Convergence Data Analytics was founded out of Stanford’s Sustainable Systems Lab with a mission of applying powerful data analysis and machine learning tools to large samples of AMI data to solve real world problems faced by utilities, regulators, planners, and customers.
As in many other industries, the relationship between utilities and their customers is being fundamentally altered by information technology. AMI infrastructure provides a steady flow of highly detailed spatial and temporal data on consumption.This data provides unprecedented detail on patterns of customer usage and can be leveraged to capture immense value from better understanding and managing the demand side of the grid and providing more personalized communications and services for customers.
But data also comes with responsibilities. How to collect and store it? How to protect it from misuse? How to earn the trust of customers who do not know the details of or may not approve of its usage? There is a growing need to deliver data-based services that are relevant to and valued by customers and that demonstrate that meter data is being used responsibly and transparently.
The open source tools that we’ve developed and integrate for our clients allow internal staff and non-technical users to apply sophisticated, extensible, and customizable algorithms to large samples of meter data and to interpret and learn from the revealed characteristics of their customers, while enforcing strict data protections and preserving anonymity. The software is designed to be adaptable to a wide range of data sources and formats and the resulting derived customer features have obvious applications in improving customer segmentation and targeting for EE and DR programs, implementing repeatable and data-driven evaluation methods, and supporting distribution level planning exercises.