Continuous estimation of speed and torque of induction motors using the unscented Kalman filter under voltage sag

Due to sensor limitations in some applications, induction motors state estimators are widely used in industries. One of the most powerful tools available for estimation is the Kalman filter. In this paper, unscented Kalman filter (UKF) and extended Kalman filter (EKF) is used to estimate the speed and torque of an induction motor. In the UKF algorithm, three types of unscented transformation (UT): basic, general and spherical types are presented and compared. It will be shown that the spherical UKF presents good estimation performance. Speed and torque Estimation approach is applied at both steady state conditions and at the time of sudden and rapid change in the motor input voltage. It will be shown that, EKF cannot trace the motor speed at the time of a large disturbance. Finally, experimental validation is presented to show the effectiveness of UKF for continuous estimation of torque and speed of induction motorsComo se veía las limitaciones en los sensores en algunas aplicaciones, los motores asíncronos estimadores de estado ya son ampliamente utilizados en las industrias. Una de las herramientas disponibles y más potentes es el filtro de Kalman. En el presente artículo el Filtro de Kalman Unscented (UKF en siglas en inglés) y el Filtro de Kalman Extendido(EKF) se usan para estimación de la velocidad y el par motor o torque de un motor de inducción. En el algoritmo de UKF, hay 3 tipos de la transformación “unscented” que son presentados y comparados: básica, general y esférica. Se muestra en ese artículo que el UKF esférico presentará una buena estimación. En materia de la estimación de la velocidad y el par motor, que son aplicados tanto en condiciones que están en estado estacionario como en los cambios repentinos y rápidos en el voltaje de entrada del motor. Y además va a mostrar que el EKF no es capaz de rastrear la velocidad del motor en el momento cuando hay una larga perturbación. Por último, la validación experimental es presentada para mostrar la eficacia del UKF de forma continua en la estimación del par motor y la velocidad de los motores asíncronos

A Lyapunov spectrum based hybrid static and dynamic approach for contingency ranking

Abstract The goal of contingency ranking is to provide a list of possible critical situations and rank them according to the severity of their impact on a power network. The methods of contingency ranking may be divided into two major categories: static and dynamic techniques. Static approaches are fast and can be implemented in real‐time, but they present different results depending on the parameter which has been selected for contingency ranking. Dynamic methodologies are more accurate than static ones, but they are time‐consuming. This paper presents a novel combined static and dynamic method for contingency ranking which takes advantage of both techniques and shows the performance evaluation for the hybrid method using accuracy and efficiency as criteria. The proposed method uses three well‐known static indices and the Lyapunov spectrum based dynamic approach to select the worst critical lines. IEEE 39‐bus (New England grid) and IEEE 118‐bus networks are utilized to verify the proposed method. The method provides speed and accuracy. One of the prominent features of the proposed approach is its ability to rank contingencies that lead to network load flow divergence

The value of energy storage in optimal non-firm wind capacity connection to power systems

Wind is a variable and uncontrollable source of power with a low capacity factor. Using energy storage facilities with a non-firm connection strategy is the key to maximum integration of distant wind farms into a transmission-constrained power system. In this paper, we explore the application of energy storage in optimal allocation of wind capacity to a power system from distant wind sites. Energy storage decreases transmission connection requirements, smoothes the wind farm output and decreases the wind energy curtailments in a non-firm wind capacity allocation strategy. Specifically, we examine the use of compressed air energy storage (CABS) technology to supplement wind farms and downsize the transmission connection requirements. Benders decomposition approach is applied to decompose this computationally challenging and large-scale mixed-integer linear programming (MILP) into smaller problems. The simulation results show that using energy storage systems can decrease the variation of wind farms output as well as the total cost, including investment and operation costs, and increase the wind energy penetration into the power system. (C) 2013 Elsevier Ltd. All rights reserved