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A Novel Method for the Approximation of Risk of Blackout in Operational Conditions Lilliam Urrego Agudelo

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A Novel Method for the Approximation of Risk of Blackout in Operational Conditions Lilliam Urrego Agudelo A novel method for the Approximation of risk of Blackout in operational conditions Lilliam Urrego Agudelo To cite this version: Lilliam Urrego Agudelo. A novel method for the Approximation of risk of Blackout in operational con- ditions. Signal and Image Processing. Université Paris-Est, 2016. English. NNT : 2016PESC1071. tel-01552787 HAL Id: tel-01552787 https://tel.archives-ouvertes.fr/tel-01552787 Submitted on 3 Jul 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. UNIVERSITÉ PARIS EST THÈSE DE DOCTORAT PAR URREGO AGUDELO Lilliam -------------------------------------------------------------------------------------------------------- A novel method for the approximation of risk of blackout in operational conditions ---------------------------------------------------------------------------------------------------------- Soutenue le 04 novembre 2016 à Créteil devant le jury compose de: Rachid Outbib, Rapporteur Anne Philippe, Rapporteur Frederic Heliodore, Examinateur Serge Poullain, Examinateur El-Ghazali Talbi, Examinateur Amir Nakib, co-Directeur Patrick Siarry, Directeur November 2016 ii UNIVERSITÉ PARIS-EST Abstract A novel method for the Approximation of risk of "Blackout" in operational conditions. The electricity industry can be characterized by several risks: regulatory, adequacy, human error, etc. One of the most outstanding aspects, because of their impact, is related to not supply demand (DNS). To avoid these DNS problems: cascading failures or blackouts, much has been done on equipment reliability, security of the electrical systems, asset management, the learned lessons of the big events, contingency plans, and development of monitoring systems etc. To prevent cascading failures, particularly in reliability studies, determinist criteria were applied, such as N-1, which allows to avoid the initial event of failure in the planning and operation of the system. In general, analysis tools for these preventive actions are applied separately for the planning and for the system operation of an electric power. After a cascading failure, considerable efforts must be done to analyze faults to minimize the possibility of a similar event. In spite of all these efforts, blackouts or large cascading failures still happen, although events are considered to be rare due to the efforts of the industry. Indeed, it is a challenge from the point of view of analysis and simulation, due to the large number of possible interactions and their diversity and complexity, to obtain a good prediction of a situation. Moreover, effective methods for understanding this phenomenon, and to mitigate the cascading failures are not developed yet. In our work, a new methodology is proposed to estimate the blackout risk using complex systems models. This approach is based on the use of variables that can be precursors of a DNS event. In other terms, it is based on the study of the dependence or correlation iii between the variables involved in the blackout risk, and the self-organized criticality (SOC) property of complex systems. Once the SOC conditions are determined, a direct current statistical power flow model DC SPFM was executed to simulate the behavior of the system and its variables for the performance of the electrical system. Simulations results were compared to the real operation behavior of the electrical power system. The DC power flow is a simplified model, which represents the complex phenomenon in a simple way, however neglects some aspects of the events of operation of the system that can happen in blackouts. The representation of cascading failures and evolution of the network in a simple model allows the analysis of the temporary relations in the operation of electrical networks, besides the interaction between reliability of short-term and long-term (with improvements network). The process of network improvement can be understood like a response or reaction of the system to its reliability requirements. This methodology is focused on the operational planning of the following day (day ahead market), but it can be applied to other time scales, example expansion planning. The proposed method for analyzing the risk of blackout is a technical based approach that does not include external variables like human factors, information technology, and communications or procedural failures that can cause the blackout. Keep in mind that the events that cause blackouts often are a combination or the sequence of causes associated with different factors, the proposed method could be complemented by other elements that analyze the external variables to include in addition to the technical issues. The results show that the complex behavior with a power law and the Hurst index is greater than 0.5. The simulations based on our model have the same behavior as the real behavior of the system. For using the complexity theory, the SOC conditions must be established for the day ahead analyzed market. Then an inverse simulation is executed, where the endpoint of the simulation is the current situation of the system, and allows the system to evolve and meet the requisites of criticality auto-organized in a desired point of operation. After simulating the criterion of reliability used in the operation of the electrical system for cascading failures, they are validated by historical failures obtained from the electrical iv system. These results, allow the identification of lines with the biggest probability to fail, the sequence of associate events, and what simulations of actions of operation or expansion, can reduce the risk of failures of the transmission network. In the power system, the possible advantage of this methodology in the operative process is to include the risk information in decision making. Advantages expected for the electrical network are the appropriate evaluation of the risk of the network, the increase the reliability of the system (probabilistic analysis), and a progress of the planning of the risk of the day ahead (holistic analysis) and situational awareness. Future work should be focused on better modeling and evaluation of cascading outages from the steady-state and transient stability points of view. v UNIVERSITÉ PARIS-EST Resúmen Metodología de estimación del riesgo apagón en la operación de los sistemas eléctricos La industria eléctrica se puede caracterizar por varios riesgos, el regulatorio, suministro errores humanos etc. Uno de los más importantes, debido a su impacto es el relacionado con la demanda no suministrada (DNS). Para evitar la DNS: fallas en cascada o apagones, se ha realizado bastante en la confiabilidad de los equipos, seguridad de los sistemas eléctrico, gestión de activos, en las lecciones aprendidas de los grandes eventos, planes de contingencia y desarrollo de sistemas de monitoreo etc Para prevenir las fallas en cascada en los estudios de confiabilidad, se aplican los criterios determinísticos, tales como el N-1, el cual permite evitar el evento inicial de falla en la planeación y operación del sistema. En general, las herramientas de análisis para las acciones preventivas son aplicadas de forma separada para la planeación y operación del sistema en los sistemas de potencia. Después de una falla en cascada, se deben realizar esfuerzos considerables para analizar las fallas y minimizar la posibilidad de eventos similares. A pesar de todos estos esfuerzos, los apagones o grandes fallas en cascada aun ocurren, aunque los eventos son considerados raros debido a los esfuerzos de la industria. En efecto, es un reto para el análisis y la simulación, debido al gran número de posibles iteraciones y su diversidad y complejidad para obtener una buena predicción de la situación. Además aún no han sido desarrollado métodos efectivos para el entendimiento y la mitigación de las fallas en cascada, en forma holística. En este trabajo, una metodología es propuesta para estimar el riesgo del apagón usando modelos de sistemas complejos, está basado en el uso de variables que pueden ser precursoras de un evento que ocasione DNS. En otras palabras, está basado en la dependencia entre algunas variables involucradas en el riesgo apagón usando las propiedades de los sistemas complejos auto-organizados críticos (SOC). vi Una vez que las condiciones SOC son determinadas, con un modelo de flujo de carga estadístico se simula el comportamiento del sistema y el desempeño de las variables del sistema eléctrico. Los resultados de las simulaciones fueron comparados con la operación real del sistema eléctrico colombiano. El flujo de carga DC es un modelo simplificado, que representa un fenómeno complejo de una manera simple, sin embargo deja de lado algunos aspectos de los eventos de falla que pueden suceder en los apagones. La representación de las fallas en cascada y la evolución de la red en un modelo simple, permite el análisis de la relación temporal de las redes eléctricas, además la interacción entre la confiabilidad de corto y mediano plazo. El proceso de mejora de la red puede ser visto como una respuesta a los requerimientos de confiabilidad
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