Graciela Colome - Academia.edu (original) (raw)

Papers by Graciela Colome

Research paper thumbnail of Estado del Arte y Tendencias en el Modelamiento de Carga

Revista técnica energía, Jan 26, 2022

Load modeling is a fundamental task in the design, planning, operation, control and many other st... more Load modeling is a fundamental task in the design, planning, operation, control and many other studies and applications related with the appropriate electrical systems operation. Although load modeling was widely studied in the past, a great interest has emerged in these days from researchers and industry due to different causes such as the technological change in demand, continuous networks growth, operation close to stability limits, distributed generation, great deployment of measurement technologies, just to mention some. In this context, the aim of this work is to present a literature review on load modeling prioritizing the most significant researches through the last decade. To achieve this, these authors proposed the first systematic methodology for classifying literature focused on load modeling. Based on this methodology, the results deduced include current research trends, areas of little research and future research issues. These results are thoroughly described and highlighted in the paper.

Research paper thumbnail of An Intelligent Controlled Islanding Scheme for power systems

In this paper a new Intelligent Controlled Islanding Scheme (ICIS) able to change its behavior ac... more In this paper a new Intelligent Controlled Islanding Scheme (ICIS) able to change its behavior according to the state of the system is presented. As a first step, generators are classified into coherent groups by means of a recursive clustering algorithm applied to the measurements delivered by Phasor Measurement Units (PMU). In a second, tie-lines to be opened in order to create the islands are determined by means of concepts based on graph theory, shortest electrical distance and active power imbalance. A reduced frequency response model is employed to determine the power imbalance limits on each island. Finally, a DC power flow based procedure is used to assess and control possible overloads after islanding. The 39 bus - New England System is used to test proposed islanding scheme showing its capability to avoid power systems collapse.

Research paper thumbnail of Fault-Induced Delayed Voltage Recovery Assessment based on Dynamic Voltage Indices

2018 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D-LA)

This paper presents a new methodology for assessing fault-induced delayed voltage recovery (FIDVR... more This paper presents a new methodology for assessing fault-induced delayed voltage recovery (FIDVR) problem sin power systems based on the calculation of dynamic voltage indices. The indices allow obtaining information on the power system post-contingency dynamic behavior. As part of the methodology, the calculation of instantaneous indices (voltage index -VI), indices per time window (dynamic voltage index DVI), per bus (DVIb)(DVI_{b})(DVIb) and of the whole system (wide-area dynamic voltage index - WADVI) is proposed. These indices are compared with thresholds to determine buses with delayed voltage recovery problems. Case studies were simulated in the New England 39 bus test system in which the proposed methodology was implemented. The methodology is used to identify voltage recovery problems from a low computational time procedure, with which indices are obtained that allow determining the location and magnitude of delayed voltage recovery events.

Research paper thumbnail of Predicción de la Estabilidad Transitoria de Sistemas Eléctricos utilizando Aprendizaje Automático

2022 IEEE Biennial Congress of Argentina (ARGENCON)

Research paper thumbnail of Evaluación de la Estabilidad de Corto Plazo y Discriminación de Inestabilidades Transitoria y de Tensión

2022 IEEE Biennial Congress of Argentina (ARGENCON)

Research paper thumbnail of Estimación Paramétrica del Modelo de Carga ZIP basada en Técnicas de Optimización y en Mediciones de PMU

2022 IEEE Biennial Congress of Argentina (ARGENCON)

Research paper thumbnail of Monitoring of power system dynamics under incomplete PMU observability condition

IET Generation, Transmission & Distribution, 2020

Research paper thumbnail of Estado del Arte y Tendencias en el Modelamiento de Carga

Revista Técnica "energía", 2022

El modelamiento de la carga es fundamental en el diseño, planificación, operación, control y much... more El modelamiento de la carga es fundamental en el diseño, planificación, operación, control y muchos otros estudios y aplicaciones relacionados al correcto funcionamiento de los sistemas eléctricos. Aunque el modelamiento de carga ha sido ampliamente estudiado en el pasado, hoy en día ha resurgido un gran interés por parte de los investigadores y la industria debido: al cambio tecnológico de la demanda, al crecimiento continuo de las redes, a la operación cerca de los límites de estabilidad, a la generación distribuida, al gran despliegue de tecnologías de medición, entre muchos otros. En este contexto, el objetivo de este trabajo es presentar una revisión bibliográfica sobre modelamiento de carga, en la cual se prioriza las investigaciones de la última década. Para lograr el objetivo precitado primero se propone, a conocimiento de los autores, la primera metodología sistemática de clasificación bibliográfica enfocada específicamente al modelamiento de carga. En base a esta metodolog...

