The company’s software products have been assembled to leverage proliferation of distributed resources and their streams of data along with the desire to transact with each other and the utility. CEO, Tom Osterhus states, “We built our software applications to ingest the terabytes of historical customer and grid performance data that inform forecasts of future use and optimal location and value of distributed resources.” IA’s software provides a multi-year ‘blueprint’ for growth on the grid, by location, for planning and capital deployment to efficiently match future needs by corresponding the expected attributes of customer need with known characteristics of potential production assets.
As the energy industry evolves, utilities want dynamic products that they can configure and grow with their needs to forecast load, prices and execute programs to manage their distribution systems better. IA offers two primary products; LoadSEER for the distribution planning and resource integration groups and IDROP, for near-real time operations of grid edge portfolios, to manage these emerging needs.
We built our software applications to ingest the terabytes of historical customer and grid performance data that inform forecasts of future use and optimal location and value of distributed resources
One of IA’s clients, Pacific Gas & Electric (PG&E) in California—a combined natural gas and electric utility has been a dedicated user of IA’s LoadSEER software. Several dozen engineers in various areas of the utility leverage IA’s scenario analysis capabilities to “stress test” sections of the grid, providing stakeholders and regulators the value and capacity to host higher penetrations of solar assets on the system. PG&E has adopted LoadSEER as core to its planning environment and uses the software to understand the impacts of a “multi-owner” energy portfolio.
Applied data science within scale data architecture is the only way to ensure that utilities and other participants in the distributed energy markets may make capital and system decisions based on the most granular sets of data and understand the interaction between utility and customer. “The complexity of these interactions at the edge require a platform approach that may house and compute against a multitude of scenarios; we will continue providing the proven software on which utilities and others may rely to embrace a complex future,” concludes Osterhus.