An efficient and accurate solution for distribution system state estimation with multiarea architecture

Distribution system state estimation (DSSE) is an essential tool for the management and control of future distribution networks. Distribution grids are usually characterized by a very large number of nodes and different voltage levels. Moreover, different portions of the system can be operated by different distribution system operators. In this context, multiarea approaches are key tools to efficiently perform DSSE. This paper presents a novel approach for multiarea state estimation in distribution systems. The proposed algorithm is based on a two-step procedure, where the first-step local estimations are refined through a newly designed second step that allows the integration of the measurement information available in the adjacent areas. The main novelty in this paper is the mathematical analysis of the impact brought by possible measurements shared among different areas, which drives the design of a new efficient weighted least squares formulation of the second step to maximize the achievable estimation accuracy. Tests performed on the unbalanced IEEE 123-bus network prove the goodness of the new multiarea estimator proposed and show the accuracy and efficiency enhancements obtainable with respect to previous literature

Improved Fine Particles Monitoring in Smart Cities by Means of Advanced Data Concentrator

Traffic reduction and air-quality improvement are among the main goals of several projects worldwide. This article presents a fine particle monitoring based on heterogeneous air quality mobile sensors and an advanced data concentrator (AdDC), so that the level of pollution in the urban area, where few accurate fixed measurement stations are present, can be assessed with better accuracy. Some urban buses are used to carry low-cost sensors, thus implementing a mobile sensor network and increasing the time and space resolution of air quality information. The data obtained by these low-cost sensors are significantly affected by uncertainties, also due to atmospheric factors, such as humidity. The proposed AdDC processes all the obtained measurements and exploits the information obtained by the accurate fixed stations to improve the accuracy of the low-cost mobile sensors. In particular, a new compensation methodology, specifically targeted to the fine particles monitoring, is proposed. The monitoring of relative humidity is added, with the relevant on-the-fly calibration, so that the measured values can be used to correct the effects of humidity on PM2.5 sensors. The validity of the proposed system is proven by means of simulations performed on an appropriate set up

Selection of features based on electric power quantities for non-intrusive load monitoring

Non-intrusive load monitoring (NILM) is a process of determining the operating states and the energy consumption of single electric devices using a single energy meter providing aggregate load measurements. Due to the large spread of power electronic-based and nonlinear devices connected to the network, the time signals of both voltage and current are typically non-sinusoidal. The effectiveness of a NILM algorithm strongly depends on determining a set of discriminative features. In this paper, voltage and current signals were combined to define, according to the definitions provided in Standard IEEE 1459, different power quantities, that can be used to distinguish different types of appliance. Multi-layer perceptron (MLP) classifiers were trained to solve the appliance detection problem as a multi-class event classification problem, varying the electric features in input. This allowed to select an optimal set of features guarantying good classification performance in identifying typical electric loads

Compressive Sensing-Based Harmonic Sources Identification in Smart Grids

Identifying the prevailing polluting sources would help the distribution system operators in acting directly on the cause of the problem, thus reducing the corresponding negative effects. Due to the limited availability of specific measurement devices, ad hoc methodologies must be considered. In this regard, compressive sensing (CS)-based solutions are perfect candidates. This mathematical technique allows recovering sparse signals when a limited number of measurements are available, thus overcoming the lack of power quality meters. In this article, a new formulation of the ell _{1} -minimization algorithm for CS problems, with quadratic constraint, has been designed and investigated in the framework of the identification of the main polluting sources in smart grids. A novel whitening transformation is proposed for this context. This specific transformation allows the energy of the measurement errors to be appropriately estimated, and thus, better identification results are obtained. The validity of the proposal is proven by means of several simulations and tests performed on two distribution networks for which suitable measurement systems are considered along with a realistic quantification of the uncertainty sources

The review of soil legacy data as a first step for the construction of a soil health monitoring system in the Mediterranean Region