Research paper thumbnail of Chaos in Power Systems: Towards Short-term Voltage Stability Analysis

2018 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D-LA), 2018

Power systems are highly non-linear and they sometimes may exhibit a chaotic dynamic behavior tha... more Power systems are highly non-linear and they sometimes may exhibit a chaotic dynamic behavior that leads to instability and subsequent voltage collapse. That is why the analysis of nonlinear dynamic systems using computational techniques based on chaos theory gives the possibility of detecting these instability phenomena. This paper presents a new approach for analyzing the short-term voltage stability based on the concept of chaos, the representation of dynamics in an embedding dimension, the computing of Lyapunov exponents and a multidimensional analysis for determining embedding parameters using space-time techniques. The results of the application of the proposed techniques for assessing short-term voltage stability in the New England 39-bus test system are presented, which demonstrate that the proposed approach is suitable for determining stability/instability state to post- contingency voltage time series with complex dynamic behavior.

Research paper thumbnail of Real-time State Estimation in a System Partially Observed by PMUs: A Coherency Data Mining Based Approach

2019 9th International Conference on Power and Energy Systems (ICPES), 2019

This paper presents a real-time state estimator (SE) in a system that is partially observed by ph... more This paper presents a real-time state estimator (SE) in a system that is partially observed by phasor measurement units (PMUs). The algorithm involves two stages. The first stage runs at SCADA speed and is based on a static state estimator (SSE) with measurements from remote terminal units (RTUs) and PMUs. The second stage runs at PMU speed and is based on a linear state estimator (LSE) that uses only phasor measurements. In order to compensate the lack of measurements in stage two and ensure the observability of the entire system a novel methodology that generates voltage dynamic pseudo-measurements is proposed. This approach is based on the concept of coherency of an electric power system (EPS) and defines, firstly, the PMU location that allows observing all the coherent areas and, secondly, a classifier that forecasts coherency in real time with the aim of calculating dynamic pseudo-measurements. The state estimation algorithm together with the proposed methodology have been evaluated on the New England system under several operating scenarios. Results show the ability of the methodology for generating dynamic pseudo-measurement to operate with accuracy in real time conditions. As a result, the SE is able to accurately estimate the state in real time in the presence of both slow and fast transient phenomena.

Research paper thumbnail of Real-time transient stability assessment of electric power systems using predictive-SIME based on machine learning

2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America), 2017

This paper presents a novel methodology based on machine learning for assessing the power system ... more This paper presents a novel methodology based on machine learning for assessing the power system transient stability (TS) in real-time using synchronized phasor measurements as input in order to predict the power system TS status related to the single machine equivalent (SIME) results. Based on the probabilistic models of input parameters, such as load variation and the occurrence of contingencies, Monte Carlo-type simulation is performed off-line to iteratively evaluate the system TS responses using the SIME methodology. Afterwards, the database obtained from the off-line simulations is employed for structuring and training an intelligent SIME's TS margin classifier based on support vector machines (SVM) to be used for real-time transient stability assessment (TSA). Besides, the SVM is optimally tuned by using the swarm variant of the mean-variance mapping optimization MVMOS. Several tests are then performed on the New England benchmark power system. Results demonstrate the feasibility and effectiveness that could be achieved in estimating the transient stability status related to the SIME's TS margins, which will also be of great value for defining suitable emergency control actions in real time.

Research paper thumbnail of Assessment of Dynamic Voltage Support Control Schemes for Photovoltaic Generators Connected to Power Systems

2019 IEEE 4th Colombian Conference on Automatic Control (CCAC), 2019

Nowadays, the trend is that modern power systems operate with high penetration of photovoltaic ge... more Nowadays, the trend is that modern power systems operate with high penetration of photovoltaic generation, which must provide adequate voltage support in contingency situations. This paper presents an analysis and assessment of the effect on the dynamic performance of the voltage magnitude of two voltage control schemes of photovoltaic generators connected to power systems. Fault-ride through (FRT)-based dynamic voltage support schemes with and without injection of reactive power are evaluated. Study cases in the IEEE 14-bus test system are presented in which the performance of the contingency voltage response is assessed from dynamic voltage indices. Results showed that with a control scheme for photovoltaic systems which injects reactive power into the power system in the transient stage it is possible to avoid problems of fault-induced delayed voltage recovery (FIDVR) and fast voltage collapses.

