Planning of interconnected power systems considering security under cascading outages and catastrophic events

This work presents a method for assessing the vulnerability of a composite power system. It is based on the modeling of failures and repairs using stochastic point process theory and procedure of sequential Monte Carlo simulation to compute the indexes of vulnerability. Stochastic point process modeling allows including constant and time varying rates, a necessity in those scenarios considering aging and diverse maintenance strategies. It also allows representing the repair process performed in the power system as it really is: a queuing system. Sequential Monte Carlo simulation is applied because it can artificially generate all the aspects involved in the operating sequence of a power system and also because it can easily manage non stationary probabilistic models. The indexes of vulnerability are the probability of occurrence of a high order loss of component scenario, its frequency and its duration. A high order loss of component scenario is that one higher than n ? 2. Examples using the IEEE one Area RTS show how the presence of aging and others factor that produce increasing component failure rates increase dramatically the risk of occurrence of high order loss of component scenarios. On the other hand, the improvement in aspect such as preventive maintenance and repair performance reduces risk. Although the main focus of this method is composite power systems, its development gave another products such as procedures for assessment of power distribution systems, protective relaying schemes and power substations

• Autores: Zapata Grisales, Carlos Julio
• Tipo de recurso: Doctoral thesis
• Fecha de publicación: 2010
• Institución: Universidad de los Andes
• Repositorio: Séneca: repositorio Uniandes
• Idioma: eng
• OAI Identifier: oai:repositorio.uniandes.edu.co:1992/7765
• Acceso en línea: http://hdl.handle.net/1992/7765
• Palabra clave: Sistemas electrónicos de seguridad - Investigaciones; Confiabilidad (Ingeniería) - Investigaciones; Análisis estocástico - Investigaciones; Método de MonteCarlo - Investigaciones; Ingeniería
• Rights: openAccess
• License: https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf