A Distributed Control Strategy for Islanded Single-Phase Microgrids with Hybrid Energy Storage Systems Based on Power Line Signaling

Energy management control is essential to microgrids (MGs), especially to single-phase ones. To handle the variety of distributed generators (DGs) that can be found in a MG, e.g., renewable energy sources (RESs) and energy storage systems (ESSs), a coordinated power regulation is required. The latter are generally battery-based systems whose lifetime is directly related to charge/discharge processes, whereas the most common RESs in a MG are photovoltaic (PV) units. Hybrid energy storage systems (HESS) extend batteries life expectancy, thanks to the effect of supercapacitors, but they also require more complex control strategies. Conventional droop methodologies are usually applied to provide autonomous and coordinated power control. This paper proposes a method for coordination of a single-phase MG composed by a number of sources (HESS, RES, etc.) using power line signaling (PLS). In this distributed control strategy, a signal whose frequency is higher than the grid is broadcasted to communicate with all DGs when the state of charge (SoC) of the batteries reaches a maximum value. This technique prevents batteries from overcharging and maximizes the power contribution of the RESs to the MG. Moreover, different commands apart from the SoC can be broadcasted, just by changing to other frequency bands. The HESS master unit operates as a grid-forming unit, whereas RESs act as grid followers. Supercapacitors in the HESS compensate for energy peaks, while batteries respond smoothly to changes in the load, also expanding its lifetime due to less aggressive power references. In this paper, a control structure that allows the implementation of this strategy in single-phase MGs is presented, with the analysis of the optimal range of PLS frequencies and the required self-adaptive proportional-resonant controllers

Ontology modelling methodology for temporal and interdependent applications

The increasing adoption of Semantic Web technology by several classes of applications in recent years, has made ontology engineering a crucial part of application development. Nowadays, the abundant accessibility of interdependent information from multiple resources and representing various fields such as health, transport, and banking etc., further evidence the growing need for utilising ontology for the development of Web applications. While there have been several advances in the adoption of the ontology for application development, less emphasis is being made on the modelling methodologies for representing modern-day application that are characterised by the temporal nature of the data they process, which is captured from multiple sources. Taking into account the benefits of a methodology in the system development, we propose a novel methodology for modelling ontologies representing Context-Aware Temporal and Interdependent Systems (CATIS). CATIS is an ontology development methodology for modelling temporal interdependent applications in order to achieve the desired results when modelling sophisticated applications with temporal and inter dependent attributes to suit today's application requirements

Distribution System Voltage Management and Optimization for Integration of Renewables and Electric Vehicles: Research Gap Analysis

California is striving to achieve 33% renewable penetration by 2020 in accordance with the state’s Renewable Portfolio Standard (RPS). The behavior of renewable resources and electric vehicles in distribution systems is creating constraints on the penetration of these resources into the distribution system. One such constraint is the ability of present-­‐‑day voltage management methodologies to maintain proper distribution system voltage profiles in the face of higher penetrations of PV and electric vehicle technologies. This white paper describes the research gaps that have been identified in current Volt/VAR Optimization and Control (VVOC) technologies, the emerging technologies which are becoming available for use in VVOC, and the research gaps which exist and must be overcome in order to realize the full promise of these emerging technologies

Invest to Save: Report and Recommendations of the NSF-DELOS Working Group on Digital Archiving and Preservation

Digital archiving and preservation are important areas for research and development, but there is no agreed upon set of priorities or coherent plan for research in this area. Research projects in this area tend to be small and driven by particular institutional problems or concerns. As a consequence, proposed solutions from experimental projects and prototypes tend not to scale to millions of digital objects, nor do the results from disparate projects readily build on each other. It is also unclear whether it is worthwhile to seek general solutions or whether different strategies are needed for different types of digital objects and collections. The lack of coordination in both research and development means that there are some areas where researchers are reinventing the wheel while other areas are neglected. Digital archiving and preservation is an area that will benefit from an exercise in analysis, priority setting, and planning for future research. The WG aims to survey current research activities, identify gaps, and develop a white paper proposing future research directions in the area of digital preservation. Some of the potential areas for research include repository architectures and inter-operability among digital archives; automated tools for capture, ingest, and normalization of digital objects; and harmonization of preservation formats and metadata. There can also be opportunities for development of commercial products in the areas of mass storage systems, repositories and repository management systems, and data management software and tools.

Meeting of the MINDS: an information retrieval research agenda

Since its inception in the late 1950s, the field of Information Retrieval (IR) has developed tools that help people find, organize, and analyze information. The key early influences on the field are well-known. Among them are H. P. Luhn's pioneering work, the development of the vector space retrieval model by Salton and his students, Cleverdon's development of the Cranfield experimental methodology, Spärck Jones' development of idf, and a series of probabilistic retrieval models by Robertson and Croft. Until the development of the WorldWideWeb (Web), IR was of greatest interest to professional information analysts such as librarians, intelligence analysts, the legal community, and the pharmaceutical industry