SBIR-STTR Award

Advanced Visualizations for Smart Grid Data Analytics
Profile last edited on: 12/29/2020

Program
SBIR
Agency
DOE
Total Award Amount
$1,349,294
Award Phase
2
Principal Investigator
Harvey Smallman
Activity Indicator

Company Information

Pacific Science & Engineering Group (AKA:PSE~Pacific Science and Engineering Group)

9180 Brown Deer Road
San Diego, CA 92121
   (858) 535-1661
   info@pacific-science.com
   www.pacific-science.com
Multiple Locations:   
Congressional District:   52
County:   San Diego

Phase I

Phase I year
2020
Phase I Amount
$199,999
Next-generation power grid technologies such as smart meters and load controls help meet current energy demands and prepare for the future. These grid technologies offer unprecedented visibility into the power grid but also add an overwhelming amount of data that must be integrated and interpreted by system operators for managing grid load, preventing surges and outages, and managing safety risks to the grid in real time. Current monitoring displays are visually and functionally non-integrated and inflexible to the information needs of the grid management team, often resulting in slow, reactive decision-making and an inability to manage risks in real-time. The project team proposes to research, develop, and demonstrate a decision support system that promotes proactive decision making and enables real-time risk management in grid operations. This decision support system will enable real-time risk management by automatically integrating data from disparate sources, allowing operators to quickly understand and evaluate the impact of those data on grid management decisions, and externalizing the decision-making process to improve decision transparency and quality. In Phase I, a tailored user-centered design process to develop a new decision support display concept that supports real-time risk management will be employed. This process will be used to identify the risk management needs of representative system operators and grid managers from a local utility company strongly endorsing this effort, determine the cognitive challenges related to integrating and processing information needed for making risk management decisions, design and communicate its decision support design concepts, assess the technical feasibility of its new decision support design concepts, and secure endorsement of this work for modernized grid operations. In Phase II, the project team will develop a data-driven, working prototype of the decision support display concept for transition to a local utility company, and potentially power system vendors, for implementation, testing, and refinement. This project will lead to more informed and well-managed risk mitigation, in turn leading to wider benefits of more reliable energy service with fewer interruptions, reduced consumer and business costs associated with power outages and system failures, and increased public safety from well-managed power grids.

Phase II

Phase II year
2021 (last award $$: 2021)
Phase II Amount
$1,149,295
Current grid monitoring displays are rich with data, but visually and functionally nonintegrated and inflexible to the information needs of the grid management team. This often results in slow, reactive decisionmaking and an inability to manage risks in realtime. In this Phase II SBIR, the project team will develop a working prototype of the human machine interface HMI concept constructed in Phase I, validate the performance benefits of the concept, and expand the scope to support different emergency operations, normal operations, and the transition between the two. In Phase I, the project team researched, developed, and demonstrated an HMI concept that supports realtime risk management in emergency grid operations during the Public Safety Power Shutoff PSPS process in response to wildfire risk. This HMI supports realtime risk management by automatically integrating data from disparate sources, allowing operators to quickly understand and evaluate the impact of those data on grid management decisions, and externalizing the decisionmaking process to improve decision transparency and quality. The HMI concept was created through application of our tailored usercentered design UCD process. Phase II will consist of two main technical work threads. First, the project team will implement a working prototype of the HMI concept developed in Phase I and use this prototype to conduct a performance validation of the concept. Second, we will extend our successful UCD process employed during Phase I to broaden the scope of our HMI concept to other nonPSPS emergencies and normal grid monitoring operations to extend our support of modernized grid operations. In general, this project will lead to better, more consistent, defensible, and transparent grid monitoring and risk management decisions, in turn leading to wider benefits of more reliable energy service with fewer interruptions, reduced consumer and business costs associated with power outages and system failures, and increased public safety from well managed power grids.