Research paper thumbnail of Dynamic state estimation of an electric power system

2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America), 2017

An estimator of the dynamic state of an electric power system (EPS) is presented in this paper. T... more An estimator of the dynamic state of an electric power system (EPS) is presented in this paper. The developed algorithm involves two stages which are based on the weighted least square (WLS) technique. The first stage uses conventional measurements (delivered by RTU — SCADA meters) and synchronized phasor measurements (delivered by PMU meters) in order to estimate the state of the system forming an iterative hybrid state estimator (HSE). The second stage uses synchronized phasor measurements and voltage pseudo-measurements obtained from the estimated state on the first stage and the dynamic information delivered from synchronized phasor measurements. This stage runs at PMU speed. The method has been tested on the New England system. Results prove the estimator can accurately estimate the state of a system on dynamic condition in the presence of both slow and fast transient phenomena.

Research paper thumbnail of Distributed Parametric Identification of Low Frequency Oscillatory Modes in Multiple PMU

2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA), 2020

This paper analyses performance in the estimation of low frequency oscillatory modes utilizing Pr... more This paper analyses performance in the estimation of low frequency oscillatory modes utilizing Prony's method of parametric identification applied to multiple signals (multiProny) in distributed form. The analyzed methodology applies the multiProny method by area and integrates local modal estimates in a consensus optimization process that determines a global solution for the entire system. In each area, multiple measurements are processed corresponding to ringdown data, recorded in case of contingencies by PMUs (Phasor Measurement Units) of a WAMS (Wide Area Monitoring Systems). The distributed method of optimization and consensus used here is based on the distributed ADMM (Alternating Direction Method of Multipliers) algorithm. The performance of the distributed Prony method is evaluated by processing known analytical signals and synchrophasorial voltage measurements recorded at low voltage by the MedFasee BT Argentina Project: Observatory of the Dynamics of the Sistema Argentino de Interconexión (SADI). The results show that more precise oscillatory modes are obtained with the distributed multiProny method than with the simple Prony method when processing a single signal or a set of signals in a centralized way.

Research paper thumbnail of Determinación de los modos oscilatorios en el SADI a partir del análisis de las mediciones de las PMU de datos tipo ambiente en Baja Tensión

Revista Técnica "energía", 2021

Este trabajo presenta el análisis de correlación canónica (CCA) y de Yule Walker (YW) de las medi... more Este trabajo presenta el análisis de correlación canónica (CCA) y de Yule Walker (YW) de las mediciones de las PMU (Phasor Measurement Unit) registradas en el marco del Proyecto MedFasee BT Argentina, que observa la dinámica del Sistema Argentino de Interconexión (SADI). Los métodos de CCA y YW se utilizan para determinar los modos oscilatorios de baja frecuencia con bajo amortiguamiento presentes en las señales de tensión y de frecuencia. Estos modos se caracterizan por su frecuencia, amortiguamiento y pseudoenergía. Los métodos CCA y YW se aplican a las mediciones de datos de tipo ambiente de las PMU. Este estudio además de permitir la detección de los modos con bajo amortiguamiento, permitido determinar diferentes parámetros de los métodos como señal a analizar, lo cual es un requisito para el preprocesamiento, así como la definición de la ventana de análisis, periodo de muestreo y orden del sistema.

Research paper thumbnail of Data Analytics of PMU Measurement Features for Real-time Short-term Voltage Stability Prediction

2019 FISE-IEEE/CIGRE Conference - Living the energy Transition (FISE/CIGRE), 2019

Stability problems have been taking place in recent years in power systems due to different facto... more Stability problems have been taking place in recent years in power systems due to different factors without the possibility of network operators to anticipate its occurrence and impacting the continuity of the electric power service. However, the current paradigm is different as a result of new technologies that allow monitoring the dynamics based on PMU equipment and the prediction of problems in very short times with data mining. This paper presents a novel method for predicting short-term voltage stability problems in real-time through data mining and analytics techniques. These techniques are used in the proposed method to i) select the measurement features that are required to predict the post-contingency operation status by solving a multiobjective optimization problem, ii) perform pattern extraction based on symbols and iii) train an intelligent classifier to predict the state of post-contingency operation. Case studies are presented in the New England 39-bus test system in which it was obtained that the installation of only 5 PMU equipment is required to predict the post-contingency operation status with an error less than 4% and using a post-disturbance data window equal to 180 ms, this time is enough to activate control actions that allow mitigating the problem.

