Reliable model integration, simulation, and computation, based on HELM applied to the real-time operation of two interdependent systems (Electrical + Thermal). Big Data / Machine Learning complementary methodologies that will prove relevant to help HELM models assess failures, contributing to better future management. In NASA's words: "An opportunity for true symbiosis of human and machine intelligence working together'. Applications delivered follow recent NASA directives on Data Management, such as data standards and architectures to grow interoperability, leveraging partnerships and collaboration, and investing effectively & efficiently by increasing cross-agency and cross-stakeholder's exchange of data (Thermal and Electrical, Design and Maintenance Engineering, convergence of Fundamental Physics, Mathematics and Artificial Intelligence, etc.). If models and case examples advance enough on the joint electrical + thermal system, then the delivered results will inspire future prototypes that could be used in NASA and the aeronautic industry designs through related computations.
Results will advance the capabilities of the HELM toolset to support integration of the thermal and electrical subsystem in AC grids. Results will extend ongoing HELM-based SBIR and STTR projects from hybrid AC-DC electrical systems to also include associated thermal systems. Therefore, HELM can be deployable into small and microgrid larger contexts. Results open up new markets: utility microgrids, military operational bases, and ship and aircraft power systems. As new distributed energy resources (DER), such as distributed solar PV, wind energy, electric vehicles, and battery storage, are deployed, the need for automated operational solutions will increase. If they are to become widespread, they will need autonomous energy management systems with better real-time fault detection capacities, such as those contemplated under this project. Big Data/Machine Learning project-proven methods will be of relevance, as more and more components in these microgrids become Internet-of-Things-enabled, thus providing increasingly more data.