Distribution network short term scheduling in Smart Grid context

The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Fungal contamination in two Portuguese wastewater treatment plants

The presence of filamentous fungi was detected in wastewater and air collected at wastewater treatment plants (WWTP) from several European countries. The aim of the present study was to assess fungal contamination in two WWTP operating in Lisbon. In addition, particulate matter (PM) contamination data was analyzed. To apply conventional methods, air samples from the two plants were collected through impaction using an air sampler with a velocity air rate of 140 L/min. Surfaces samples were collected by swabbing the surfaces of the same indoor sites. All collected samples were incubated at 27°C for 5 to 7 d. After lab processing and incubation of collected samples, quantitative and qualitative results were obtained with identification of the isolated fungal species. For molecular methods, air samples of 250 L were also collected using the impinger method at 300 L/min airflow rate. Samples were collected into 10 ml sterile phosphate-buffered saline with 0.05% Triton X-100, and the collection liquid was subsequently used for DNA extraction. Molecular identification of Aspergillus fumigatus and Stachybotrys chartarum was achieved by real-time polymerase chain reaction (RT-PCR) using the Rotor-Gene 6000 qPCR Detection System (Corbett). Assessment of PM was also conducted with portable direct-reading equipment (Lighthouse, model 3016 IAQ). Particles concentration measurement was performed at five different sizes: PM0.5, PM1, PM2.5, PM5, and PM10. Sixteen different fungal species were detected in indoor air in a total of 5400 isolates in both plants. Penicillium sp. was the most frequently isolated fungal genus (58.9%), followed by Aspergillus sp. (21.2%) and Acremonium sp. (8.2%), in the total underground area. In a partially underground plant, Penicillium sp. (39.5%) was also the most frequently isolated, also followed by Aspergillus sp. (38.7%) and Acremonium sp. (9.7%). Using RT-PCR, only A. fumigatus was detected in air samples collected, and only from partial underground plant. Stachybotrys chartarum was not detected in any of the samples analyzed. The distribution of particle sizes showed the same tendency in both plants; however, the partially underground plant presented higher levels of contamination, except for PM2.5. Fungal contamination assessment is crucial to evaluating the potential health risks to exposed workers in these settings. In order to achieve an evaluation of potential health risks to exposed workers, it is essential to combine conventional and molecular methods for fungal detection. Protective measures to minimize worker exposure to fungi need to be adopted since wastewater is the predominant internal fungal source in this setting.

Optimizing the renewable generation mix in the portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.

Multilayer Perceptron Neural Networks Training Through Charged System Search and its Application for Non-Technical Losses Detection

The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others natureinspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids.

DC Fuzzy Multicriteria Approach to Increase the Probability of Delivering Power in Distribution Networks

This paper proposes a methodology to increase the probability of delivering power to any load point through the identification of new investments. The methodology uses a fuzzy set approach to model the uncertainty of outage parameters, load and generation. A DC fuzzy multicriteria optimization model considering the Pareto front and based on mixed integer non-linear optimization programming is developed in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power to all customers in the distribution network at the minimum possible cost for the system operator, while minimizing the non supplied energy cost. To illustrate the application of the proposed methodology, the paper includes a case study which considers an 33 bus distribution network.

Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.

Application of Visual-Inertial SLAM for 3D Mapping of Underground Environments

The underground scenarios are one of the most challenging environments for accurate and precise 3d mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS measurements acquired outside the tunnel. Results from the localization strategy are presented and analyzed.

Implementation of an IoT-based Sensor Network Integrating IoT-based Sensor Networks with Large-Scale Message Distribution

As technology advances not only do new standards and programming styles appear but also some of the previously established ones gain relevance. In a new Internet paradigm where interconnection between small devices is key to the development of new businesses and scientific advancement there is the need to find simple solutions that anyone can implement in order to allow ideas to become more than that, ideas. Open-source software is still alive and well, especially in the area of the Internet of Things. This opens windows for many low capital entrepreneurs to experiment with their ideas and actually develop prototypes, which can help identify problems with a project or shine light on possible new features and interactions. As programming becomes more and more popular between people of fields not related to software there is the need for guidance in developing something other than basic algorithms, which is where this thesis comes in: A comprehensive document explaining the challenges and available choices of developing a sensor data and message delivery system, which scales well and implements the delivery of critical messages. Modularity and extensibility were also given much importance, making this an affordable tool for anyone that wants to build a sensor network of the kind.

Progressivity in the Portuguese personal income tax system

This Work Project analyzes the evolution of the Portuguese personal income tax system’s progressivity over the period of 2005 through 2013. It presents the first computation of cardinal progressivity measures using administrative tax data for Portugal. We compute several progressivity indices and find that progressivity has had very modest variations from 2005 to 2012, whilst from 2012 to 2013 there has been a relatively stronger decrease, excluding the impact of the income tax surcharge of the years 2012 and 2013. When this latter is included, progressivity of 2012 and 2013 decreases considerably. Analyzing the effective average tax rates of the top income percentiles in the income scale, we find that these rates have increased over the period 2010–2013, suggesting that an analysis of effective tax rates is insufficient to assess progressivity in the whole tax scheme.

Establishing an association between a peri-operative perfusion score system (PerfSCORE) and post-operative patient morbidity/mortality during CPB cardiac surgery.

BACKGROUND: To date, there is no quality assurance program that correlates patient outcome to perfusion service provided during cardiopulmonary bypass (CPB). A score was devised, incorporating objective parameters that would reflect the likelihood to influence patient outcome. The purpose was to create a new method for evaluating the quality of care the perfusionist provides during CPB procedures and to deduce whether it predicts patient morbidity and mortality. METHODS: We analysed 295 consecutive elective patients. We chose 10 parameters: fluid balance, blood transfused, Hct, ACT, PaO2, PaCO2, pH, BE, potassium and CPB time. Distribution analysis was performed using the Shapiro-Wilcoxon test. This made up the PerfSCORE and we tried to find a correlation to mortality rate, patient stay in the ICU and length of mechanical ventilation. Univariate analysis (UA) using linear regression was established for each parameter. Statistical significance was established when p < 0.05. Multivariate analysis (MA) was performed with the same parameters. RESULTS: The mean age was 63.8 +/- 12.6 years with 70% males. There were 180 CABG, 88 valves, and 27 combined CABG/valve procedures. The PerfSCORE of 6.6 +/- 2.4 (0-20), mortality of 2.7% (8/295), CPB time 100 +/- 41 min (19-313), ICU stay 52 +/- 62 hrs (7-564) and mechanical ventilation of 10.5 +/- 14.8 hrs (0-564) was calculated. CPB time, fluid balance, PaO2, PerfSCORE and blood transfused were significantly correlated to mortality (UA, p < 0.05). Also, CPB time, blood transfused and PaO2 were parameters predicting mortality (MA, p < 0.01). Only pH was significantly correlated for predicting ICU stay (UA). Ultrafiltration (UF) and CPB time were significantly correlated (UA, p < 0.01) while UF (p < 0.05) was the only parameter predicting mechanical ventilation duration (MA). CONCLUSIONS: CPB time, blood transfused and PaO2 are independent risk factors of mortality. Fluid balance, blood transfusion, PaO2, PerfSCORE and CPB time are independent parameters for predicting morbidity. PerfSCORE is a quality of perfusion measure that objectively quantifies perfusion performance.

Medication incidents in primary care medicine: protocol of a study by the Swiss Federal Sentinel Reporting System.

BACKGROUND/RATIONALE: Patient safety is a major concern in healthcare systems worldwide. Although most safety research has been conducted in the inpatient setting, evidence indicates that medical errors and adverse events are a threat to patients in the primary care setting as well. Since information about the frequency and outcomes of safety incidents in primary care is required, the goals of this study are to describe the type, frequency, seasonal and regional distribution of medication incidents in primary care in Switzerland and to elucidate possible risk factors for medication incidents. Label="METHODS AND ANALYSIS" ="METHODS"/> <AbstractText STUDY DESIGN AND SETTING: We will conduct a prospective surveillance study to identify cases of medication incidents among primary care patients in Switzerland over the course of the year 2015. PARTICIPANTS: Patients undergoing drug treatment by 167 general practitioners or paediatricians reporting to the Swiss Federal Sentinel Reporting System. INCLUSION CRITERIA: Any erroneous event, as defined by the physician, related to the medication process and interfering with normal treatment course. EXCLUSION CRITERIA: Lack of treatment effect, adverse drug reactions or drug-drug or drug-disease interactions without detectable treatment error. PRIMARY OUTCOME: Medication incidents. RISK FACTORS: Age, gender, polymedication, morbidity, care dependency, hospitalisation. STATISTICAL ANALYSIS: Descriptive statistics to assess type, frequency, seasonal and regional distribution of medication incidents and logistic regression to assess their association with potential risk factors. Estimated sample size: 500 medication incidents. LIMITATIONS: We will take into account under-reporting and selective reporting among others as potential sources of bias or imprecision when interpreting the results. ETHICS AND DISSEMINATION: No formal request was necessary because of fully anonymised data. The results will be published in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: NCT0229537.

Soft tissue artifact distribution on lower limbs during treadmill gait: Influence of skin markers' location on cluster design.

Segment poses and joint kinematics estimated from skin markers are highly affected by soft tissue artifact (STA) and its rigid motion component (STARM). While four marker-clusters could decrease the STA non-rigid motion during gait activity, other data, such as marker location or STARM patterns, would be crucial to compensate for STA in clinical gait analysis. The present study proposed 1) to devise a comprehensive average map illustrating the spatial distribution of STA for the lower limb during treadmill gait and 2) to analyze STARM from four marker-clusters assigned to areas extracted from spatial distribution. All experiments were realized using a stereophotogrammetric system to track the skin markers and a bi-plane fluoroscopic system to track the knee prosthesis. Computation of the spatial distribution of STA was realized on 19 subjects using 80 markers apposed on the lower limb. Three different areas were extracted from the distribution map of the thigh. The marker displacement reached a maximum of 24.9mm and 15.3mm in the proximal areas of thigh and shank, respectively. STARM was larger on thigh than the shank with RMS error in cluster orientations between 1.2° and 8.1°. The translation RMS errors were also large (3.0mm to 16.2mm). No marker-cluster correctly compensated for STARM. However, the coefficient of multiple correlations exhibited excellent scores between skin and bone kinematics, as well as for STARM between subjects. These correlations highlight dependencies between STARM and the kinematic components. This study provides new insights for modeling STARM for gait activity.

Investigation of the applicability of LVDC microgrids in utility distribution in Russia

The research towards efficient, reliable and environmental-friendly power supply solutions is producing growing interest to the “Smart Grid” approach for the development of the electricity networks and managing the increasing energy consumption. One of the novel approaches is an LVDC microgrid. The purpose of the research is to analyze the possibilities for the implementation of LVDC microgrids in public distribution networks in Russia. The research contains the analysis of the modern Russian electric power industry, electricity market, electricity distribution business, regulatory framework and standardization, related to the implementation of LVDC microgrid concept. For the purpose of the economic feasibility estimation, a theoretical case study for comparing low voltage AC and medium voltage AC with LVDC microgrid solutions for a small settlement in Russia is presented. The results of the market and regulatory framework analysis along with the economic comparison of AC and DC solutions show that implementation of the LVDC microgrid concept in Russia is possible and can be economically feasible. From the electric power industry and regulatory framework point of view, there are no serious obstacles for the LVDC microgrids in Russian distribution networks. However, the most suitable use cases at the moment are expected to be found in the electrification of remote settlements, which are isolated from the Unified Energy System of Russia.

The mechanism of the regulation of energy distribution between photosystems 1 and 2 in the cyanobacterium Synechococcus sp. strain PCC 7002 /

Cyanobacteria are able to regulate the distribution of absorbed light energy between photo systems 1 and 2 in response to light conditions. The mechanism of this regulation (the state transition) was investigated in the marine cyanobacterium Synechococcus sp. strain PCC 7002. Three cell types were used: the wild type, psaL mutant (deletion of a photo system 1 subunit thought to be involved in photo system 1 trimerization) and the apcD mutant (a deletion of a phycobilisome subunit thought to be responsible for energy transfer to photo system 1). Evidence from 77K fluorescence emission spectroscopy, room temperature fluorescence and absorption cross-section measurements were used to determine a model of energy distribution from the phycobilisome and chlorophyll antennas in state 1 and state 2. The data confirm that in state 1 the phycobilisome is primarily attached to PS2. In state 2, a portion of the phycobilisome absorbed light energy is redistributed to photo system 1. This energy is directly transferred to photo system 1 by one of the phycobilisome terminal emitters, the product of the apcD gene, rather than via the photo system 2 chlorophyll antenna by spillover (energy transfer between the photo system 2 and photo system 1 chlorophyll antenna). The data also show that energy absorbed by the photo system 2 chlorophyll antenna is redistributed to photo system 1 in state 2. This could occur in one of two ways; by spillover or in a way analogous to higher plants where a segment of the chlorophyll antenna is dissociated from photo system 2 and becomes part of the photo system 1 antenna. The presence of energy transfer between neighbouring photo system 2 antennae was determined at both the phycobilisome and chlorophyll level, in states 1 and 2. Increases in antenna absorption cross-section with increasing reaction center closure showed that there is energy transfer (connectivity) between photosystem 2 antennas. No significant difference was shown in the amount of connectivity under these four conditions.