Holomorphic Embedded Load Flow for Autonomous Spacecraft Power Systems, Phase II

The proposed innovation advances the ability to apply the Holomorphic Embedding Load Flow Technology (HELM™) method to provide deterministic load flow modeling for spacecraft power systems.

Future deep-space vehicles need intelligent, fault-tolerant and autonomous control of power management and distribution. Due to communications latency, control algorithms for future autonomous space power systems need to be very robust, highly reliable and fault tolerant.

Modeling of load flows is vital both to design spacecraft power systems and to operate them autonomously. A key element is state estimation—given the available sensors and their readings, what is the real state of the system? What action is required to maintain operation? State estimation is especially important when the system is in an off-nominal condition. Human operators draw upon experience to integrate off-nominal sensor readings and develop a gestalt of system state, but autonomous operation requires computation.

Current modeling techniques (i.e., Newton-Raphson (NR) optimization) are not equal to this task due to their iterative nature and initial point dependency. Many off-nominal cases cannot be solved at all using NR. Worse, even more off-nominal cases appear to be solvable using NR, but the solutions are actually invalid. An NR-based autonomous control system faced with off-nominal conditions will reach an incorrect conclusion more often than not, with potentially catastrophic consequences for the spacecraft.

By contrast, HELM™ provides deterministic solutions for off-nominal states, without dependence on initial solution seeds, thereby providing the level of fidelity and surety needed to develop an autonomous system. In Phase I, Gridquant Technologies LLC successfully adapted HELM™ to solve the non-linearity problems of a small DC micro-grid, which will enable NASA to develop and implement the advanced architectures needed for future long-term deep-space exploration.

Data and Resources

Additional Info

Field Value
Maintainer TECHPORT SUPPORT
Last Updated August 14, 2022, 01:16 (CDT)
Created August 14, 2022, 01:16 (CDT)
Identifier TECHPORT_33667
Issued 2017-05-01
Modified 2020-01-29
accessLevel public
bureauCode {026:00}
catalog_@context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
catalog_@id https://data.nasa.gov/data.json
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
catalog_describedBy https://project-open-data.cio.gov/v1.1/schema/catalog.json
landingPage https://techport.nasa.gov/view/33667
programCode {026:027}
publisher Space Technology Mission Directorate
resource-type Dataset
source_datajson_identifier true
source_hash 18857a3892869be01e672fb2eb7affe0e585069c
source_schema_version 1.1