As the world accelerates its transition to clean and renewable energy, smart grids face increasing complexity — managing fluctuating solar/wind input, ensuring grid stability, and maintaining compliance with safety standards. Traditional grid control systems are no longer enough.
We were inspired to build an AI agentic system that could help utilities autonomously monitor, reason, and act in real time — unlocking the full potential of smart grids powered by clean energy.
⚡ What It Does Smart-grid Agentic AI is a multi-agent system powered by LangChain and Gemini, designed to monitor, diagnose, and manage smart grid operations in real time.
🔹 Monitoring Agent – Continuously scans voltage, frequency, and fault data from the grid. 🔹 Control Agent – Uses Gemini's reasoning to suggest safe and optimal actions (e.g., load shift, storage dispatch). 🔹 Compliance Agent – Retrieves and interprets standards like IEEE 1547 using RAG. 🔹 Reporting Agent – Summarizes system health and decisions for human operators.
It simulates a real-world smart grid and allows AI agents to reason over streaming data to make intelligent decisions — helping integrate more renewables safely and reliably.
🛠️ How We Built It LangChain Agents: Each agent has a unique toolset and role, collaborating using LangChain's multi-agent orchestration.
Gemini API: For advanced reasoning, technical document understanding, and decision-making.
Chroma DB: For document retrieval and RAG (Retrieval-Augmented Generation) from standards and manuals.
Simulated Grid Data: Time-series CSV simulates voltage, frequency, and fault signals.
Successfully implemented an agentic reasoning system capable of monitoring and managing smart grid conditions.
Integrated Gemini's advanced reasoning with retrieval from real technical documents to ensure industry compliance.
Built a clean and extensible multi-agent architecture ready for real-world deployment or extension.
Made clean energy a central theme — not just technically but ethically.
Built With
- langchain
- llm
- mongodb
- rag
- react
- typescript

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