Research paper thumbnail of Identificación de Generadores Coherentes en Tiempo Real utilizando Mediciones Sincrofasoriales (PMU)

Revista Técnica "Energía", 2012

El presente trabajo aborda el problema de la identificación de generadores coherentes utilizando ... more El presente trabajo aborda el problema de la identificación de generadores coherentes utilizando mediciones sincrofasoriales (PMU). Se presenta el problema de evaluación de coherencia entre generadores y se describen las principales metodologías utilizadas para su estudio. Debido a que los grupos de generadores coherentes varían en el tiempo en función del estado de operación del sistema, se propone una nueva metodología para su identificación en tiempo real. En base a casos de estudio se evalúa el desempeño de la metodología propuesta frente a otras técnicas de la bibliografía y sobre este análisis se determina que su capacidad de adaptación a los datos la convierten en una opción atractiva para su aplicación en ambientes en tiempo real, así como en la caracterización del sistema basada en simulaciones.

Research paper thumbnail of Real-time multi-state classification of short-term voltage stability based on multivariate time series machine learning

International Journal of Electrical Power & Energy Systems, 2019

The analysis of the significant amount of data collected by PMU devices in wide-area monitoring, ... more The analysis of the significant amount of data collected by PMU devices in wide-area monitoring, protection and control (WAMPAC) applications has been a great challenge for assessing power system fast phenomena. This paper presents a novel methodology for real-time assessment of short-term voltage stability (STVS) under large disturbances with an approach based on data mining and machine learning. This methodology classifies off-line the power system stability in multiple operating states through the calculation of the maximal Lyapunov exponent and dynamic voltage indices. This allows identifying not only fast voltage collapses (FVC) but also faultinduced delayed voltage recovery (FIDVR) events. The multivariate time series data of the power system dynamic response are processed and transformed with a symbolic representation technique. This together with the operating state classification are used to train an intelligent machine based on Random Forest proposed for applying in real time to classify the post-disturbance operating state. This methodology is tested in the New England 39-bus system. The performance of the methodology to classify the STVS in real time was verified, obtaining a classification error less than 2% using a post-contingency data window of 0.58 s and less than onethird of all the bus voltage measurements. Results show the ability of the methodology to predict voltage stability problems, having enough time to carry out automatic control actions to prevent or mitigate problems.

Research paper thumbnail of State estimation of power system based on SCADA and PMU measurements

2016 IEEE ANDESCON, 2016

A two stage state estimator (SE) of an Electric Power System (EPS) is presented in this paper. It... more A two stage state estimator (SE) of an Electric Power System (EPS) is presented in this paper. It combines SCADA (Supervisory Control and Data Acquisition) and PMU (Phasor Measurement Unit) measurements. This feature gives it more accuracy on estimation over conventional algorithms based on SCADA measurements and also the possibility to obtain dynamic information of the system behavior. In the first stage a nonlinear HSE (Hybrid State Estimator) is executed at every updating moment of SCADA measurements. The state is defined as the vector of complex bus voltages and it is estimated by WLS (Weighted Least Square) technique. The measurement vector includes SCADA measurements and PMU voltage measurements. In the second stage a nonlinear SE is executed at every updating moment of PMU measurements. The state is defined as the vector of complex branch currents and it is estimated by WLS technique. The measurement vector of this case includes only PMU voltage and current measurements. The performance of the proposed method is analyzed on a 17 bus system (IEEE 14 bus system modified). Results show the ability of the algorithm to track the voltage dynamic accurately.

Research paper thumbnail of An Intelligent Controlled Islanding Scheme for power systems

2015 18th International Conference on Intelligent System Application to Power Systems (ISAP), 2015

In this paper a new Intelligent Controlled Islanding Scheme (ICIS) able to change its behavior ac... more In this paper a new Intelligent Controlled Islanding Scheme (ICIS) able to change its behavior according to the state of the system is presented. As a first step, generators are classified into coherent groups by means of a recursive clustering algorithm applied to the measurements delivered by Phasor Measurement Units (PMU). In a second, tie-lines to be opened in order to create the islands are determined by means of concepts based on graph theory, shortest electrical distance and active power imbalance. A reduced frequency response model is employed to determine the power imbalance limits on each island. Finally, a DC power flow based procedure is used to assess and control possible overloads after islanding. The 39 bus - New England System is used to test proposed islanding scheme showing its capability to avoid power systems collapse.