In the Mediterranean region and particularly in the Near East and North Africa Mediterranean (NENA) countries, the soils and landscapes are extensively degraded, due to long-term unsustainable anthropogenic pressure and the effects of climate change. The average level of health of the soil resources is low and already inadequate to support economic development and food security targets. In the context of the sustainable management and protection of soil resources, considering the specificities of Mediterranean environmental conditions, there is an urgent need to make soil data and soil information (SDI) data understandable and usable for the purpose of monitoring soil health and assessing soil ecosystems in the region. Steps toward this aim are being taken within the PRIMA-funded SOIL4MED project, which focuses on monitoring soil health and developing information systems to promote sustainable soil management in Mediterranean region, aligning with the Global Soil Partnership aims and approaches. The project starts with a comprehensive review of legacy soil point data provided by partner countries, i.e. Italy, Lebanon, Spain, France, Tunisia, Greece, Egypt, Jordan, Turkey, and Morocco. A total of almost 9,000 soil profiles data were collected, thanks also to the contributions of some research institutes (i.e., IAO, CREA, IRD/ORSTOM). These were then subjected to detailed analysis in order to ascertain the types of survey methods employed, the different soil classification systems used and the type of data available for each country (e.g., field data, lab data). The systematic collection of data has revealed several key findings. Firstly, that legacy data are frequently old, in non-digital format and lack homogeneity in terms of soil classification systems, field and lab methods, and data formats. Secondly, that if properly processed, such data are able to provide an overview of soil characteristics and properties in the Mediterranean area. Therefore, to use these data systematically and effectively, they must be harmonized and digitized in order to develop an easily accessible and standardized database of soil information. The process of collecting, evaluating, integrating multiple types of soil legacy data, homogenizing them using a single classification system (WRB, 2022), and their subsequent inclusion in a database, provides a more robust and complete view of the evidence available about soil health in the MR. It is a key step in the selection of soil health indicators and provides useful information to define past and present soil health conditions. This collaborative effort represents a crucial preparatory step for the future realization of the Soil Atlas of the Mediterranean Region

A Practical Solution for Locating the Source of Voltage Dips in HV/MV Interconnected Grids

Monitoring the technical performance of a power system is significantly enhanced when distributed instrumentation produces coherent field data, i.e., synchronized by GPS timestamping. In this paper a practical methodology is presented to improve the localisation of the source of a voltage dip on power grids. The proposed solution makes use of synchronised dip data provided by power quality meters. Field data reporting events occurred in an HV/MV interconnected system in South Africa are used to validate the results obtained by the improved method and compare with results of two alternative methods

The interplay between single particle anisotropy and interparticle interactions in ensembles of magnetic nanoparticles

This paper aims to analyze the competition of single particle anisotropy and interparticle interactions in nanoparticle ensembles using a random anisotropy model. The model is first applied to ideal systems of non-interacting and strongly dipolar interacting ensembles of maghemite nanoparticles. The investigation is then extended to more complex systems of pure cobalt ferrite CoFe2O4 (CFO) and mixed cobalt-nickel ferrite (Co,Ni)Fe2O4 (CNFO) nanoparticles. Both samples were synthetized by the polyol process and exhibit the same particle size (DTEM 48 5 nm), but with different interparticle interaction strengths and single particle anisotropy. The implementation of the random anisotropy model allows investigation of the influence of single particle anisotropy and interparticle interactions, and sheds light on their complex interplay as well as on their individual contribution. This analysis is of fundamental importance in order to understand the physics of these systems and to develop technological applications based on concentrated magnetic nanoparticles, where single and collective behaviors coexist

Testing surgical face masks in an emergency context: The experience of italian laboratories during the COVID-19 pandemic crisis

