Aplicación del control inteligente en oscilaciones usando FACTS (STATCOM y SVC)

Context: Reducing the oscillations of the electrical power systems is an important task in order to maintain their stability. This paper presents a methodology for adjusting the parameters of a fuzzy oscillations controller with a Static Var Compensator (SVC) and a Static Synchronous Compensator (STATCOM).Methodology: The methodology consists of tuning a fuzzy controller to dampen oscillations in an electrical power system, with different optimization techniques such as: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Chaotic Optimization Algorithm (COA).Results: The voltage and speed oscillations of a system composed of a synchronous machine connected to an infinite bus bar (SMIB) are obtained through simulations. There is data before and after connecting a SVC and a STATCOM, installed independently and in different operating conditions. The results obtained show that using a technique for adjusting parameters in the fuzzy controller is better than the adjustment of trial and error.Conclusion: With the obtained results, it is possible to verify the effectiveness of the fuzzy controller using Flexible AC Transmissions Systems (FACTS).Contexto: Reducir las oscilaciones de un sistema eléctrico de potencia es necesario para mantener la estabilidad del mismo. En este trabajo se presenta una metodología para la sintonización de un controlador de oscilaciones de tipo difuso, un compensador de Volts Ampere Reactive, (VAR, por sus siglas en inglés), uno estático (Static Var Compensator, SVC, por sus siglas en inglés), y un compensador estático síncrono (Static Synchronous Compensator, STATCOM, por sus siglas en inglés), por métodos inteligentes.Método: Consiste en sintonizar un controlador de tipo difuso para amortiguar las oscilaciones de un sistema eléctrico de potencia por medio de un STATCOM o un SVC, a través de diferentes técnicas de optimización tales como: algoritmos genéticos (GA, Genetic Algorithm), optimización por enjambre de partículas (PSO, Particle Swarm Optimization) y algoritmo de optimización caótica (COA, Chaotic Optimization Algorithm).Resultados: A través de simulación se obtienen las oscilaciones en el voltaje y la velocidad de un sistema compuesto por una máquina sincróna conectada a un barraje infinito (SMIB, Single Machine Infinite Bus) antes y después de conectar un SVC y un STATCOM, ambos instalados independientemente y en diferentes condiciones de operación. Los resultados muestran las ventajas de utilizar métodos de ajuste para el controlador difuso comparados con el ajuste a ensayo y error.Conclusión: A partir de los resultados obtenidos, se comprueba la efectividad del controlador difuso utilizado en el control de oscilaciones con dispositivos Flexible AC Transmissions Systems (FACTS, por sus siglas en inglés) tanto en el SVC como en el STATCOM

Smart control application in the oscillations using FACTS (STATCOM and SVC)

Context: Reducing the oscillations of the electrical power systems is an important task in order to maintain their stability. This paper presents a methodology for adjusting the parameters of a fuzzy oscillations controller with a Static Var Compensator (SVC) and a Static Synchronous Compensator (STATCOM). Methodology: The methodology consists of tuning a fuzzy controller to dampen oscillations in an electrical power system, with different optimization techniques such as: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Chaotic Optimization Algorithm (COA). Results: The voltage and speed oscillations of a system composed of a synchronous machine connected to an infinite bus bar (SMIB) are obtained through simulations. There is data before and after connecting a SVC and a STATCOM, installed independently and in different operating conditions. The results obtained show that using a technique for adjusting parameters in the fuzzy controller is better than the adjustment of trial and error. Conclusion: With the obtained results, it is possible to verify the effectiveness of the fuzzy controller using Flexible AC Transmissions Systems (FACTS)

Aplicación del control inteligente en oscilaciones usando FACTS (STATCOM y SVC)

Context: Reducing the oscillations of the electrical power systems is an important task in order to maintain their stability. This paper presents a methodology for adjusting the parameters of a fuzzy oscillations controller with a Static Var Compensator (SVC) and a Static Synchronous Compensator (STATCOM).Methodology: The methodology consists of tuning a fuzzy controller to dampen oscillations in an electrical power system, with different optimization techniques such as: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Chaotic Optimization Algorithm (COA).Results: The voltage and speed oscillations of a system composed of a synchronous machine connected to an infinite bus bar (SMIB) are obtained through simulations. There is data before and after connecting a SVC and a STATCOM, installed independently and in different operating conditions. The results obtained show that using a technique for adjusting parameters in the fuzzy controller is better than the adjustment of trial and error.Conclusion: With the obtained results, it is possible to verify the effectiveness of the fuzzy controller using Flexible AC Transmissions Systems (FACTS).Contexto: Reducir las oscilaciones de un sistema eléctrico de potencia es necesario para mantener la estabilidad del mismo. En este trabajo se presenta una metodología para la sintonización de un controlador de oscilaciones de tipo difuso, un compensador de Volts Ampere Reactive, (VAR, por sus siglas en inglés), uno estático (Static Var Compensator, SVC, por sus siglas en inglés), y un compensador estático síncrono (Static Synchronous Compensator, STATCOM, por sus siglas en inglés), por métodos inteligentes.Método: Consiste en sintonizar un controlador de tipo difuso para amortiguar las oscilaciones de un sistema eléctrico de potencia por medio de un STATCOM o un SVC, a través de diferentes técnicas de optimización tales como: algoritmos genéticos (GA, Genetic Algorithm), optimización por enjambre de partículas (PSO, Particle Swarm Optimization) y algoritmo de optimización caótica (COA, Chaotic Optimization Algorithm).Resultados: A través de simulación se obtienen las oscilaciones en el voltaje y la velocidad de un sistema compuesto por una máquina sincróna conectada a un barraje infinito (SMIB, Single Machine Infinite Bus) antes y después de conectar un SVC y un STATCOM, ambos instalados independientemente y en diferentes condiciones de operación. Los resultados muestran las ventajas de utilizar métodos de ajuste para el controlador difuso comparados con el ajuste a ensayo y error.Conclusión: A partir de los resultados obtenidos, se comprueba la efectividad del controlador difuso utilizado en el control de oscilaciones con dispositivos Flexible AC Transmissions Systems (FACTS, por sus siglas en inglés) tanto en el SVC como en el STATCOM

Effects of pre-operative isolation on postoperative pulmonary complications after elective surgery: an international prospective cohort study an international prospective cohort study

We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05–1.36, p = 0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3 days, with an OR (95%CI) at 4–7 days or ≥ 8 days of 1.25 (1.04–1.48), p = 0.015 and 1.31 (1.11–1.55), p = 0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care. We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05–1.36, p = 0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3 days, with an OR (95%CI) at 4–7 days or ≥ 8 days of 1.25 (1.04–1.48), p = 0.015 and 1.31 (1.11–1.55), p = 0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care