Research paper thumbnail of Estado del Arte y Tendencias en el Modelamiento de Carga

Revista técnica energía, Jan 26, 2022

Load modeling is a fundamental task in the design, planning, operation, control and many other st... more Load modeling is a fundamental task in the design, planning, operation, control and many other studies and applications related with the appropriate electrical systems operation. Although load modeling was widely studied in the past, a great interest has emerged in these days from researchers and industry due to different causes such as the technological change in demand, continuous networks growth, operation close to stability limits, distributed generation, great deployment of measurement technologies, just to mention some. In this context, the aim of this work is to present a literature review on load modeling prioritizing the most significant researches through the last decade. To achieve this, these authors proposed the first systematic methodology for classifying literature focused on load modeling. Based on this methodology, the results deduced include current research trends, areas of little research and future research issues. These results are thoroughly described and highlighted in the paper.

Research paper thumbnail of An Intelligent Controlled Islanding Scheme for power systems

In this paper a new Intelligent Controlled Islanding Scheme (ICIS) able to change its behavior ac... more In this paper a new Intelligent Controlled Islanding Scheme (ICIS) able to change its behavior according to the state of the system is presented. As a first step, generators are classified into coherent groups by means of a recursive clustering algorithm applied to the measurements delivered by Phasor Measurement Units (PMU). In a second, tie-lines to be opened in order to create the islands are determined by means of concepts based on graph theory, shortest electrical distance and active power imbalance. A reduced frequency response model is employed to determine the power imbalance limits on each island. Finally, a DC power flow based procedure is used to assess and control possible overloads after islanding. The 39 bus - New England System is used to test proposed islanding scheme showing its capability to avoid power systems collapse.

Research paper thumbnail of Fault-Induced Delayed Voltage Recovery Assessment based on Dynamic Voltage Indices

2018 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D-LA)

This paper presents a new methodology for assessing fault-induced delayed voltage recovery (FIDVR... more This paper presents a new methodology for assessing fault-induced delayed voltage recovery (FIDVR) problem sin power systems based on the calculation of dynamic voltage indices. The indices allow obtaining information on the power system post-contingency dynamic behavior. As part of the methodology, the calculation of instantaneous indices (voltage index -VI), indices per time window (dynamic voltage index DVI), per bus (DVIb)(DVI_{b})(DVIb) and of the whole system (wide-area dynamic voltage index - WADVI) is proposed. These indices are compared with thresholds to determine buses with delayed voltage recovery problems. Case studies were simulated in the New England 39 bus test system in which the proposed methodology was implemented. The methodology is used to identify voltage recovery problems from a low computational time procedure, with which indices are obtained that allow determining the location and magnitude of delayed voltage recovery events.

Research paper thumbnail of Predicción de la Estabilidad Transitoria de Sistemas Eléctricos utilizando Aprendizaje Automático

2022 IEEE Biennial Congress of Argentina (ARGENCON)

Research paper thumbnail of Evaluación de la Estabilidad de Corto Plazo y Discriminación de Inestabilidades Transitoria y de Tensión

2022 IEEE Biennial Congress of Argentina (ARGENCON)

Research paper thumbnail of Estimación Paramétrica del Modelo de Carga ZIP basada en Técnicas de Optimización y en Mediciones de PMU

2022 IEEE Biennial Congress of Argentina (ARGENCON)

Research paper thumbnail of Monitoring of power system dynamics under incomplete PMU observability condition

IET Generation, Transmission & Distribution, 2020

Research paper thumbnail of Estado del Arte y Tendencias en el Modelamiento de Carga

Revista Técnica "energía", 2022

El modelamiento de la carga es fundamental en el diseño, planificación, operación, control y much... more El modelamiento de la carga es fundamental en el diseño, planificación, operación, control y muchos otros estudios y aplicaciones relacionados al correcto funcionamiento de los sistemas eléctricos. Aunque el modelamiento de carga ha sido ampliamente estudiado en el pasado, hoy en día ha resurgido un gran interés por parte de los investigadores y la industria debido: al cambio tecnológico de la demanda, al crecimiento continuo de las redes, a la operación cerca de los límites de estabilidad, a la generación distribuida, al gran despliegue de tecnologías de medición, entre muchos otros. En este contexto, el objetivo de este trabajo es presentar una revisión bibliográfica sobre modelamiento de carga, en la cual se prioriza las investigaciones de la última década. Para lograr el objetivo precitado primero se propone, a conocimiento de los autores, la primera metodología sistemática de clasificación bibliográfica enfocada específicamente al modelamiento de carga. En base a esta metodolog...

