The objective of this funding opportunity announcement (FOA) is to enhance grid reliability and resilience through R&D with demonstrations of analytics that utilize power system sensors to develop tools for the grid of the future. Demonstrations with power sector utilities is required since this will help ensure that the analytics can meaningfully support power sector system planning and operations. Projects that build on/implement industry standards like CIM and existing platforms like GridAPPs-D are encouraged to help facilitate scalability, interoperability, and relevance of the work to the broader electricity industry. Primary use of synthetic data or model generated data do not meet this FOA objective.

An applicant’s project team should, at a minimum, include:

1. an electric utility or a system operating entity serving the area with the field demonstration,
2. a system planner relevant to the service territory of the demonstration,
3. a domestic technology product provider, and
4. a domestic technology developer. It is encouraged that teams also include universities and community organizations (such as municipalities, tribes, school districts, etc.).

The Overall FOA objectives are:

• A field demonstration of a relevant sensor utilization/data analytics technology – this should be no less than 20% of the project scope.
• Design and validate case studies that consider both rural and urban uses of sensor data for enhancing the resilience and reliability of the grid.
• Develop scalable methodologies for enabling distribution system protection using senor data.
• Develop novel methods for harnessing big data to enable automated event detection and classification.
• Establish innovative approaches for generating and recording contextual information associated with historical data to enable automated data labeling.
• Develop new approaches for capturing contextual information associated with data generated by grid sensors.
• Develop rigorously validated approaches to enable uncertainty-informed load forecasting with variable (moving) prediction time horizons as well as computationally efficient online learning; a focus on extreme weather and climate conditions is encouraged.
• Develop technology that integrates human factors and/or cognitive science considerations to enhance effectiveness of decision support systems related sensor data analytics.
• Develop uncertainty-informed data-integration methods to enable integrating data from multiple sensors and sources with variable degrees of data veracity.

Projects should have a distribution focus, but projects that look at both transmission and distribution are encouraged.

There is one area of interest for this FOA: Sensor Data Analytics Demonstrations for system monitoring and control. Projects should support at least one of the following:

1. Demonstration of applications utilizing existing AMI data
2. Demonstration utilizing high fidelity synchronized measurement for grid stability monitoring and control
3. Demonstration of applications utilizing mixes of different sensors for improving grid resilience, security, and safety leveraging commercial off-the-shelf sensors

Projects should have a distribution focus but projects that include both transmission and distribution are encouraged.

Total federal funding of $7.0M will be available to research and development (R&D) and demonstrations tasks. Projects must include an R&D phase and a demonstration phase and must break out funding allocated to each. Applicant organization(s) must provide 20% cost share for the R&D phase and 50% cost share for the demonstration phase. Projects should culminate in a field demonstration – the demonstration portion of the project should be no less than 20% of the total project scope.