Power quality in DC distribution networks

This paper presents an overview of power quality in low-voltage DC distribution networks. We study which of the power quality disturbances in AC networks are also relevant in DC networks, as well as other disturbances specific to DC networks. The paper reviews the current status of international regulations in this topic and proposes different indices for the detection and characterization of the main types of power quality disturbances, presenting some results obtained in different laboratory tests in DC networks using different DC voltage shapes delivered by different DC power source types

Power Quality Concerns in Implementing Smart Distribution-Grid Applications

This paper maps the expected and possible adverse consequences for power quality of introducing several smart distribution-grid technologies and applications. The material presented in this paper is the result of discussions in an international CIGRE-CIRED joint working group. The following technologies and applications are discussed: 1) microgrids; 2) advanced voltage control; 3) feeder reconfiguration; and 4) demand-side management. Recommendations are given based on the mapping

Rapid Voltage Changes in Power System Networks and Their Effect on Flicker

A rapid voltage change (RVC) is a type of power-quality (PQ) disturbance that has not received sufficient attention in the international PQ standards. Presently, EC 61000-4-30, Ed. 3, defines a precise method for RVC detection and analysis. RVCs can cause or contribute to flicker. However, the existing studies on the subject have not found a correlation between the short-term flicker severity index Pst and the parameters of an RVC event. This paper provides an interpretation of this lack of correlation and shows that instead there is a correlation of RVC events with the instantaneous flicker sensation Pinst. This work is based on the analysis of both simulated waveforms containing RVCs and waveforms recorded in low-voltage and medium-voltage locations

Predicting Electrical Faults in Power Distribution Network

Electricity is becoming increasingly important in modern civilization, and as a result, the emphasis on and use of power infrastructure is gradually expanding. Simultaneously, investment and distribution modes are shifting from the large-scale centralized generation of electricity and sheer consumption to decentralized generators and extremely sophisticated clients. This transformation puts further strain on old infrastructure, necessitating significant expenditures in future years to ensure a consistent supply. Subsequent technical and prediction technologies can help to maximize the use of the current grid while lowering the probability of faults. This study discusses some of the local grid difficulties as well as a prospective maintenance and failure probabilistic model. To provide an effective and convenient power source to consumers, a high Volta protects and maintains under fault conditions. Most of the fault identification and localization approaches rely on real and reactive power converter observations of electronic values. This can be seen in metrics and ground evaluations derived via internet traffic. This paper provides a thorough examination of the mechanisms for error detection, diagnosis, and localization in overhead lines. The proposal is then able to make suggestions about the ways that can be incorporated to predict foreseen faults in the electrical network. The three classifiers, Random Forest, XGBoost and Decision tree are producing high accuracies, while Logistic Regression and SVM are producing realistic accuracy results

Non-invasive vascular assessment using photoplethysmography

Photoplethysmography (PPG) has become widely accepted as a valuable clinical tool for performing non-invasive biomedical monitoring. The dominant clinical application of PPG has been pulse oximetry, which uses spectral analysis of the peripheral blood supply to establish haemoglobin saturation. PPG has also found success in screening for venous dysfunction, though to a limited degree. Arterial Disease (AD) is a condition where blood flow in the arteries of the body is reduced,a condition known as ischaernia. Ischaernia can result in pain in the affected areas, such as chest pain for an ischearnic heart, but does not always produce symptoms. The most common form of AD is arteriosclerosis, which affects around 5% of the population over 50 years old. Arteriosclerosis, more commonly known as 'hardening of the arteries' is a condition that results in a gradual thickening, hardening and loss of elasticity in the walls of the arteries, reducing overall blood flow. This thesis investigates the possibility of employing PPG to perform vascular assessment, specifically arterial assessment, in two ways. PPG based perfusion monitoring may allow identification of ischaernia in the periphery. To further investigate this premise, prospective experimental trials are performed, firstly to assess the viability of PPG based perfusion monitoring and culminating in the development of a more objective method for determining ABPI using PPG based vascular assessment. A complex interaction between the heart and the connective vasculature, detected at the measuring site, generates the PPG signal. The haemodynamic properties of the vasculature will affect the shape of the PPG waveform, characterising the PPG signal with the properties of the intermediary vasculature. This thesis investigates the feasibility of deriving quantitative vascular parameters from the PPG signal. A quantitative approach allows direct identification of pathology, simplifying vascular assessment. Both forward and inverse models are developed in order to investigate this topic. Application of the models in prospective experimental trials with both normal subjects and subjects suffering PVD have shown encouraging results. It is concluded that the PPG signal contains information on the connective vasculature of the subject. PPG may be used to perform vascular assessment using either perfusion based techniques, where the magnitude of the PPG signal is of interest, or by directly assessing the connective vasculature using PPG, where the shape of the PPG signal is of interest. it is argued that PPG perfusion based techniques for performing the ABPI diagnosis protocol can offer greater sensitivity to the onset of PAD, compared to more conventional methods. It is speculated that the PPG based ABPI diagnosis protocol could provide enhanced PAD diagnosis, detecting the onset of the disease and allowing a treatmenpt lan to be formed soonert han was possible previously. The determination of quantitative vascular parameters using PPG shape could allow direct vascular diagnosis, reducing subjectivity due to interpretation. The prospective trials investigating PPG shape analysis concentrated on PVD diagnosis, but it is speculated that quantitative PPG shaped based vascular assessment could be a powerful tool in the diagnosis of many vascular based pathological conditions

