P-class phasor measurement unit algorithms using adaptive filtering to enhance accuracy at off-nominal frequencies

While the present standard C.37.118-2005 for Phasor Measurement Units (PMUs) requires testing only at steady-state conditions, proposed new versions of the standard require much more stringent testing, involving frequency ramps and off-nominal frequency testing. This paper presents two new algorithms for “P Class” PMUs which enable performance at off-nominal frequencies to be retained at levels comparable to the performance for nominal frequency input. The performances of the algorithms are compared to the “Basic” Synchrophasor Estimation Model described in the new standard. The proposed algorithms show a much better performance than the “Basic” algorithm, particularly in the measurements of frequency and rate-of-change-of-frequency at off-nominal frequencies and in the presence of unbalance and harmonics

Medium voltage fault location using distributed LV measurements

An MV fault location technique based exclusively on low voltage measurements in the distribution network is presented in this paper. The technique is based on sequence component analysis of the voltage measurements in order to characterise the LV voltage during MV faults. The accuracy of the technique is evaluated using a DigSILENT PowerFactory model where various fault conditions have been studied including the impact of distributed generation connection on the network voltage profile. The model represents the Power Networks Demonstration Centre’s (PNDC) MV and LV test network. This is to facilitate the validation of the model in the future implementing physical fault testing and measurements using the PNDC network

Impact of realistic communications for fast-acting demand side management

The rising penetration of intermittent energy resources is increasing the need for more diverse electrical energy resources that are able to support ancillary services. Demand side management (DSM) has a significant potential to fulfil this role but several challenges are still impeding the wide-scale integration of DSM. One of the major challenges is ensuring the performance of the networks that enable communications between control centres and the end DSM resources. This paper presents an analysis of all communications networks that typically participate in the activation of DSM, and provides an estimate for the overall latency that these networks incur. The most significant sources of delay from each of the components of the communications network are identified which allows the most critical aspects to be determined. This analysis therefore offers a detailed evaluation of the performance of DSM resources in the scope of providing real-time ancillary services. It is shown that, using available communications technologies, DSM can be used to provide primary frequency support services. In some cases, Neighbourhood Area Networks (NANs) may add significant delay, requiring careful choice of the technologies deployed

Adaptive protection architecture for the smart grid

Unique and varied power system conditions are already being experienced as a result of the deployment of novel control strategies and new generation and distribution related technologies driven by the smart grid. A particular challenge is related to ensuring the correct and reliable operation of protection schemes. Implementing smarter protection in the form of adaptive setting selection is one way of tackling some of the protection performance issues. However, introducing such new approaches especially to safety critical systems such as protection carries an element of risk. Furthermore, integrating new secondary systems into the substation is a complex and costly procedure. To this end, this paper proposes an adaptive protection architecture that facilitates the integration of such schemes into modern digital substations which are a staple of smart grids. Functional features of the architecture also offer powerful means of de-risking schemes and flexible implementation through self-contained modules that are suitable for reuse. An example adaptive distance protection scheme is presented and tested to demonstrate how the architecture can be implemented and to highlight the architecture's novel features

ERIGrid Holistic Test Description for Validating Cyber-Physical Energy Systems

Smart energy solutions aim to modify and optimise the operation of existing energy infrastructure. Such cyber-physical technology must be mature before deployment to the actual infrastructure, and competitive solutions will have to be compliant to standards still under development. Achieving this technology readiness and harmonisation requires reproducible experiments and appropriately realistic testing environments. Such testbeds for multi-domain cyber-physical experiments are complex in and of themselves. This work addresses a method for the scoping and design of experiments where both testbed and solution each require detailed expertise. This empirical work first revisited present test description approaches, developed a newdescription method for cyber-physical energy systems testing, and matured it by means of user involvement. The new Holistic Test Description (HTD) method facilitates the conception, deconstruction and reproduction of complex experimental designs in the domains of cyber-physical energy systems. This work develops the background and motivation, offers a guideline and examples to the proposed approach, and summarises experience from three years of its application.This work received funding in the European Community’s Horizon 2020 Program (H2020/2014–2020) under project “ERIGrid” (Grant Agreement No. 654113)

Data driven transformer level misconfiguration detection in power distribution grids

As more novel devices are integrated into the electricity grid due to the changes taking place in the energy system, ways of detecting deviations from the intended settings are needed. If misconfigurations of, for example, reactive power control curves of inverters go unnoticed, the safe and reliable operation of the power grid can no longer be ensured due to possible voltage violations or overloadings. Therefore, methods of detection of misconfigurations of said inverters using operational data at transformers are presented and compared. These methods include preprocessing by dimensionality reduction as well as detection by supervised learning approaches. The data used is of high reliability as it was collected in a lab setting reenacting typical and relevant grid operation situations. Furthermore, this data was recreated by simulation to validate the simulation data, which could also potentially be used for detection applications on a bigger scale. The results for both data sources were compared and conclusions drawn about applicability and usability for grid operators

Analysis of the Impact of Relative Humidity and Mineral Nuclei Mode Aerosols Particle Concentration on the Visibility of Desert Aerosols

This paper presents the results of the Analysis of the Impact of relative humidity and water-soluble aerosol particle concentrations on the visibility and particle size distribution of desert aerosols based on microphysical properties of desert aerosols. The microphysical properties (the extinction coefficients, volume mix ratios, dry mode radii and wet mode radii) were extracted from Optical Properties of Aerosols and Clouds (OPAC 4.0) at eight relative humidities (00 to 99%RH) and at the spectral range of 0.4-0.8 mm. the concentrations of mineral nuclie component (MINN) were varied to obtain five different models. The angstrom exponent (a), the turbidity (b), the curvature (a2), humidification factor (g), the mean exponent of aerosol growth curve (µ) and the mean exponent of aerosol size distributions (n) were determined from the regression analysis of some standard equations. It was observed that the values of (a) are less than 1 throughout the 5 models which signifies the dominance of coarse mode particles over fine mode particles. It was observed that the curvature (a2) has both monomodal and bimodal types of distributions all through the 5 models and this signifies the dominance of coarse mode particles with some traces of fine mode particles. The visibility was observed to decrease with the increase in RH and increased with wavelength. The analysis further found that there is an inverse power law relationship between humidification factor, the mean exponent of the aerosol size distribution with the mean exponent of the aerosol growth curve (as the magnitude of (µ) decreases across the five models, the magnitudes of (g) and (n) increase, but the magnitude of both (g) and (n) increases for a given (µ) across the individual models). The mean exponent of aerosol size distribution (µ) being less than 3 indicate hazy condition of the desert atmosphere

The global burden of adolescent and young adult cancer in 2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults. Findings There were 1.19 million (95% UI 1.11-1.28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59.6 [54.5-65.7] per 100 000 person-years) and high-middle SDI countries (53.2 [48.8-57.9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14.2 [12.9-15.6] per 100 000 person-years) and middle SDI (13.6 [12.6-14.8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23.5 million (21.9-25.2) DALYs to the global burden of disease, of which 2.7% (1.9-3.6) came from YLDs and 97.3% (96.4-98.1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe