EcoGrid Intelligence: AI-Driven Climate Resilience Analysis

EcoGrid Intelligence: AI-Driven Climate Resilience Analysis for Global Energy Infrastructure on Liquid Galaxy is an AI-driven geospatial analysis system designed to proactively identify global energy infrastructure at risk of operational failure due to severe climate events such as heatwaves, droughts, and wind anomalies. It addresses the problem of critical infrastructure and meteorological data being siloed, which prevents stakeholders from achieving a unified, spatial understanding of risk. The solution dynamically fuses live climate anomalies with global energy infrastructure maps to create an interactive analytical canvas on the Liquid Galaxy platform. The EcoGrid Intelligence system follows a layered architecture: Data Sources and Risk Assessment: Climate Data: Streams live and forecasted climate anomalies, including temperature deviations, precipitation extremes, and wind intensity, from the Open-Meteo API. Infrastructure Data: Geospatial coordinates, generation type (hydro, nuclear, solar), and operational capacity are sourced from the Global Power Plant Database. Risk Model: A deterministic model computes a Climate Vulnerability Score (CVS) by evaluating localized anomaly intensity against the plant type's operational sensitivities. AI Orchestration: Google’s Gemini models act as the system’s brain to autonomously determine region-relevant climate anomalies, trigger API calls, interpret the resulting CVS metrics, and structure the output for spatial rendering. Visualization: The results are converted into Keyhole Markup Language (KML), generating elements like Placemark, LookAt, and FlyTo for native, synchronized rendering and camera guidance on the Liquid Galaxy multi-screen rig. Outputs: Primary displays render immersive climate anomaly heatmaps and color-coded nodes indicating vulnerability levels, while secondary screens display dynamically generated HTML content and AI-driven insights.