Investigation of the impact of load tap changers and automatic generation control on cascading events

This paper presents an assessment of the impact of control mechanisms, specifically load tap changers (LTCs) and automatic generation control (AGC), on cascading events in power systems with renewable generation. In order to identify the impact of these voltage and frequency related mechanisms, a large number of dynamic RMS simulations for various operating conditions is performed taking into consideration renewable generation, system loading and the action of protection devices. The sequences in which the cascading events appear are analysed, and each cascading event is described by the component that trips, the time and the reason for tripping. The number and reason of cascading events, the average load loss and the time between consecutive events are used as metrics to quantify the impact of LTCs and AGC. The study is demonstrated on a modified version of the IEEE-39 bus model with renewable generation and protection devices

Online identification of cascading events in power systems with renewable generation using measurement data and machine learning

This paper introduces a framework for online identification of cascading events in power systems with renewable generation, based on supervised machine learning techniques and measurement data. Cascading events are low-probability, high-impact events, the propagation of which can lead even to large-scale blackouts, with severe consequences to society. The proposed methodology is based on Long-short term memory networks, considering uncertainties associated with renewable generation, system loading and initial contingencies. By utilizing time-series measurement data, the proposed method can predict the appearance of cascading events, as defined by the discrete action of protection devices which can capture voltage, frequency or transient instability related dynamic phenomena. The proposed framework is applied on a modified version of the IEEE-39 bus model incorporating detailed dynamic renewable generation and protection devices implementations. Results highlight that the suggested method can successfully identify cases with cascading events with up to 95.6% accuracy and with an average inference time of 0.042s, taking into account practical considerations related to phasor measurement units, such as availability and noise in measurement data

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Investigation of Cascading Events in Power Systems with Renewable Generation

The paper introduces a framework for characterisation and investigation of cascading events in power systems with renewable generation using time domain dynamic simulations. The paper aims at identifying the cascading event patterns by including protection device operation in RMS simulations and analyzing them. The cascading events are characterised by the power system components involved, the sequence of trippings and the reason for failure (e.g. voltage/frequency), while considering a wide range of possible operating conditions defined by economic dispatch. Changes in observed cascading failure patterns for different operating conditions are identified and investigated, taking also into consideration the impact of renewable generation. The framework is demonstrated on a modified version of the Anderson-Fouad 9 bus model incorporating renewable generation and protection devices

Investigation of the impact of load tap changers and automatic generation control on cascading events

This paper presents an assessment of the impact of control mechanisms, specifically load tap changers (LTCs) and automatic generation control (AGC), on cascading events in power systems with renewable generation. In order to identify the impact of these voltage and frequency related mechanisms, a large number of dynamic RMS simulations for various operating conditions is performed taking into consideration renewable generation, system loading and the action of protection devices. The sequences in which the cascading events appear are analysed, and each cascading event is described by the component that trips, the time and the reason for tripping. The number and reason of cascading events, the average load loss and the time between consecutive events are used as metrics to quantify the impact of LTCs and AGC. The study is demonstrated on a modified version of the IEEE-39 bus model with renewable generation and protection devices.</p

A method for variance-based sensitivity analysis of cascading failures

Cascading failures of relay operations in power systems are inherently linked with the propagation of wide-area power system blackouts. In this paper, we consider a power system cascading failure as an indicator matrix encoding: what power system relays operated within a cascading failure inherently capturing the component and the sequence of tripping events. We propose that this matrix may then be used with extended forms of variance-based sensitivity estimators to quantitatively rank how sensitive observed power system cascading failures are to power system variables, considering overall system cascading failures as well as cascading failures grouped by network area and relay types. We demonstrate our proposed method by investigating the sensitivity of cascading failures to relay parameters, system conditions, and fault location using a version of the IEEE 39 bus model modified to include protection relays, wind farms, and tap-changing transformers. Input power system variables included: system operational scenario, disturbance location, relay parameters or thresholds. The Case Studies' results confirm the method's utility by successfully generating relative rankings of input variables' importance with respect to cascading failure propagation. The results also show cascading failures' sensitivity to input variables to be high due to non-linear relationships between input variables and cascading failures

Delaying surgery for patients with a previous SARS-CoV-2 infection

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