Space-Time Insight Adds Predictive Analytics
Space-Time Insight has announced some next-generation capabilities timed for debut at next week’s Distributech Conference (Jan. 28 – 31). The company is focused on problem solving for asset-intensive industries, with many large deployments with electric utilities. The company focuses on freeing data from many different silos and sensor systems for real-time awareness and understanding of system performance and replacement issues. The new product features include predictive analytics to forecast and plan for unexpected events.
The company’s server-based tools pull from SAP and Oracle databases as well as legacy systems, meters and sensor networks, and even social media. The server does the data aggregation function, and doesn’t pull and store data, but instead helps visualize and catalog status and events that allows users to query across both time and space. The tools also are helpful to correlate asset data to other inputs, gauging the impacts of sun, ice, wind and heat. With this kind of understanding, along with performance-related degradation of assets, you can see that it’s not too much of a stretch to begin predicting outcomes and planning long-term maintenance.
Space Time Insights has recently won a contract for the Southern California Edison smart grid demonstration in Irvine., where their geospatial and visual analytics software will provide a centralized view of multiple technologies, assets and services deployed—ranging from smart meters and advanced distribution equipment to renewable power sources, security networks, energy-efficient home appliances, solar systems, electric vehicles and more.
“With so many integrated technologies we need a visualization and analysis system capable of giving us insight into what’s working, what’s not and how we can continuously improve the interconnectivity and interoperability of all the systems involved in the project,” said Doug Kim, Director Advanced Technology, Southern California Edison.
Using Space-Time Insight’s software, SCE will be able to understand critical aspects of the smart grid, such as the impact of electric vehicles on off-peak energy consumption, the cost and emissions savings of circuit voltage optimization, and many of the potential distribution system benefits.
Field service is another big issue with utilities with widely geographically dispersed assets and the need to send a skilled technician remotely to service these assets when they falter or fail. With the greater detail on the point of failure that Space-Time Insights tools provide, they can send the right person with the right skills with the right tools and materials, decreasing costs.
The new predictive analytic capability is particularly suited for outage planning. Users can view such things as a projected storm path and see reports related to expected asset loss and customer impacts. Multiple models and outcomes can be visualized and assessed, making for better contingency planning.
With this new level of business intelligence that isn’t pre-defined, users get whole new insight and understanding of the dynamic nature of their networks. The connection between performance across space and time leads to a whole host of helpful analysis.