The most obvious and immediate NASA application for this technology is the ISS, which was used as the demonstration system for the Phase I. The ISS has a complex electrical power system that is redundant and segmented in nature. In addition, several factors including humans-in-the-loop and communication latency make the investigation into autonomous control of the ISS attractive. NASA's Advanced Modular Power System (AMPS) program is another potential application. The repeated use of modular components is particularly well-suited to analysis with a model library where parameters are flexible but the underlying mathematical model is the same. Additionally, an agent-based control scheme could provide modularity and plug-and-play capability to the controls as well as the electrical components. The wide applicability of the demonstrated approach enables this technology to also be applied to other robust and autonomous electrical power systems such as satellites, landers, rovers and other isolated or limited contact vehicles used during space missions. Other types of power systems can take advantage of the simulation architecture and proposed control approach. For example, terrestrial microgrid based systems that incorporate renewable energy sources are similar in nature to the ISS. These applications could include military operating bases or large office buildings. It should be noted that these systems can be either ac or dc in nature; however, the overall modeling environment and control structure can be largely the same. In the case of terrestrial microgrids, the simulation environment will provide (1) an inexpensive and fast means of simulating a detailed model (three-phase detail) of the dynamic system's electromechanical characteristics during isolated or near-isolated operation with potential new nuclear, solar, or wind power sources; (2) information to electric grid researchers regarding the control and aggregation of renewable energy sources which can lead to better informed decisions of stability and future system planning; and (3) an opportunity to electric grid system operators to evaluate the feasibility and advantages of a real-time or near-real-time simulation in the control of an electric grid for online dynamic security assessment, system control and/or reconfiguring, robustness to loss of system components, and operator training of a larger scale electric grid.