20.3C : Energy Resilience for Air Force Operations through Local Energy Exchanges
The US Air Force (AF) and the Department of Defense’s (DoD) future requires a fundamentally different kind of energy infrastructure – one that is more distributed and less reliant on fossil fuels. As renewables advance, less power will be generated by traditional sources and more from dispersed small individual producers. This offers an opportunity and a challenge to DoD/AF. New producers provide increased energy capacity over a larger geographical footprint, which implies a more resilient national security asset while lowering DoD/AF costs and impacts. The challenge is being able to understand these resources and how to access them.
Kinnami and Case Western Reserve University (CWRU) propose to develop Local Energy Xchanges (LEX), regional energy marketplaces for the trade of renewable energy which will provide DoD/AF the data needed for awareness of new opportunities to reduce carbon emissions and of how to access new energy resources.
The goal of this effort is to establish a technical architecture that will address DoD/AF needs for resilient data in current and future energy systems/operations. We will secure the support of an Air Force Phase II project sponsor and select a location for proof of concept.
LEX provides a new resource for energy data collection currently unavailable to the DoD/AF. Forecasts in EIA’s Annual Energy Outlook 2020 (AEO2020) call for residential solar photovoltaic (PV) capacity increases by an average of 6.1% per year through 2050 and commercial PV capacity increases by an average of 3.4% per year.
Having access to real-time energy data on location, generation and storage capacity, access and availability provide key new metrics and more options for DoD/AF decision making and better utilization of all available energy resources.
Understanding the make-up and status of these new resources will be fundamental to future energy resilience for normal DoD/AF operations, during natural disasters or in the battlespace. CWRU’s development of Community-Based Resource Allocation (CoBRA) tools combined with AmiShare, Kinnami’s resilient data platform, provides a secure environment for LEX activities. CoBRA’s electricity management tools facilitate multiple market mechanisms for LEX participants to make sense of the marketplace and identify the best opportunities. CWRU’s involvement with the IoT Collaborative and Great Lakes Energy Institute creates a network of research, industry, government, neighborhood and non-profit entities that form an ecosystem of talent and knowledge for the project. Kinnami’s AmiShare resilient data platform is the foundation for LEX. AmiShare is a distributed, integrated storage and security platform that protects sensitive information everywhere. Kinnami's data platform is engineered to perform in degraded environments, stores data securely on any storage device while treating all storage and access devices as hostile. These are key security tenets the DoD/AF will require.
Anticipated Benefits Our proposed solution enables the secure use of previously unknown or unavailable real-time energy data to create a more resilient energy system improving decision making, optimizing costs while reducing emissions.
Key benefits:
- Better energy indicators: The platform will provide real-time data on available energy resources, generation status/situational awareness, storage capabilities, transport options and service disruptions.
- Increased productivity: Visibility into energy data networks (performance, service gaps, storage, etc.) will enable autonomous operations and the adjustment of resources for situational needs and energy conservation through AI/ML analysis of this data.
- More/better energy options: DoD/AF bases will be able to tap into a larger market of both buyers and sellers building redundant energy networks around essential facilities while being able to securely use and share energy data. Surplus power produced by local energy networks can be a low-cost source of energy to DoD/AF operations. For example, as storage capacity increases, installations could share or sell excess capacity during high demand/price periods and restore in low or even negative market posture, e.g., wind energy at night.
- More tactical data: Data from energy networks is a useful tool to forecast the potential energy resource in a particular area/mission. This could be critical for operations planning purposes.
- Resiliency in degraded environments: Whether in the battlespace or during a natural disaster, access to real-time energy status data provides insight and options for operations and recovery.
- New energy information: Local energy networks act independently from central grids and provides resiliency when the central grid has been compromised. Having access to data from such networks allow the DoD/AF to understand system conditions at all times. FEMA, DHS and programs like AFWERX Agility Prime will benefit from access to this data. The need for this type of platform extends to a variety of stakeholders on a global scale.
Our initial go to market approach is comprised of three focus areas. The first is directly working with businesses and utilities. Businesses are being pressed to improve their energy portfolios while utilities require more and better indicators as to service gaps in order to address new market demands. Second is to engage with government, including cities and at the local level, in order to achieve carbon reduction targets and smart city monitoring, for which usage of the common data architecture (CDA) at the grassroots level is key. Our third focus area involves building an ecosystem around the platform that fosters further innovation. We foresee this project providing opportunities for developers to develop energy or other related applications. A Developer Hub complete with APIs and distributed data security will establish this ecosystem.
