and during plug-and-play operation.Comment: Accepted for publication in IEEE Transactions on Industrial Electronic

Modeling and Recognition of Smart Grid Faults by a Combined Approach of Dissimilarity Learning and One-Class Classification

Detecting faults in electrical power grids is of paramount importance, either from the electricity operator and consumer viewpoints. Modern electric power grids (smart grids) are equipped with smart sensors that allow to gather real-time information regarding the physical status of all the component elements belonging to the whole infrastructure (e.g., cables and related insulation, transformers, breakers and so on). In real-world smart grid systems, usually, additional information that are related to the operational status of the grid itself are collected such as meteorological information. Designing a suitable recognition (discrimination) model of faults in a real-world smart grid system is hence a challenging task. This follows from the heterogeneity of the information that actually determine a typical fault condition. The second point is that, for synthesizing a recognition model, in practice only the conditions of observed faults are usually meaningful. Therefore, a suitable recognition model should be synthesized by making use of the observed fault conditions only. In this paper, we deal with the problem of modeling and recognizing faults in a real-world smart grid system, which supplies the entire city of Rome, Italy. Recognition of faults is addressed by following a combined approach of multiple dissimilarity measures customization and one-class classification techniques. We provide here an in-depth study related to the available data and to the models synthesized by the proposed one-class classifier. We offer also a comprehensive analysis of the fault recognition results by exploiting a fuzzy set based reliability decision rule

Digital Electrical Substation Communications based on Deterministic Time-Sensitive Networking over Ethernet

The authors would like to thank Alberto Sánchez Pérez and Grupo Cuerva S.L. for their assistance in the realization of the field tests at their electrical substation facility in Escúzar (Granada, Spain); and Jesús Torres Tenor and the CIRCE Foundation for their contribution to the development of a substation GOOSE traffic generator.This work presents a novel use case with Time-Sensitive Networks (TSN) for implementing a deterministic system allowing the joint transmission of all substation communications over the same Ethernet-based infrastructure. This approach streamlines the transition to Smart Grid by simplifying the typically complex architecture of electrical substations, characterized by multiple field buses and bridging devices. Thus, Smart Grid represents a disruptive innovation advancing substations to an “all-digital” environment with a uniform interface to access, manage, and update their communications and variables. TSN can serve as its underlying foundation as it is based on open, interoperable standards and enhancements for Ethernet that can establish deterministic communications with bounded end-to-end latency. This is shown with a TSN Proof of Concept (PoC) in a real-life substation that can integrate its most usual signals: digitized analog triggers for critical events or interlocks, GOOSE signaling (IEC 61850), and Best-Effort “Internet-like” traffic. This TSN PoC is shown to be versatile enough to propagate digitized critical events around 160 µs earlier than legacy substation equipment while preserving the integrity of background traffic. Furthermore, its flexibility was characterized in-depth in controlled laboratory tests, thereby confirming TSN as a viable alternative for supporting Smart Grid so long as the appropriate configuration is supplied.Amiga-7 Project RTI2018-096228-B-C3FITOPTIVIS Project H2020-RIA ECSEL-JU-2017-783162Spanish Ministerio de Economia y Transformacion Digital (MINECO) APCIN PCI2018-093184German Research Foundation (DFG

State-of-the-art in Power Line Communications: from the Applications to the Medium

In recent decades, power line communication has attracted considerable attention from the research community and industry, as well as from regulatory and standardization bodies. In this article we provide an overview of both narrowband and broadband systems, covering potential applications, regulatory and standardization efforts and recent research advancements in channel characterization, physical layer performance, medium access and higher layer specifications and evaluations. We also identify areas of current and further study that will enable the continued success of power line communication technology.Comment: 19 pages, 12 figures. Accepted for publication, IEEE Journal on Selected Areas in Communications. Special Issue on Power Line Communications and its Integration with the Networking Ecosystem. 201

A Novel Multiplex Network-based Sensor Information Fusion Model and Its Application to Industrial Multiphase Flow System

This work was supported by National Natural Science Foundation of China under Grant No. 61473203, and the Natural Science Foundation of Tianjin, China under Grant No. 16JCYBJC18200.Peer reviewedPostprin