GridMind Autonomous Multi-Agent Grid Governance

GridMind AG is an autonomous multi-agent governance system designed to manage the unpredictable fluctuations of modern, renewable-heavy power grids. Traditional mathematical optimization solvers work perfectly under stable conditions, but they quickly stall or fail when hit with sudden, real-world anomalies—like a micro-cloud instantly dropping a major solar array's output. To bridge this gap, we used LangGraph to build a network of specialized, Gemini-powered agents that function as an intelligent supervisory layer directly over the raw grid telemetry. One agent constantly evaluates the incoming sensor data for rapid frequency anomalies, while another monitors hard physical constraints. When a critical threshold is breached, the orchestration agent safely overrides the standard mathematical solver to execute fast, corrective control loops—such as dynamic load shedding or immediate power rerouting—to keep the distribution network stable and prevent a cascading blackout. Crucially, every single autonomous decision made by the network is backed by explicit reasoning and recorded as structured, auditable JSON logs. This creates a completely transparent history of agent actions that stream in real time to a React dashboard, giving human operators complete visibility into the exact logic behind every system intervention.