Reducing uncertainty – responses for electricity utilities to severe solar storms

Until recently, electricity utilities in mid- and low-latitude regions believed that solar storms had no (or only insignificant) effect on their power systems. Then it was noticed that the onset of damage in several large transformers, leading to their failure, correlated very closely with the Halloween storm of 2003. Since then engineers have started to appreciate that a very severe storm could have serious consequences outside the high-latitude regions. There are many uncertainties in predicting the effects of solar storms on electrical systems. The severity and time of arrival of a storm are difficult to model; so are the geomagnetically induced currents (GICs) expected to flow in the power networks. Published information about the responses of different types of transformers to GICs is contradictory. Measurements of the abnormal power flows in networks during solar storms generally do not take into account the effects of the current distortion and unbalance, potentially giving misleading signals to the operators. The normal requirement for optimum system management, while allowing for the possibility of faults caused by lightning, birds and other causes, limits the capacity of system operators to respond to the threats of GICs, which are not assessed easily by the N − 1 reliability criterion. A utility’s response to the threat of damage by GICs depends on the expected frequency and magnitude of solar storms. Approaches to formulating a response are located in a system model incorporating space physics, network analysis, transformer engineering, network reliability and decision support and the benefits are identified. Approaches adopted in high-latitude regions might not be appropriate where fewer storms are expected to reach damaging levels. The risks of an extreme storm cannot be ignored, and understanding the response mechanisms suitable for low-latitude regions has the capacity to inform and reduce the uncertainty for power systems planners and operators worldwide

Reliability worth assessment of electricity consumers: a South African case study

This paper discusses the results obtained from a customer survey conducted in Cape Town, South Africa, using in-person interviews with approximately 275 sample business customers. The survey included customer interruption cost estimation questions based on the direct costing method. The results obtained show that customer interruption cost for business customers varies with duration and time of occurrence of power interruptions. The variation was shown to be dependent on customer segment. Furthermore, it revealed that business customers can be grouped in terms of the investment they make to mitigate the impact of power interruptions on their activities, such as the use of backup power supplies

Challenges, solutions and lessons learnt from testing power system performance with a general power theory-controlled converter

A novel control approach for power-electronic converters has been shown to reduce the losses in delivery systems to below the levels possible with conventional methods. In this research, an 80 kW converter was retrofitted to operate using the General Power Theory (GPT). The effect of compensation using the GPT in a three-bus test network was studied by Simulink simulation and in the physical power system infrastructure of the Power Networks Demonstration Centre. The simulation results demonstrated that the converter did not need the concept of reactive power for control and could improve the system power factor. The experimental measurements were used for comparison with the simulation results. Challenges faced during experimental testing are discussed. Solutions are proposed to resolve some of the measurement problems that hindered the full experimental validation at this stage. The practical lessons learnt are helpful for future tests and identified real-world issues that may be encountered during deployment

Feature Selection To Facilitate Surgical Planning From MRI Of Placenta Accreta Spectrum Disorder

Feature Selection Models provide a ranking of pathological MRI markers able to predict the outcome of Placenta Accreta Spectrum Disorder, which could be used to aid in clinical decision-making and improve maternal outcome. The potential being to reduce the workload of radiologists by establishing the most clinically relevant pathological MRI markers that predict outcome. Our results found three pathological markers to have the highest ranking to the outcomes with an average accuracy of 75% using a Random Forest Selection Model and Boruta algorithm

Use of Super Resolution Reconstruction MRI for surgical planning in Placenta Accreta Spectrum Disorder: Case Series

INTRODUCTION: Comprehensive imaging using ultrasound and MRI of placenta accreta spectrum (PAS) aims to prevent catastrophic haemorrhage and maternal death. Standard MRI of the placenta is limited by between-slice motion which can be mitigated by super-resolution reconstruction (SRR) MRI. We applied SRR in suspected PAS cases to determine its ability to enhance anatomical placental assessment and predict adverse maternal outcome. METHODS: Suspected PAS patients (n = 22) underwent MRI at a gestational age (weeks + days) of (32+3±3+2, range (27+1-38+6)). SRR of the placental-myometrial-bladder interface involving rigid motion correction of acquired MRI slices combined with robust outlier detection to reconstruct an isotropic high-resolution volume, was achieved in twelve. 2D MRI or SRR images alone, and paired data were assessed by four radiologists in three review rounds. All radiologists were blinded to results of the ultrasound, original MR image reports, case outcomes, and PAS diagnosis. A Random Forest Classification model was used to highlight the most predictive pathological MRI markers for major obstetric haemorrhage (MOH), bladder adherence (BA), and placental attachment depth (PAD). RESULTS: At delivery, four patients had placenta praevia with no abnormal attachment, two were clinically diagnosed with PAS, and six had histopathological PAS confirmation. Pathological MRI markers (T2-dark intraplacental bands, and loss of retroplacental T2-hypointense line) predicting MOH were more visible using SRR imaging (accuracy 0.73), in comparison to 2D MRI or paired imaging. Bladder wall interruption, predicting BA, was only easily detected by paired imaging (accuracy 0.72). Better detection of certain pathological markers predicting PAD was found using 2D MRI (placental bulge and myometrial thinning (accuracy 0.81)), and SRR (loss of retroplacental T2-hypointense line (accuracy 0.82)). DISCUSSION: The addition of SRR to 2D MRI potentially improved anatomical assessment of certain pathological MRI markers of abnormal placentation that predict maternal morbidity which may benefit surgical planning

