The US Air Force (AF) and the Department of Defenseâs (DoD) future requires a fundamentally different kind of energy infrastructure â one that is more distributed and less reliant on fossil fuels. This requires real-time access to data on energy sources, usage levels, operating conditions and disruptions. Establishing the framework for a secure platform to manage energy data is a key step in DoD/AFâs energy transition. Kinnami and West Virginia University (WVU) are proposing an integrated, secure, distributed data collection and analytics platform to advance DoD/AF decision making. Our project will establish the key indicators, data transmission formats/protocols, data collection sources and provide analysis tools/algorithms necessary for informed AF decision making. In Phase I, we will engage with target AF customers to identify needs, develop a Phase II project and execute an MOU to deliver a resilient energy data and analysis platform to the Air Force. Reliable energy for DoD/AF operations and the associated energy data for decision making are key elements for mission success. Decision-making requires reliable energy data collection, storage, availability and secure collaboration. In an IoT/sensor-dominated era, upon which generates real-time energy data that decision-making relies, it is also imperative to consider the dataâs threats and trustworthiness when deploying connected devices. WVUâs grid analytics system cannot operate without trustworthy energy data. Data has been collected by utilities and ISOs for years but is unavailable and not in a suitable form for processing. Currently, WVU uses static Supervisory Control and Data Acquisition (SCADA) which is insufficient for current analysis which requires additional real-time Phasor Measurement Unit data. For example, access to real-time data and WVUâs models can be used for identifying potential grid problems before they cause catastrophic failure in DoD/AF micro-grids. DoD/AF are not alone in reimagining energy needs. WVU researchers have realized that the lack of access to real-time energy data impedes everyoneâs ability to identify problems and opportunities, commercial or otherwise. WVUâs power system lab specializes in grid analytics, monitoring & control, disruption and system modeling, but without access to key energy data, these capabilities are not realized. This must be addressed in order to facilitate the challenge involved with new distributed energy resources. Security and privacy are major concerns for data collection/sharing for every energy producer. Kinnamiâs AmiShare is a distributed, integrated storage and security platform that removes these obstacles for defense and commercial markets. Our proposed energy data platform, underpinned by AmiShare, will support not only WVUâs analysis tools but also will support the development of other analysis tools such as AI/ML applications to meet f
