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In this paper, the power system model is formulated as a finite dimensional linear system whose state-space entries depend continuously on a time varying parameter vector called the scheduling variables. This system is referred to as the linear parameter varying (LPV) system. Although the trajectory of the changing parameters such as load levels and tie line flows is not known in advance, in most situations, they can be measured in real time. The LPV technique is applied to the decentralized design of power system stabilizers (PSS) for large systems. In the approach developed, instead of considering the complete system model with all the interconnections, we develop a decentralized approach where each individual machine is considered separately with arbitrarily changing real and reactive power output in a defined range. These variables are chosen as the scheduling variables. The designed controller automatically adjusts its parameters depending on the scheduling variables to coordinate with change of operating conditions and the dynamics of the rest of the system. The resulting decentralized PSSs give good performance in a large operating range. Design procedures are presented and comparisons are made between the LPV decentralized PSSs and conventionally designed PSSs on the 50-generator IEEE test system. [ABSTRACT FROM AUTHOR]

There is a low-frequency inter area oscillation mode in middle and western 60-Hz areas of Japan. The mode is damped, i.e., stable for small disturbances, but diverges in an oscillatory manner for large disturbances. It restricts power transmission in the areas. This paper shows that the instability is caused by nonlinear interactions between a few modes. The areas are represented with West30-machine system model prepared by the lEE of Japan. Numerical simulations are executed to obtain a critical case in which generator swings last without diverging or damping. Natural oscillation modes contained in the swings, are then calculated. Two modes have strong interactions with the interarea mode, and act so as to deteriorate its damping. Last, we examine how their influence changes with load level of the system. [ABSTRACT FROM AUTHOR]

Predicting market clearing prices is an important but difficult task, and neural networks have been widely used. A single neural network, however, may misrepresent part of the input-output data mapping that could have been correctly represented by different networks. The use of a "committee machine" composed of multiple networks can in principle alleviate such a difficulty. A major challenge for using a committee machine is to properly combine predictions from multiple networks, since the performance of individual networks is input dependent due to mapping misrepresentation. This paper presents a new method in which weighting coefficients for combining network predictions are the probabilities that individual networks capture the true input-output relationship at that prediction instant. Testing of the New England market cleaning prices demonstrates that the new method performs better than individual networks, and better than committee machines using current ensemble-averaging methods. [ABSTRACT FROM AUTHOR]

The paper presents analytical and experimental results on model-based linear estimation of dynamic phasors and dynamic symmetrical components in energy processing systems. The procedure is based on the Kalman filter, and shares its features regarding the simultaneous effective suppression of measurement noise and a very good tracking ability. The procedure is illustrated experimentally with examples involving single and three-phase inductors. [ABSTRACT FROM AUTHOR]

Contingency analysis (CA) is critical in many routine power system and market analyzes to show potential problems with the system. Due to the tremendous and yet increasing amount of data computed by CA, effective visualizations are needed to present the CA results to assist the system operators and engineers to comprehend the static security status of the system in a quick and intuitive manner. The desirable functionalities of such visualizations include showing the overall system security status, showing the severity levels of the contingencies in terms of their associated limit violations, and showing the geographic connection between the violated elements and the contingent elements. The traditional EMS display of CA results is a tabe War list of elements with limit violations. This paper explores interactive three-dimensional visualizations for contingency data. We visualize vulnerability levels of power system elements and severity information of outages separately. The overall situation of the whole system is conveyed "at a glance" by the overview visualizations, while more detailed information is displayed as needed. [ABSTRACT FROM AUTHOR]