Hitachi and the Southwest Power Pool (SPP) have entered into a strategic partnership aimed at addressing challenges in the modernization of U.S. energy infrastructure, with a focus on improving the generator interconnection (GI) process.
The collaboration will develop an integrated, AI-enabled solution intended to reduce the time required for GI study analysis by up to 80%. The goal is to support more efficient decision-making for GI customers and to enhance SPP’s ability to integrate new generating capacity across its 14-state region.
Electricity demand in the U.S. is rising, driven by factors such as data center development, increased manufacturing activity, and broader electrification trends. Data center electricity consumption, for example, is projected to grow from 4.4% of U.S. electricity demand in 2023 to as much as 12% by 2028. In SPP’s territory, resource margins are forecast to decline from 24% in 2020 to 5% in 2029 if current trends continue.
A significant volume of generation—more than twice the amount currently produced in the U.S.—is awaiting approval in the interconnection queue. These delays are primarily due to the complex technical studies required to assess potential impacts on grid reliability and performance before new resources can be connected.
To address this challenge, the project will leverage a range of capabilities from across Hitachi’s portfolio. These include Method’s design services, GlobalLogic’s software engineering, Hitachi Energy’s modeling tools for energy portfolio management, Hitachi R&D’s AI algorithms for energy systems, and Hitachi Vantara’s infrastructure platform, Hitachi iQ, which incorporates NVIDIA computing and AI technologies.
SPP, serving as the regional transmission organization, will lead the integration of these technologies, applying its experience in energy system coordination and grid optimization. The organization will also provide guidance to ensure that the initiative aligns with operational standards and industry regulations.
The planned AI-based system is designed to automate processes, enhance predictive analysis, and support integration with communication systems. These tools are intended to streamline various aspects of the GI study process and complement ongoing improvements at SPP, including efforts to update its transmission planning approach.
Phase one of the project is expected to conclude by winter 2025/26, with goals that include accelerating current systems, refining data management, and deploying AI-enhanced simulation modeling.
