Contingency Analysis using Synchrophasor Measurements

Abstract -This paper presents a new algorithm, using phasor measurements, that allows real-time analysis and correction of contingencies in power systems. The focus is specifically on overloaded lines. Contingency indicative phasor limits are investigated using current magnitude and voltage angle. These limits are applied to a rotating phasor chart. An algorithm which predicts sensitivity is applied to an off-line system in order to determine the buses that need to be monitored. An online system with available phasor measurement unit (PMU) data is used to verify the phasor chart obtained using off-line data. The chart is completed for on-line PMU data, and compared with the off-line chart for further verification

Towards a Mathematical Theory of Cortical Micro-circuits

The theoretical setting of hierarchical Bayesian inference is gaining acceptance as a framework for understanding cortical computation. In this paper, we describe how Bayesian belief propagation in a spatio-temporal hierarchical model, called Hierarchical Temporal Memory (HTM), can lead to a mathematical model for cortical circuits. An HTM node is abstracted using a coincidence detector and a mixture of Markov chains. Bayesian belief propagation equations for such an HTM node define a set of functional constraints for a neuronal implementation. Anatomical data provide a contrasting set of organizational constraints. The combination of these two constraints suggests a theoretically derived interpretation for many anatomical and physiological features and predicts several others. We describe the pattern recognition capabilities of HTM networks and demonstrate the application of the derived circuits for modeling the subjective contour effect. We also discuss how the theory and the circuit can be extended to explain cortical features that are not explained by the current model and describe testable predictions that can be derived from the model