Islanding in Distribution Systems Considering Wind Power and Storage

In modern power systems the penetration of renewable energies has been growing dramatically. The combination of renewable energy and energy storage is seen as an opportunity to better exploit the intermittent and uncertain local generation in distribution systems, especially in the case of islanding. The main goal of this paper is to keep the load and generation units on-line under islanding conditions with respect to the total power imbalance of the isolated area and minimizing the power losses and nodal voltage deviations. A two-stage stochastic linear programming model is introduced to solve the optimization problem and find the best combination of generation, demand and electrical energy storage under islanding conditions. The proposed model has been tested on a 69-bus distribution system and the results obtained in the islanded areas are presented considering two case studies (with and without electrical energy storage), under different levels of generation and deman

Frequent Itemsets Mining for Big Data: A Comparative Analysis

Itemset mining is a well-known exploratory data mining technique used to discover interesting correlations hidden in a data collection. Since it supports different targeted analyses, it is profitably exploited in a wide range of different domains, ranging from network traffic data to medical records. With the increasing amount of generated data, different scalable algorithms have been developed, exploiting the advantages of distributed computing frameworks, such as Apache Hadoop and Spark. This paper reviews Hadoop- and Spark-based scalable algorithms addressing the frequent itemset mining problem in the Big Data domain through both theoretical and experimental comparative analyses. Since the itemset mining task is computationally expensive, its distribution and parallelization strategies heavily affect memory usage, load balancing, and communication costs. A detailed discussion of the algorithmic choices of the distributed methods for frequent itemset mining is followed by an experimental analysis comparing the performance of state-of-the-art distributed implementations on both synthetic and real datasets. The strengths and weaknesses of the algorithms are thoroughly discussed with respect to the dataset features (e.g., data distribution, average transaction length, number of records), and specific parameter settings. Finally, based on theoretical and experimental analyses, open research directions for the parallelization of the itemset mining problem are presented

An efficient data exchange mechanism for chained network functions

Thanks to the increasing success of virtualization technologies and processing capabilities of computing devices, the deployment of virtual network functions is evolving towards a unified approach aiming at concentrating a huge amount of such functions within a limited number of commodity servers. To keep pace with this trend, a key issue to address is the definition of a secure and efficient way to move data between the different virtualized environments hosting the functions and a centralized component that builds the function chains within a single server. This paper proposes an efficient algorithm that realizes this vision and that, by exploiting the peculiarities of this application domain, is more efficient than classical solutions. The algorithm that manages the data exchanges is validated by performing a formal verification of its main safety and security properties, and an extensive functional and performance evaluation is presented

Area Formation and Content Assignment for LTE Broadcasting

Broadcasting and multicasting services in LTE networks are shaping up to be an effective way to provide popular content. A key requirement is that cells are aggregated into areas where a tight time synchronization among transmissions is enforced, so as to broadcast the same radio resources. Our paper addresses a facet of LTE broadcasting that has so far received little attention: the creation of broadcasting areas and the assignment of content to them in order to efficiently exploit radio resources and satisfy user requests. Our original clustering approach, named Single-Content Fusion, achieves these goals by initially aggregating cells into single-content areas and maximizing cell similarity in content interests. Aggregated areas are then merged into multiple-content areas by virtue of similar spatial coverage. We show the validity of our solution pointing out the advantages it provides in comparison to other approaches. We also discuss the impact of various system factors (e.g., number of served users, broadcast data rate, area size) and the scalability of our proposal in large, realistic scenarios with both static and time-varying user interest

A rejoinder to the comments of Benedetto et al. on the paper "Critical remarks on the Italian research assessment exercise VQR 2011-2014" (Journal of Informetrics, 11(2): 337-357)

The paper "Critical remarks on the Italian research assessment exercise VQR 2011-2014" (Franceschini & Maisano, 2017) analyzed some vulnerabilities of the recently concluded Italian assessment exercise. Some apical (former and current)members of ANVUR promptly commented on our criticisms through a letter to the editor (Benedetto, Checchi, Graziosi, & Malgarini, 2017). We believe that this letter is not very convincing. In the following, we provide a rejoinder to the comments directed to our paper

Life Cycle Assessment (LCA) of biogas-fed Solid Oxide Fuel Cell (SOFC) plant

The Life Cycle Assessment (LCA) of biogas-fed Solid Oxide Fuel Cell (SOFC) integrated with a CO2 recovery system is presented in this work. The goal of the work is to evaluate the environmental performance of an SOFC fueled with sewage biogas and to compare it with traditional technologies (internal combustion engines and microturbines) using the same fuel. CO2 recovery is performed through a tubular photobioreactor, fixing the recovered carbon in the form of a micro-algae. The analysis takes into account both the biogas production line (anaerobic digester) and its exploitation into the fuel cell (i.e., the power generator). Results show that the SOFC manufacturing activity is highly intensive since it requires a large amount of use of electricity. During operation, instead, the highest burden is associated with the fuel production. We analyzed two scenarios for biogas operation underlining the benefits of introducing sludge pre-thickening before the anaerobic digestion process. The use of a sludge pre-thickening system can reduce the inlet flow of natural gas into the plant, thus affecting the fuel chain contribution and reducing the overall impact. The photobioreactor results in consuming more energy than what it produces (looking at the operation phase only; the manufacturing phase was not even included) and being responsible for more carbon emissions than the amount fixed in algae. On the other side, data for the photobioreactor system were based on a real system at the proof-of-concept level. Therefore significant improvements are expected for an industrial-size system. Finally, the SOFC environmental burdens have been compared with main competitors in the same field (internal combustion engines and microturbines), showing the superior environmental performance. The proposed energy system is thus an interesting choice for cleaner energy production