Robust Coordinated Design of PSS and TCSC using PSO Technique for Power System Stability Enhancement

Power system stability improvement by coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC) controller is addressed in this paper. Particle Swarm Optimization (PSO) technique is employed for optimization of the parameterconstrained nonlinear optimization problem implemented in a simulation environment. The proposed controllers are tested on a weakly connected power system. The non-linear simulation results are presented for wide range of loading conditions with various fault disturbances and fault clearing sequences as well as for various small disturbances. The eigenvalue analysis and simulation results show the effectiveness and robustness of proposed controllers to improve the stability performance of power system by efficient damping of low frequency oscillations under various disturbances

Prevalence and identification of Candida sp. in pregnant women using VITEK-2

Background: Candida sp. is seen in several areas of body such as, mouth, groin area including vagina and digestive tract as thrush or gastroenteritis. The slide-culture technique and the VITEK-2 automated system were used for species-identification of the fungus; nonetheless, a gold standard or any first identification method would have inherent errors in arriving at a correct identification of a microorganism at species level.Methods: Morphological fungal criteria were ascertained with germ tubes, glucose agar, sugar fermentation and sugar assimilation tests Candida from vaginal swabs and other clinical samples of 85 infected pregnant women with diabetes, by growing swab lots on Sabouraud’s Dextrose Agar (SDA) plates, the slide culture technique and the VITEK-2 automated system.Results: Of 85 patients, 122 isolates in SDA culture were determined as 7 Candida sp.  with number of isolates of each species, as follows: 47 C. albicans, 9 C. famata, 11 C. glabrata, 13 C. guilliermondii, 8 C. krusei, 3 C. parapsilosis and 37 C. tropicalis from vaginal swabs. From 60 vaginal swabs, 46 urine samples and 12 throat swabs it was seen that C. albicans was most prevalent. However, withVITEK-2, 201 fungal strains were identified; Candida sp. was isolated in all samples: 59 C. albicans, 19 C. famata, 21 C. glabrata, 23 C. guilliermondii,18 C. krusei, 13 C. parapsilosis and 48 C. tropicalis.Conclusions: The most prevalent species among the isolated fungi was C. albicans, causing VC in diabetic pregnant women

Dynamic Energy Management

We present a unified method, based on convex optimization, for managing the power produced and consumed by a network of devices over time. We start with the simple setting of optimizing power flows in a static network, and then proceed to the case of optimizing dynamic power flows, i.e., power flows that change with time over a horizon. We leverage this to develop a real-time control strategy, model predictive control, which at each time step solves a dynamic power flow optimization problem, using forecasts of future quantities such as demands, capacities, or prices, to choose the current power flow values. Finally, we consider a useful extension of model predictive control that explicitly accounts for uncertainty in the forecasts. We mirror our framework with an object-oriented software implementation, an open-source Python library for planning and controlling power flows at any scale. We demonstrate our method with various examples. Appendices give more detail about the package, and describe some basic but very effective methods for constructing forecasts from historical data.Comment: 63 pages, 15 figures, accompanying open source librar

Planar Tc99m – sestamibi scintimammography should be considered cautiously in the axillary evaluation of breast cancer protocols: Results of an international multicenter trial

BACKGROUND: Lymph node status is the most important prognostic indicator in breast cancer in recently diagnosed primary lesion. As a part of an interregional protocol using scintimammography with Tc99m compounds, the value of planar Tc99m sestamibi scanning for axillary lymph node evaluation is presented. Since there is a wide range of reported values, a standardized protocol of planar imaging was performed. METHODS: One hundred and forty-nine female patients were included prospectively from different regions. Their mean age was 55.1 ± 11.9 years. Histological report was obtained from 2.987 excised lymph nodes from 150 axillas. An early planar chest image was obtained at 10 min in all patients and a delayed one in 95 patients, all images performed with 740–925 MBq dose of Tc99m sestamibi. Blind lecture of all axillary regions was interpreted by 2 independent observers considering any well defined focal area of increased uptake as an involved axilla. Diagnostic values, 95% confidence intervals [CI] and also likelihood ratios (LR) were calculated. RESULTS: Node histology demonstrated tumor involvement in 546 out of 2987 lymph nodes. Sestamibi was positive in 30 axillas (25 true-positive) and negative in 120 (only 55 true-negative). The sensitivity corresponded to 27.8% [CI = 18.9–38.2] and specificity to 91.7% [81.6–97.2]. The positive and negative LR were 3.33 and 0.79, respectively. There was no difference between early and delayed images. Sensitivity was higher in patients with palpable lesions. CONCLUSION: This work confirmed that non tomographic Tc99m sestamibi scintimammography had a very low detection rate for axillary lymph node involvement and it should not be applied for clinical assessment of breast cancer

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject