Federated approach for the distributed simulation of a network, is an alternative method that aims to combine existing simulation models and software together using a Run Time Infrastructure (RTI), rather than building the whole simulation from scratch. In this study, an approach that significantly reduces the inter-federate communication load in federated simulation of communication networks is proposed. Rather than communicating packet-level information among federates, characteristics of packet flows in individual federates are dynamically identified and communicated. Flow characterization is done with the Gaussian Mixtures Algorithm (GMA) using a Self Organizing Mixture Network (SOMN) technique. In simulations of a network partitioned into eight federates in space parallel manner, it is shown that significant speedups are achieved with the proposed approach without unduly compromising accuracy.

A power system is typically one small part of a larger interconnected network and is affected to a varying degree, by contingencies external to itself as well as by the reaction of external network to its own contingencies. Thus, the accuracy of a complete interconnected network model would affect the results of many transmission level analyses. In an interconnected power system, the real-time network security and power transfer capability analyses require a ¡§real-time¡¨ complete network base case solution. In order to accurately assess the system security and the inter-area transfer capability, it is highly desirable that any available information from all areas is used. With the advent of communications among operations control center computers, real-time telemetered data can be exchanged for complete network modeling. Measurement time skew should be considered in the complete network modeling when combining large area data received via a data communication network. In this dissertation, several suggestions aiming toward the improvement of complete network modeling are offered. A discrete event simulation technique is used to assess the performance of a data exchange scheme that uses Internet interface to the SCADA system. Performance modeling of data exchange on the Internet is established and a quantitative analysis of the data exchange delay is presented. With the prediction mechanisms, the effect of time skew of interchanged data among utilities can be minimized, and consequently, state estimation (SE) could provide the accurate real-time complete network models of the interconnected network for security and available transfer capability analyses. In order to accommodate the effects of randomly varying arrival of measurement data and setup a base case for more accurate analyses of network security and transfer capability, an implementation of a stochastic Extended Kalman Filter (EKF) algorithm is proposed to provide optimal estimates of interconnected network states for systems in which some or all measurements are delayed. To have an accurate state estimation of a complete network, it is essential to have the capability of detecting bad data in the model. An efficient information debugging methodology based on the stochastic EKF algorithm is used for the detection, diagnosis and elimination of bad data.