Research paper thumbnail of Chaos in Power Systems: Towards Short-term Voltage Stability Analysis

2018 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D-LA), 2018

Power systems are highly non-linear and they sometimes may exhibit a chaotic dynamic behavior tha... more Power systems are highly non-linear and they sometimes may exhibit a chaotic dynamic behavior that leads to instability and subsequent voltage collapse. That is why the analysis of nonlinear dynamic systems using computational techniques based on chaos theory gives the possibility of detecting these instability phenomena. This paper presents a new approach for analyzing the short-term voltage stability based on the concept of chaos, the representation of dynamics in an embedding dimension, the computing of Lyapunov exponents and a multidimensional analysis for determining embedding parameters using space-time techniques. The results of the application of the proposed techniques for assessing short-term voltage stability in the New England 39-bus test system are presented, which demonstrate that the proposed approach is suitable for determining stability/instability state to post- contingency voltage time series with complex dynamic behavior.

Research paper thumbnail of Real-time State Estimation in a System Partially Observed by PMUs: A Coherency Data Mining Based Approach

2019 9th International Conference on Power and Energy Systems (ICPES), 2019

This paper presents a real-time state estimator (SE) in a system that is partially observed by ph... more This paper presents a real-time state estimator (SE) in a system that is partially observed by phasor measurement units (PMUs). The algorithm involves two stages. The first stage runs at SCADA speed and is based on a static state estimator (SSE) with measurements from remote terminal units (RTUs) and PMUs. The second stage runs at PMU speed and is based on a linear state estimator (LSE) that uses only phasor measurements. In order to compensate the lack of measurements in stage two and ensure the observability of the entire system a novel methodology that generates voltage dynamic pseudo-measurements is proposed. This approach is based on the concept of coherency of an electric power system (EPS) and defines, firstly, the PMU location that allows observing all the coherent areas and, secondly, a classifier that forecasts coherency in real time with the aim of calculating dynamic pseudo-measurements. The state estimation algorithm together with the proposed methodology have been evaluated on the New England system under several operating scenarios. Results show the ability of the methodology for generating dynamic pseudo-measurement to operate with accuracy in real time conditions. As a result, the SE is able to accurately estimate the state in real time in the presence of both slow and fast transient phenomena.

Research paper thumbnail of Real-time transient stability assessment of electric power systems using predictive-SIME based on machine learning

2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America), 2017

This paper presents a novel methodology based on machine learning for assessing the power system ... more This paper presents a novel methodology based on machine learning for assessing the power system transient stability (TS) in real-time using synchronized phasor measurements as input in order to predict the power system TS status related to the single machine equivalent (SIME) results. Based on the probabilistic models of input parameters, such as load variation and the occurrence of contingencies, Monte Carlo-type simulation is performed off-line to iteratively evaluate the system TS responses using the SIME methodology. Afterwards, the database obtained from the off-line simulations is employed for structuring and training an intelligent SIME's TS margin classifier based on support vector machines (SVM) to be used for real-time transient stability assessment (TSA). Besides, the SVM is optimally tuned by using the swarm variant of the mean-variance mapping optimization MVMOS. Several tests are then performed on the New England benchmark power system. Results demonstrate the feasibility and effectiveness that could be achieved in estimating the transient stability status related to the SIME's TS margins, which will also be of great value for defining suitable emergency control actions in real time.

Research paper thumbnail of Assessment of Dynamic Voltage Support Control Schemes for Photovoltaic Generators Connected to Power Systems

2019 IEEE 4th Colombian Conference on Automatic Control (CCAC), 2019

Nowadays, the trend is that modern power systems operate with high penetration of photovoltaic ge... more Nowadays, the trend is that modern power systems operate with high penetration of photovoltaic generation, which must provide adequate voltage support in contingency situations. This paper presents an analysis and assessment of the effect on the dynamic performance of the voltage magnitude of two voltage control schemes of photovoltaic generators connected to power systems. Fault-ride through (FRT)-based dynamic voltage support schemes with and without injection of reactive power are evaluated. Study cases in the IEEE 14-bus test system are presented in which the performance of the contingency voltage response is assessed from dynamic voltage indices. Results showed that with a control scheme for photovoltaic systems which injects reactive power into the power system in the transient stage it is possible to avoid problems of fault-induced delayed voltage recovery (FIDVR) and fast voltage collapses.