PMU-based distribution system state estimation with adaptive accuracy exploiting local decision metrics and IoT paradigm

A novel adaptive distribution system state estimation (DSSE) solution is presented and discussed, which relies on distributed decision points and exploits the Cloud-based Internet of Things (IoT) paradigm. Up to now, DSSE procedures have been using fixed settings regardless of the actual values of measurement accuracy, which is instead affected by the actual operating conditions of the network. The proposed DSSE is innovative with respect to previous literature, because it is adaptive in the use of updated accuracies for the measurement devices. The information used in the estimation process along with the rate of the execution are updated, depending on the indications of appropriate local metrics aimed at detecting possible variations in the operating conditions of the distribution network. Specifically, the variations and the trend of variation of the rms voltage values obtained by phasor measurement units (PMUs) are used to trigger changes in the DSSE. In case dynamics are detected, the measurement data are sent to the DSSE at higher rates and the estimation process runs consequently, updating the accuracy values to be considered in the estimation. The proposed system relies on a Cloud-based IoT platform, which has been designed to incorporate heterogeneous measurement devices, such as PMUs and smart meters. The results obtained on a 13-bus system demonstrate the validity of the proposed methodology that is efficient both in the estimation process and in the use of the communication resources

AI Applications to Power Systems

Today, the flow of electricity is bidirectional, and not all electricity is centrally produced in large power plants. With the growing emergence of prosumers and microgrids, the amount of electricity produced by sources other than large, traditional power plants is ever-increasing. These alternative sources include photovoltaic (PV), wind turbine (WT), geothermal, and biomass renewable generation plants. Some renewable energy resources (solar PV and wind turbine generation) are highly dependent on natural processes and parameters (wind speed, wind direction, temperature, solar irradiation, humidity, etc.). Thus, the outputs are so stochastic in nature. New data-science-inspired real-time solutions are needed in order to co-develop digital twins of large intermittent renewable plants whose services can be globally delivered

Saigas on the brink: Multidisciplinary analysis of the factors influencing mass mortality events

In 2015, more than 200,000 saiga antelopes died in 3 weeks in central Kazakhstan. The proximate cause of death is confirmed as hemorrhagic septicemia caused by the bacterium Pasteurella multocida type B, based on multiple strands of evidence. Statistical modeling suggests that there was unusually high relative humidity and temperature in the days leading up to the mortality event; temperature and humidity anomalies were also observed in two previous similar events in the same region. The modeled influence of environmental covariates is consistent with known drivers of hemorrhagic septicemia. Given the saiga population’s vulnerability to mass mortality and the likely exacerbation of climate-related and environmental stressors in the future, management of risks to population viability such as poaching and viral livestock disease is urgently needed, as well as robust ongoing veterinary surveillance. A multidisciplinary approach is needed to research mass mortality events under rapid environmental change

NASA Tech Briefs, September 2011

Topics covered include: Fused Reality for Enhanced Flight Test Capabilities; Thermography to Inspect Insulation of Large Cryogenic Tanks; Crush Test Abuse Stand; Test Generator for MATLAB Simulations; Dynamic Monitoring of Cleanroom Fallout Using an Air Particle Counter; Enhancement to Non-Contacting Stress Measurement of Blade Vibration Frequency; Positively Verifying Mating of Previously Unverifiable Flight Connectors; Radiation-Tolerant Intelligent Memory Stack - RTIMS; Ultra-Low-Dropout Linear Regulator; Excitation of a Parallel Plate Waveguide by an Array of Rectangular Waveguides; FPGA for Power Control of MSL Avionics; UAVSAR Active Electronically Scanned Array; Lockout/Tagout (LOTO) Simulator; Silicon Carbide Mounts for Fabry-Perot Interferometers; Measuring the In-Process Figure, Final Prescription, and System Alignment of Large; Optics and Segmented Mirrors Using Lidar Metrology; Fiber-Reinforced Reactive Nano-Epoxy Composites; Polymerization Initiated at the Sidewalls of Carbon Nanotubes; Metal-Matrix/Hollow-Ceramic-Sphere Composites; Piezoelectrically Enhanced Photocathodes; Iridium-Doped Ruthenium Oxide Catalyst for Oxygen Evolution; Improved Mo-Re VPS Alloys for High-Temperature Uses; Data Service Provider Cost Estimation Tool; Hybrid Power Management-Based Vehicle Architecture; Force Limit System; Levitated Duct Fan (LDF) Aircraft Auxiliary Generator; Compact, Two-Sided Structural Cold Plate Configuration; AN Fitting Reconditioning Tool; Active Response Gravity Offload System; Method and Apparatus for Forming Nanodroplets; Rapid Detection of the Varicella Zoster Virus in Saliva; Improved Devices for Collecting Sweat for Chemical Analysis; Phase-Controlled Magnetic Mirror for Wavefront Correction; and Frame-Transfer Gating Raman Spectroscopy for Time-Resolved Multiscalar Combustion Diagnostics