A power system is never in a steady state due to continuous load variations, disturbances, maneuvers, and the operation of protection systems. A generation deficit causes a frequency drop in the system that must be controlled. If this frequency deviation is not properly managed, it can result in the loss of synchronism between generators and, eventually, lead to a partial or even total system collapse. This article presents a load shedding scheme applied to the IEEE 39-bus New England system. The scheme considers an N-1 contingency space to evaluate the dynamic frequency response, aiming to determine the appropriate settings for low-frequency relays activated by the rate of change of frequency (ROCOF).

Real-time voltage stability assessment, via conventional methods, is a difficult task due to the required large amount of information, high execution times and computational cost. Based on these limitations, this technical work proposes a method for the estimation of the voltage stability margin through the application of artificial intelligence algorithms. For this purpose, several operation scenarios are first generated via Monte Carlo simulations, considering the load variability and the n-1 security criterion. Afterwards, the voltage stability margin of PV curves is determined for each scenario to obtain a database. This information allows structuring a data matrix for training an artificial neural network and a support vector machine, in its regression version, to predict the voltage stability margin, capable of being used in real time. The performance of the prediction tools is evaluated through the mean square error and the coefficient of determination. The proposed methodology is applied to the IEEE 14 bus test system, showing so promising results.

Este documento presenta una metodología para el diseño de un Esquema de Alivio de Carga (EAC) para sistemas eléctricos que sirve a facilidades de extracción de petrolero. El campo petrolero, a lo largo de su operación, ha experimentado problemas en su sistema de generación eléctrica, lo cual ha ocasionado colapsos totales por baja frecuencia. El sistema eléctrico del campo es modelado en software de simulación ETAP, incluyendo la dinámica de los generadores y sus sistemas de control (reguladores automáticos de voltaje y reguladores de velocidad) considerando valores típicos y validando los modelos en base a mediciones obtenidas del sistema SCADA. A través de simulaciones en el dominio del tiempo, se obtiene la evolución de la frecuencia ante la perdida de generación para varios escenarios operativos; estos escenarios son clasificados en base a la tasa de cambio de la frecuencia (ROCOF). Se genera una lista de prioridad cargas para su desconexión. Finalmente, se proponen un EAC adaptativo y EAC de frecuencia fija y ROCOF, cuyo desempeño es comparado a través de simulaciones dinámicas.

An Electric Power System (EPS) is a dynamic system that, due to continuous variations in the load, the presence of disturbances, switching operations, and/or the operation of the protection system, is never in a steady state. A deficit in generation causes a drop in the system’s frequency that, if not controlled, could result in the loss of synchronism between generators or areas and, in the worst-case scenario, a total or partial system collapse. This article presents a methodology to identify a subset of representative events that generalizes the N-1 generation contingency space; this subset can later be applied in the development of Under-Frequency Load-Shedding (UFLS) schemes based on the Rate of Change of Frequency (ROCOF).

In this paper a new strategy for controlled power system islanding based on PMU measurements is presented. The scheme is meant to be used in a real-time fashion. First, the groups of coherent generators are determined by means of a recursive clustering algorithm applied to the measurements obtained by the PMUs. In the second step, the closest distance and imbalance determination are the main factors taking into consideration to define the islands to be created. A comparison of performance between the proposed versus the traditional designed controlled islanding scheme is presented, and the main conclusions are highlighted.

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.