Grid Optimization & DERMS

The electric grid was built to push power one way, from large plants to homes and businesses. That model is breaking down as millions of rooftop solar panels, home batteries, EV chargers, and smart devices connect at the edge — each one both a load and, potentially, a resource. Managing this two-way, fast-changing network is one of the hardest problems in energy, and it is where distributed energy resource management systems, or DERMS, and grid-optimization software come in.

AI is what makes real-time coordination possible at this scale. Machine-learning models forecast load and generation, optimization engines decide how to dispatch and balance thousands of devices, and a new generation of generative-AI assistants help control-room operators make sense of the flood of grid data. Grid-enhancing technologies add another layer, using sensors and analytics to safely push more power through existing wires. The common thread is turning overwhelming complexity into decisions an operator can act on.

In the control room, OATI Genie brings agentic generative AI to grid operations, cutting outage-processing time dramatically at the California ISO. Camus Energy gives utilities and cooperatives real-time visibility and coordinated control of distributed energy resources, and the established grid platforms — GE Vernova GridOS, Hitachi Energy Grid Automation, Schneider EcoStruxure, and Eaton Brightlayer — embed AI across grid management, while Uplight engages customers and their devices as flexible resources. Grid-enhancing technologies from LineVision and Heimdall Power use sensors and analytics to unlock spare capacity on existing transmission lines.

AI is shifting grid operations from reacting to problems toward anticipating and orchestrating them, which is essential as distributed resources multiply and load grows. The work of the grid operator moves from manual monitoring toward supervising AI recommendations and handling the exceptions, raising the value of engineers who understand both power systems and data. The honest caveat is that the grid is safety-critical and heavily regulated, so AI here augments proven physics-based operations rather than replacing operator judgment — a wrong dispatch decision has real consequences. Used well, these tools let utilities absorb far more clean, distributed energy without rebuilding the grid from scratch.