In-situ Atmospheric Intelligence for Hybrid Power Grids: Volume 2 (Automated Data Flow Tests)
Abstract
Uninterrupted electrical power is critical to current and future successes of the armed services. Future Multi-Domain Operations battlefields will be filled with multiple dissimilar energy networks. To achieve battlespace dominance, energy flow characterizations of individual platforms and the aggregate battlespace must be developed to adapt and exploit the variable operating conditions. The Atmospheric Intelligence for Hybrid Power Grids (AI-HPG) Project goals seek to develop and demonstrate the ability to use organically obtained atmospheric knowledge to forecast and optimize a hybridized grids short-term energy requirements. The current effort focuses on effectively integrating photovoltaics, as a local energy source, into traditional power resources for demonstration purposes. Once successful, a wide range of locally sourced energy sources could follow. This project focused on investigating an AIHPG Test-bed that would generate data that could prove/disprove the feasibility of integrated, tactical hybrid power and provide additional real-world measurements useful to future simulation work. In Phase I, a tactical hybrid power simulation with atmospheric input was constructed. Phase II proved the feasibility of the simulation. This report documents Phase IIIs success in automating the AI-HPG Test-bed, which consists of three major components: atmospheric intelligence, power optimization, and coincident data acquired to calibrate AI-HPG Testbed components.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 18, 2020
- Accession Number
- AD1109968
Entities
People
- Gail Tirrell Vaucher
- Gordon Parker
- Michael D Lee
- Morris Berman
- Robert A Jane
- Sean D'arcy
- Thomas Price
Organizations
- United States Army Research Laboratory