The increasing integration of distributed energy resources (DERs)—such as renewable generation, energy storage systems, and responsive loads—has introduced significant variability and complexity into modern power systems. As the scale of controllable devices grows, traditional manual configuration and static management frameworks impose a heavy cognitive burden on grid operators, making it increasingly difficult to manage the system efficiently and respond to dynamic changes in real-time.
Building on this foundation, our current work focuses on the novel paradigm of Intent-Based Energy Management System. This approach bridges the semantic gap between human operational goals and machine-level control:
- Intent Translation & Mapping: The system automatically parses abstract Operator Intents into executable control policies for physical and virtual resources.
- Closed-Loop Verification: By establishing a feedback mechanism between the infrastructure and the intent translator, the system ensures continuous alignment with operational goals.
This approach fundamentally transforms grid management by shielding operators from the complexity of underlying physical resources. It allows for intuitive, goal-oriented supervision, ensuring that the power system remains manageable, resilient, and responsive even as complexity scales.