Research paper thumbnail of Dynamic state estimation of an electric power system

2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America), 2017

An estimator of the dynamic state of an electric power system (EPS) is presented in this paper. T... more An estimator of the dynamic state of an electric power system (EPS) is presented in this paper. The developed algorithm involves two stages which are based on the weighted least square (WLS) technique. The first stage uses conventional measurements (delivered by RTU — SCADA meters) and synchronized phasor measurements (delivered by PMU meters) in order to estimate the state of the system forming an iterative hybrid state estimator (HSE). The second stage uses synchronized phasor measurements and voltage pseudo-measurements obtained from the estimated state on the first stage and the dynamic information delivered from synchronized phasor measurements. This stage runs at PMU speed. The method has been tested on the New England system. Results prove the estimator can accurately estimate the state of a system on dynamic condition in the presence of both slow and fast transient phenomena.

Research paper thumbnail of Distributed Parametric Identification of Low Frequency Oscillatory Modes in Multiple PMU

2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA), 2020

This paper analyses performance in the estimation of low frequency oscillatory modes utilizing Pr... more This paper analyses performance in the estimation of low frequency oscillatory modes utilizing Prony's method of parametric identification applied to multiple signals (multiProny) in distributed form. The analyzed methodology applies the multiProny method by area and integrates local modal estimates in a consensus optimization process that determines a global solution for the entire system. In each area, multiple measurements are processed corresponding to ringdown data, recorded in case of contingencies by PMUs (Phasor Measurement Units) of a WAMS (Wide Area Monitoring Systems). The distributed method of optimization and consensus used here is based on the distributed ADMM (Alternating Direction Method of Multipliers) algorithm. The performance of the distributed Prony method is evaluated by processing known analytical signals and synchrophasorial voltage measurements recorded at low voltage by the MedFasee BT Argentina Project: Observatory of the Dynamics of the Sistema Argentino de Interconexión (SADI). The results show that more precise oscillatory modes are obtained with the distributed multiProny method than with the simple Prony method when processing a single signal or a set of signals in a centralized way.

Research paper thumbnail of Determinación de los modos oscilatorios en el SADI a partir del análisis de las mediciones de las PMU de datos tipo ambiente en Baja Tensión

Revista Técnica "energía", 2021

Este trabajo presenta el análisis de correlación canónica (CCA) y de Yule Walker (YW) de las medi... more Este trabajo presenta el análisis de correlación canónica (CCA) y de Yule Walker (YW) de las mediciones de las PMU (Phasor Measurement Unit) registradas en el marco del Proyecto MedFasee BT Argentina, que observa la dinámica del Sistema Argentino de Interconexión (SADI). Los métodos de CCA y YW se utilizan para determinar los modos oscilatorios de baja frecuencia con bajo amortiguamiento presentes en las señales de tensión y de frecuencia. Estos modos se caracterizan por su frecuencia, amortiguamiento y pseudoenergía. Los métodos CCA y YW se aplican a las mediciones de datos de tipo ambiente de las PMU. Este estudio además de permitir la detección de los modos con bajo amortiguamiento, permitido determinar diferentes parámetros de los métodos como señal a analizar, lo cual es un requisito para el preprocesamiento, así como la definición de la ventana de análisis, periodo de muestreo y orden del sistema.

Research paper thumbnail of Data Analytics of PMU Measurement Features for Real-time Short-term Voltage Stability Prediction

2019 FISE-IEEE/CIGRE Conference - Living the energy Transition (FISE/CIGRE), 2019

Stability problems have been taking place in recent years in power systems due to different facto... more Stability problems have been taking place in recent years in power systems due to different factors without the possibility of network operators to anticipate its occurrence and impacting the continuity of the electric power service. However, the current paradigm is different as a result of new technologies that allow monitoring the dynamics based on PMU equipment and the prediction of problems in very short times with data mining. This paper presents a novel method for predicting short-term voltage stability problems in real-time through data mining and analytics techniques. These techniques are used in the proposed method to i) select the measurement features that are required to predict the post-contingency operation status by solving a multiobjective optimization problem, ii) perform pattern extraction based on symbols and iii) train an intelligent classifier to predict the state of post-contingency operation. Case studies are presented in the New England 39-bus test system in which it was obtained that the installation of only 5 PMU equipment is required to predict the post-contingency operation status with an error less than 4% and using a post-disturbance data window equal to 180 ms, this time is enough to activate control actions that allow mitigating the problem.