Agility Prime (X20.D) : Data Resilience for the Future of Flight (ORB/eVTOL/UAMs)
The West Virginia University (WVU) Statler College of Engineering and Mineral Resources has created an innovative location-sensing software technology for unmanned aerial and ground systems when operating in challenging environments, such as degraded or denied GPS. This distributed system with agents onboard and on the ground uses an Air Data Vehicle Network and requires resilient data management not only for the command and control systems but also for all data collected by sensors onboard the device to secure the data and guarantee their integrity and privacy. Kinnami Software Corporation has developed a distributed resilient data platform, AmiShare, that has the ability to secure sensitive data and assure its integrity wherever that data is collected, stored, or shared. AmiShare can work in degraded environments.
This Phase I STTR project proposes a feasibility study to investigate integrating WVU’s location-sensing software technology with Kinnami’s distributed resilient data platform, AmiShare, and propose a technical architecture of enhanced software that is able to operate in a wider range of degraded environments, including in hostile airspace which is critical for ORB/eVTOL/UAM operations especially in disaster relief, humanitarian aid and logistics supply missions. Integration of WVU’s robotic location-sensing technology with Kinnami’s AmiShare technology will address key focus areas for Agility Prime especially in degraded environments.
During the course of this project, we will also identify a partner in the Air Force to sponsor a Phase II project to develop and test a proof of concept and we are already in discussions with a number of potential partners. WVU’s research specializes in robot localization technology for challenging environments. Its innovative research focuses on the use of multi-sensor fusion, adaptive estimation algorithms for learning sensor uncertainties without prior knowledge, the use of cooperative active perception to reduce localization errors through the motion planning ground robots and aerial robots, and the use of learning algorithms to assess environmental conditions. Kinnami is a data security company that provides tools for securing confidential information using client-side encryption. AmiShare’s distributed secure storage platform manages data security, protection & availability by defining policies for who may access data and where data are stored, providing access & protection everywhere on unreliable networks. This includes data centers, cloud, laptops, mobiles, removable drives & IoT. Data access & storage are audited and managed by administrators who define these policies, transparently to end-users.
20.3C : Energy Data Platform for Resilient DoD Operations
The US Air Force (AF) and the Department of Defense’s (DoD) future requires a fundamentally different kind of energy infrastructure – 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/AF’s 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 data’s threats and trustworthiness when deploying connected devices. WVU’s 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 WVU’s 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 everyone’s ability to identify problems and opportunities, commercial or otherwise. WVU’s 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. Kinnami’s 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 WVU’s analysis tools but also will support the development of other analysis tools such as AI/ML applications to meet future DoD/AF needs.
Anticipated Benefits
- Better energy indicators: The energy data platform provides real-time data on available energy resources, generation status/situational awareness, storage capabilities, transport options, & disruptions for arbitrary energy analytic and control platforms. WVU’s Grid Analytics is the first of many.
- Security and Privacy: DoD/AF needs a secure & resilient data platform to install confidence, provide transparency & track accountability around energy data.
- Data Availability: Unreliable access and sharing of sensitive data are obstacles to productivity. Our solution removes these problems by dynamically facilitating & auditing secure data access and sharing.
- Increased productivity: Visibility into energy data networks (status, service gaps, storage, etc.) enables the autonomous operation & adjustment of resources for situational needs & energy conservation through AI/ML analysis.
- More/better energy choices: As energy generation increases from new sources, increased data collection/analysis will reveal cost options or service gaps which DoD/AF can evaluate when building redundant energy networks for essential facilities.
- More tactical data: Analyzing data from energy networks is a useful tool to forecast the potential energy resource in a particular area/mission and may be critical for operations planning.
- Resiliency in degraded environments: The resilient data platform responds dynamically to changes in the environment as well as automates decisions to move data using whatever resources are currently available, critical in degraded/battlefield environments.
- New energy information: New & dispersed renewable energy generation is & will continue to grow exponentially. Data collection from new sources such as local energy networks or cooperatives will be important to future DoD/AF decision making. Local energy networks/cooperatives act independently from central grids & offer resiliency when the central grid has been compromised. Access to data from such networks or other previously unknown sources, allows DoD/AF to understand system conditions at all times. FEMA, DHS & programs like AFWERX Agility Prime will benefit from access to this data.
Kinnami plans to commercialize this solution with a variety of sectors including infrastructure, energy/utilities & logistics by accelerating research & technology development in a military setting. Kinnami is already in commercial discussions with three groups in the infrastructure & energy sectors about the deployment of similar technology & expects commercial revenues to scale rapidly once the platform is proven.