The first wave of the COVID-19 pandemic brought about a broader use of masks by both professionals and the general population. This resulted in a severe worldwide shortage of devices and the need to increase import and activate production of safe and effective surgical masks at the national level. In order to support the demand for testing surgical masks in the Italian context, Universities provided their contribution by setting up laboratories for testing mask performance before releasing products into the national market. This paper reports the effort of seven Italian university laboratories who set up facilities for testing face masks during the emergency period of the COVID-19 pandemic. Measurement set-ups were built, adapting the methods specified in the EN 14683:2019+AC. Data on differential pressure (DP) and bacterial filtration efficiency (BFE) of 120 masks, including different materials and designs, were collected over three months. More than 60% of the masks satisfied requirements for DP and BFE set by the standard. Masks made of nonwoven polypropylene with at least three layers (spunbonded-meltblown-spunbonded) showed the best results, ensuring both good breathability and high filtration efficiency. The majority of the masks created with alternative materials and designs did not comply with both standard requirements, resulting in suitability only as community masks. The effective partnering between universities and industries to meet a public need in an emergency context represented a fruitful example of the so-called university "third-mission"

Disease-specific and general health-related quality of life in newly diagnosed prostate cancer patients: The Pros-IT CNR study

Background: The National Research Council (CNR) prostate cancer monitoring project in Italy (Pros-IT CNR) is an observational, prospective, ongoing, multicentre study aiming to monitor a sample of Italian males diagnosed as new cases of prostate cancer. The present study aims to present data on the quality of life at time prostate cancer is diagnosed. Methods: One thousand seven hundred five patients were enrolled. Quality of life is evaluated at the time cancer was diagnosed and at subsequent assessments via the Italian version of the University of California Los Angeles-Prostate Cancer Index (UCLA-PCI) and the Short Form Health Survey (SF-12). Results: At diagnosis, lower scores on the physical component of the SF-12 were associated to older ages, obesity and the presence of 3+ moderate/severe comorbidities. Lower scores on the mental component were associated to younger ages, the presence of 3+ moderate/severe comorbidities and a T-score higher than one. Urinary and bowel functions according to UCLA-PCI were generally good. Almost 5% of the sample reported using at least one safety pad daily to control urinary loss; less than 3% reported moderate/severe problems attributable to bowel functions, and sexual function was a moderate/severe problem for 26.7%. Diabetes, 3+ moderate/severe comorbidities, T2 or T3-T4 categories and a Gleason score of eight or more were significantly associated with lower sexual function scores at diagnosis. Conclusions: Data collected by the Pros-IT CNR study have clarified the baseline status of newly diagnosed prostate cancer patients. A comprehensive assessment of quality of life will allow to objectively evaluate outcomes of different profile of care

From data to practice: brain meningioma treatment in elderly patients – a survey of the Italian Society of Neurosurgery (SINch®) and systematic review and meta-analysis

The management of meningioma in elderly patients (MEP) presents a complex and evolving challenge. Data available offer conflicting information on treatment options and complications. This survey aimed to examine the current approach to MEP, comparing the national profile to data in the current literature. A survey addressing the treatments options and management of meningioma in elderly was designed on behalf of SINch (R) (Societa Italiana di Neurochirurgia) and sent via email to all Chiefs of Neurosurgical Departments. The survey remained open for responses from May 5th, 2022, until November 21st, 2022. A search of the literature published between January 2000 and March 2023, in accordance to PRISMA guidelines, was included. A total of 51 Neurosurgical centers participated in the survey. The caseload profile of each center influences the choice of treatment selection (Stereotactic Radiosurgery versus open surgery) (p = 0.01) and the consolidated practice of discussing cases within a multidisciplinary group (p = 0.02). The pooled meta-analysis demonstrated a significant increased risk in the elderly group for permanent deficits (p < 0.00001), postoperative infections (p = 0.0004) and hemorrhage (p = 0.0001), perioperative mortality (p < 0.00001), and medical complications (p < 0.00001) as compared to the young population. This study presents the initial comprehensive analysis of the existing trends in the surgical management of MEP in Italy. The significant variation in practices primarily stems from the absence of standardized guidelines. While most centers have adopted an integrated approach, there is a need to promote a multidisciplinary care model. Prospective studies are needed to gather robust evidence in this clinical setting