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Two recent enhancements to Distributed Heterogeneous Simulation (DHS) are variable communication rates and higher-order predictors. Variable communication automatically controls the communication interval between any two subsystems in an attempt to achieve a desired accuracy during transient periods and maximize speed during steady-state periods. Higher-order predictors can better estimate the values of exchanged variables between data exchange instances, which can improve accuracy and possibly require fewer exchanges. A comparison between a single-computer simulation of an aircraft electric power system and an equivalent three-computer DHS show that the variable communication technique enables more accuracy and higher speed distributed simulations than fixed-step communication. In addition, higher-order predictors are shown to increase accuracy in some cases.

In this paper, a recently-developed algorithmic method of deriving the state equations of power systems containing power electronic components is described. Therein the system is described by the pertinent branch parameters and the circuit topology; however, unlike circuit-based algorithms, the difference equations are not implemented at the branch level. Instead, the composite system state equations are established. A demonstration of the computer implementation of this algorithm to model a variable-speed, constant-frequency aircraft generation system is described. Because of the large number of states and complexity of the system, particular attention is placed on the development of a model structure which provides optimal simulation efficiency.

In this paper, a new technique useful for the numerical simulation of large-scale systems is presented. This approach enables the overall system simulation to be formed by the dynamic interconnection of the various interdependent simulations, each representing a specific component or subsystem such as electrical, mechanical, hydraulic, or thermal. Each simulation may be developed separately using possibly different commercial-off-the-shelf simulation programs thereby allowing the most suitable language or tool to be used based on the design/analysis needs. For the purpose of demonstration, this technique is applied to a detailed simulation of a representative aircraft power system. This system is comprised of ten component models each developed using MATLAB/Simulink™, EASY5™, or ACSL™.

In this paper, a prototype DC Zonal Electrical Distribution System (ZEDS) developed under the Naval Combat Survivability effort is considered. A model of one zone is described in detail on a component level, and is viewed as a collection of interconnected dynamical subsystems each described by a set of state equations. An innovative approach for distributing the subsystems among multiple computers is shown to result in a significant improvement in simulation speed. Moreover, when Average Value Models (AVMs) replace the detailed converter models, a faster than real-time simulation can be achieved.

In the analysis of power-electronic-based energy conversion systems, it is important to identify the operational modes of the associated converters and inverters. However, as the number of switching elements increases, it becomes more difficult to analytically establish all possible modes of operation. In this paper, a modelling technique is described wherein a state-space representation of the overall system is generated automatically and updated dynamically as each new topology is encountered. Utilizing this approach, it becomes possible to identify the operational modes of converters and inverters based upon the cyclically repeated sequences of topologies that can be observed during steady-state operation. To demonstrate this technique, an example system comprised of a 6-phase synchronous machine, rectifier, and interphase transformer is considered. This system exhibits several distinct modes of operation that depend upon specific circuit connections.