A risk assessment framework for the socio-economic impacts of electricity transmission infrastructure failure due to space weather: an application to the United Kingdom

Space weather phenomena have been studied in detail in the peer‐reviewed scientific literature. However, there has arguably been scant analysis of the potential socioeconomic impacts of space weather, despite a growing gray literature from different national studies, of varying degrees of methodological rigor. In this analysis, we therefore provide a general framework for assessing the potential socioeconomic impacts of critical infrastructure failure resulting from geomagnetic disturbances, applying it to the British high‐voltage electricity transmission network. Socioeconomic analysis of this threat has hitherto failed to address the general geophysical risk, asset vulnerability, and the network structure of critical infrastructure systems. We overcome this by using a three‐part method that includes (i) estimating the probability of intense magnetospheric substorms, (ii) exploring the vulnerability of electricity transmission assets to geomagnetically induced currents, and (iii) testing the socioeconomic impacts under different levels of space weather forecasting. This has required a multidisciplinary approach, providing a step toward the standardization of space weather risk assessment. We find that for a Carrington‐sized 1‐in‐100‐year event with no space weather forecasting capability, the gross domestic product loss to the United Kingdom could be as high as £15.9 billion, with this figure dropping to £2.9 billion based on current forecasting capability. However, with existing satellites nearing the end of their life, current forecasting capability will decrease in coming years. Therefore, if no further investment takes place, critical infrastructure will become more vulnerable to space weather. Additional investment could provide enhanced forecasting, reducing the economic loss for a Carrington‐sized 1‐in‐100‐year event to £0.9 billion

Space Plasma Physics: A Review

Owing to the ever-present solar wind, our vast solar system is full of plasmas. The turbulent solar wind, together with sporadic solar eruptions, introduces various space plasma processes and phenomena in the solar atmosphere all the way to Earth’s ionosphere and atmosphere and outward to interact with the interstellar media to form the heliopause and termination shock. Remarkable progress has been made in space plasma physics in the last 65 years, mainly due to sophisticated in situ measurements of plasmas, plasma waves, neutral particles, energetic particles, and dust via space-borne satellite instrumentation. Additionally, high-technology ground-based instrumentation has led to new and greater knowledge of solar and auroral features. As a result, a new branch of space physics, i.e., space weather, has emerged since many of the space physics processes have a direct or indirect influence on humankind

Chest radiograph classification and severity of suspected COVID-19 by different radiologist groups and attending clinicians: multi-reader, multi-case study.

OBJECTIVES: To quantify reader agreement for the British Society of Thoracic Imaging (BSTI) diagnostic and severity classification for COVID-19 on chest radiographs (CXR), in particular agreement for an indeterminate CXR that could instigate CT imaging, from single and paired images. METHODS: Twenty readers (four groups of five individuals)-consultant chest (CCR), general consultant (GCR), and specialist registrar (RSR) radiologists, and infectious diseases clinicians (IDR)-assigned BSTI categories and severity in addition to modified Covid-Radiographic Assessment of Lung Edema Score (Covid-RALES), to 305 CXRs (129 paired; 2 time points) from 176 guideline-defined COVID-19 patients. Percentage agreement with a consensus of two chest radiologists was calculated for (1) categorisation to those needing CT (indeterminate) versus those that did not (classic/probable, non-COVID-19); (2) severity; and (3) severity change on paired CXRs using the two scoring systems. RESULTS: Agreement with consensus for the indeterminate category was low across all groups (28-37%). Agreement for other BSTI categories was highest for classic/probable for the other three reader groups (66-76%) compared to GCR (49%). Agreement for normal was similar across all radiologists (54-61%) but lower for IDR (31%). Agreement for a severe CXR was lower for GCR (65%), compared to the other three reader groups (84-95%). For all groups, agreement for changes across paired CXRs was modest. CONCLUSION: Agreement for the indeterminate BSTI COVID-19 CXR category is low, and generally moderate for the other BSTI categories and for severity change, suggesting that the test, rather than readers, is limited in utility for both deciding disposition and serial monitoring. KEY POINTS: • Across different reader groups, agreement for COVID-19 diagnostic categorisation on CXR varies widely. • Agreement varies to a degree that may render CXR alone ineffective for triage, especially for indeterminate cases. • Agreement for serial CXR change is moderate, limiting utility in guiding management