Bandwidth and accuracy-aware state estimation for smart grids using software defined networks

Smart grid (SG) will be one of the major application domains that will present severe pressures on future communication networks due to the expected huge number of devices that will be connected to it and that will impose stringent quality transmission requirements. To address this challenge, there is a need for a joint management of both monitoring and communication systems, so as to achieve a flexible and adaptive management of the SG services. This is the issue addressed in this paper, which provides the following major contributions. We define a new strategy to optimize the accuracy of the state estimation (SE) of the electric grid based on available network bandwidth resources and the sensing intelligent electronic devices (IEDs) installed in the field. In particular, we focus on phasor measurement units (PMUs) as measurement devices. We propose the use of the software defined networks (SDN) technologies to manage the available network bandwidth, which is then assigned by the controller to the forwarding devices to allow for the flowing of the data streams generated by the PMUs, by considering an optimization routine to maximize the accuracy of the resulting SE. Additionally, the use of SDN allows for adding and removing PMUs from the monitoring architecture without any manual intervention. We also provide the details of our implementation of the SDN solution, which is used to make simulations with an IEEE 14-bus test network in order to show performance in terms of bandwidth management and estimation accuracy

Transmission line parameters estimation in the presence of realistic PMU measurement error models

Proposals have been presented in literature to estimate line parameters and monitor their changes. Syn-chrophasor measurements from phasor measurement units (PMUs) have appeared as a possible breakthrough for accurate estimation. However, few methods consider a realistic measurement chain including PMUs and instrument transformers and their systematic and random error contributions. This paper proposes an improved method to simultaneously estimate line parameters and systematic measurement errors on multiple network lines. The algorithm is designed to deal with realistic PMU measurement errors and, in particular, with phase -angle errors caused by common time-base errors on multiple PMU channels. The impact of PMU measurement errors is investigated to achieve a comprehensive view of the performance under realistic conditions. The results obtained on an IEEE test network prove the advantages of the proposed method with respect to other recent methods and its robustness in the presence of mismatches in the error model

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

Molecular diagnosis of multiple endocrine neoplasia type 2A

Objective. To identify by means of genetic analyses individuals who are at risk of developing medullary thyroid cancer that is a component of multiple endocrine neoplasia.Subjects. A three-generation kindred with clinically and biochemically diagnosed medUllary thyroid cancer.Method. Identification of a heterozygote mutation by nucleic acid sequencing and restriction analyses.Results. A heterozygote T → C (Cys → Arg) mutation at codon 618 in exon 10 of the RET proto-oncogene was identified in 4 family members who had previously been diagnosed with medullary thyroid cancer. The same mutation was also found in one of the proband's presymptomatic children who subsequently underwent a preemptive thyroidectomy. The genetic diagnosis was confirmed by histology. No mutations were detected in any other family members.Conclusion. Identification of heterozygote germline mutations in multiple endocrine neoplasia is direct, highly accurate and cost-effective. This study demonstrates that, appropriately used, molecular diagnosis can supersede conventional biochemical methods in the management of patients with inherited cancers

Low-Cost Battery Monitoring by Converter-Based Electrochemical Impedance Spectroscopy

The use of batteries and other electrochemical devices in modern power systems is rapidly increasing, with stricter requirements in terms of cost, efficiency and reliability. Innovative monitoring solutions are therefore urged to allow a successful development of a wide range of emerging applications, including electric vehicles and large-scale energy storage to support renewable energy generation. Presently, a huge gap still exists between the accurate and sophisticated monitoring techniques commonly employed in laboratory tests, on the one hand, and the simple and rough solutions available in most commercial applications, on the other hand. The objective of this paper is therefore to contribute to the development of low-cost but accurate solutions for commercial battery condition monitoring, by proposing an embedded system that combines real-time digital signal processing with the high computational power and user friendly interface of a modern computer, at a cost comparable to a simple micro-controller. In more detail, the paper focuses on electrochemical impedance spectroscopy on a battery performed by a DC-DC power converter, and it explains how the proposed low-cost off-the-shelf hardware can control the converter, acquire the measurement signals, accurately process them in the time and frequency domains, and estimate the result uncertainty in real-time, which is necessary to promptly and reliably detect any variation in the battery condition

Effects of particulate matter on genomic DNA methylation content and iNOS promoter methylation

Background: Altered patterns of gene expression mediate the effects of particulate matter (PM) on human health, but mechanisms through which PM modifies gene expression are largely undetermined. Objectives: We aimed at identifying short- and long-term effects of PM exposure on DNA methylation, a major genomic mechanism of gene expression control, in workers in an electric furnace steel plant with well-characterized exposure to PM with aerodynamic diameters < 10 μm (PM10). Methods: We measured global genomic DNA methylation content estimated in Alu and long interspersed nuclear element-1 (LINE-1) repeated elements, and promoter DNA methylation of iNOS (inducible nitric oxide synthase), a gene suppressed by DNA methylation and induced by PM exposure in blood leukocytes. Quantitative DNA methylation analysis was performed through bisulfite PCR pyrosequencing on blood DNA obtained from 63 workers on the first day of a work week (baseline, after 2 days off work) and after 3 days of work (postexposure). Individual PM10 exposure was between 73.4 and 1,220 μg/m3. Results: Global methylation content estimated in Alu and LINE-1 repeated elements did not show changes in postexposure measures compared with baseline. PM10 exposure levels were negatively associated with methylation in both Alu [β = –0.19 %5-methylcytosine (%5mC); p = 0.04] and LINE-1 [β = –0.34 %5mC; p = 0.04], likely reflecting long-term PM10 effects. iNOS promoter DNA methylation was significantly lower in postexposure blood samples compared with baseline (difference = –0.61 %5mC; p = 0.02). Conclusions: We observed changes in global and gene specific methylation that should be further characterized in future investigations on the effects of PM

Gene expression patterns vary in clonal cell cultures from Rett syndrome females with eight different MECP2 mutations

BACKGROUND: Females with the neurological disorder Rett syndrome are heterozygous for mutations in X-linked MECP2 that encodes methyl-CpG binding protein 2 (MeCP2) thought to act as a transcriptional repressor. To identify target genes for MeCP2 modulation, we studied global gene expression in single cell-derived wild-type and mutant MECP2 expressing fibroblast clones with four common mutations (R106W, R306C, 705delG, 1155del32) and in lymphoblastoid cell lines (LCLs) that included four mutant MeCP2 (T158M, 803delG, R168X and 1159del28) expressing, and five (1159del28, R106W, R255X, 803delG, 803delG) wild-type MeCP2 expressing lines. METHODS: Clonality and mutation status were verified by androgen receptor methylation assays for X-inactivation and by sequencing MECP2 transcripts. Expression studies were done with oligonucleotide microarrays (Affymetrix U95) and verified with real-time quantitative RT-PCR using Sybr Green. RESULTS: Expression of 49 transcripts was increased, and expression of 21 transcripts was decreased, in at least 3 of 4 mutant/wild-type fibroblast comparisons. Transcript levels of 11 genes, determined by quantitative RT-PCR, were highly correlated with the microarray data. Therefore, multiple additional clones from two Rett individuals were tested by RT-PCR only. Striking expression differences were found in both mutant and wildtype MeCP2 expressing clones. Comparing expression profiles of lymphoblastoid cell lines yielded 16 differentially expressed genes. CONCLUSIONS: MeCP2 deficiency does not lead to global deregulation of gene expression. Either MeCP2's in vivo function does not involve widespread transcriptional repression, or its function is redundant in cell types that also express other methyl-CpG binding proteins. Our data suggest that clonal fibroblast strains may show substantial inter-strain variation, making them a difficult and unstable resource for genome-wide expression profiling studies

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Diseased muscles that lack dystrophin or laminin-α2 have altered compositions and proliferation of mononuclear cell populations

BACKGROUND: Multiple types of mononucleate cells reside among the multinucleate myofibers in skeletal muscles and these mononucleate cells function in muscle maintenance and repair. How neuromuscular disease might affect different types of muscle mononucleate cells had not been determined. In this study, therefore, we examined how two neuromuscular diseases, dystrophin-deficiency and laminin-α2-deficiency, altered the proliferation and composition of different subsets of muscle-derived mononucleate cells. METHODS: We used fluorescence-activated cell sorting combined with bromodeoxyuridine labeling to examine proliferation rates and compositions of mononuclear cells in diseased and healthy mouse skeletal muscle. We prepared mononucleate cells from muscles of mdx (dystrophin-deficient) or Lama2(-/- )(laminin-α2-deficient) mice and compared them to cells from healthy control muscles. We enumerated subsets of resident muscle cells based on Sca-1 and CD45 expression patterns and determined the proliferation of each cell subset in vivo by BrdU incorporation. RESULTS: We found that the proliferation and composition of the mononucleate cells in dystrophin-deficient and laminin-α2-deficient diseased muscles are different than in healthy muscle. The mdx and Lama2(-/- )muscles showed similar significant increases in CD45(+ )cells compared to healthy muscle. Changes in proliferation, however, differed between the two diseases with proliferation increased in mdx and decreased in Lama2(-/- )muscles compared to healthy muscles. In particular, the most abundant Sca-1(-)/CD45(- )subset, which contains muscle precursor cells, had increased proliferation in mdx muscle but decreased proliferation in Lama2(-/- )muscles. CONCLUSION: The similar increases in CD45(+ )cells, but opposite changes in proliferation of muscle precursor cells, may underlie aspects of the distinct pathologies in the two diseases