Research paper thumbnail of Identificación de Generadores Coherentes en Tiempo Real utilizando Mediciones Sincrofasoriales (PMU)

Revista Técnica "Energía", 2012

El presente trabajo aborda el problema de la identificación de generadores coherentes utilizando ... more El presente trabajo aborda el problema de la identificación de generadores coherentes utilizando mediciones sincrofasoriales (PMU). Se presenta el problema de evaluación de coherencia entre generadores y se describen las principales metodologías utilizadas para su estudio. Debido a que los grupos de generadores coherentes varían en el tiempo en función del estado de operación del sistema, se propone una nueva metodología para su identificación en tiempo real. En base a casos de estudio se evalúa el desempeño de la metodología propuesta frente a otras técnicas de la bibliografía y sobre este análisis se determina que su capacidad de adaptación a los datos la convierten en una opción atractiva para su aplicación en ambientes en tiempo real, así como en la caracterización del sistema basada en simulaciones.

Research paper thumbnail of Real-time multi-state classification of short-term voltage stability based on multivariate time series machine learning

International Journal of Electrical Power & Energy Systems, 2019

The analysis of the significant amount of data collected by PMU devices in wide-area monitoring, ... more The analysis of the significant amount of data collected by PMU devices in wide-area monitoring, protection and control (WAMPAC) applications has been a great challenge for assessing power system fast phenomena. This paper presents a novel methodology for real-time assessment of short-term voltage stability (STVS) under large disturbances with an approach based on data mining and machine learning. This methodology classifies off-line the power system stability in multiple operating states through the calculation of the maximal Lyapunov exponent and dynamic voltage indices. This allows identifying not only fast voltage collapses (FVC) but also faultinduced delayed voltage recovery (FIDVR) events. The multivariate time series data of the power system dynamic response are processed and transformed with a symbolic representation technique. This together with the operating state classification are used to train an intelligent machine based on Random Forest proposed for applying in real time to classify the post-disturbance operating state. This methodology is tested in the New England 39-bus system. The performance of the methodology to classify the STVS in real time was verified, obtaining a classification error less than 2% using a post-contingency data window of 0.58 s and less than onethird of all the bus voltage measurements. Results show the ability of the methodology to predict voltage stability problems, having enough time to carry out automatic control actions to prevent or mitigate problems.

Research paper thumbnail of State estimation of power system based on SCADA and PMU measurements

2016 IEEE ANDESCON, 2016

A two stage state estimator (SE) of an Electric Power System (EPS) is presented in this paper. It... more A two stage state estimator (SE) of an Electric Power System (EPS) is presented in this paper. It combines SCADA (Supervisory Control and Data Acquisition) and PMU (Phasor Measurement Unit) measurements. This feature gives it more accuracy on estimation over conventional algorithms based on SCADA measurements and also the possibility to obtain dynamic information of the system behavior. In the first stage a nonlinear HSE (Hybrid State Estimator) is executed at every updating moment of SCADA measurements. The state is defined as the vector of complex bus voltages and it is estimated by WLS (Weighted Least Square) technique. The measurement vector includes SCADA measurements and PMU voltage measurements. In the second stage a nonlinear SE is executed at every updating moment of PMU measurements. The state is defined as the vector of complex branch currents and it is estimated by WLS technique. The measurement vector of this case includes only PMU voltage and current measurements. The performance of the proposed method is analyzed on a 17 bus system (IEEE 14 bus system modified). Results show the ability of the algorithm to track the voltage dynamic accurately.

Research paper thumbnail of An Intelligent Controlled Islanding Scheme for power systems

2015 18th International Conference on Intelligent System Application to Power Systems (ISAP), 2015

In this paper a new Intelligent Controlled Islanding Scheme (ICIS) able to change its behavior ac... more In this paper a new Intelligent Controlled Islanding Scheme (ICIS) able to change its behavior according to the state of the system is presented. As a first step, generators are classified into coherent groups by means of a recursive clustering algorithm applied to the measurements delivered by Phasor Measurement Units (PMU). In a second, tie-lines to be opened in order to create the islands are determined by means of concepts based on graph theory, shortest electrical distance and active power imbalance. A reduced frequency response model is employed to determine the power imbalance limits on each island. Finally, a DC power flow based procedure is used to assess and control possible overloads after islanding. The 39 bus - New England System is used to test proposed islanding scheme showing its capability to avoid power systems collapse.