Interactive 3D simulation of an urban neighborhood electricity grid, featuring modern houses, detailed electrical infrastructure, real-time smart meter data, and anomaly detection for power theft.
Instalação
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Interactive 3D simulation of an urban neighborhood electricity grid, featuring modern houses, detailed electrical infrastructure, real-time smart meter data, and anomaly detection for power theft.
Skill: UrbanGrid3DSim
Category: 3D Simulation & AI Analytics
Priority: High
Description
This skill enables DevinOS to create and manage an interactive 3D simulation of an urban electricity grid. It focuses on a generic neighborhood, procedurally generating streets, modern houses, electricity poles, overhead wiring, and transformers. Each house is equipped with a virtual smart meter providing live consumption data. The simulation integrates real-time power flow analysis and an AI-driven anomaly detection system to identify potential power theft or unauthorized load.
Purpose
To provide a powerful tool for urban planning, electrical grid management, and anomaly detection. It allows for visual inspection of grid infrastructure, real-time monitoring of power consumption, and proactive identification of power theft, thereby improving efficiency, reducing losses, and enhancing urban infrastructure management.
Trigger
Use this skill when:
A user requests a 3D interactive simulation of an urban area with electrical infrastructure.
There is a need to visualize power distribution and consumption patterns.
Anomaly detection in electricity usage is required for a specific geographical area.
Designing or evaluating urban electrical grid layouts.
Training AI agents on complex 3D environment interaction and data analysis.
Context
Geographical data for the target urban neighborhood (street layouts, plot sizes).
Architectural specifications or visual references for modern regional houses.
Technical specifications for electrical components (poles, wires, transformers, smart meters).
Real-time or simulated power consumption data for individual houses.
Defined rules for power distribution and load balancing.
Existing 3D asset libraries for common urban elements (trees, cars, etc.).
Workflow
Input Parameters: Receive natural language description or structured data specifying:
Number of streets (e.g., 3 streets).
Number of houses per street (e.g., 20 houses per street).
General architectural style (e.g., modern regional houses).
Electrical grid details (poles, wires, transformers at each branch head).
Simulation scenario (e.g., varying loads, specific theft scenarios).
Procedural Urban Generation:
Generate a 2D street layout based on input parameters.
Place house plots along the streets.
Procedurally generate 3D models of modern regional-style houses, ensuring variety and adherence to style guidelines.
Place electricity poles and transformers at specified locations (e.g., head of each branch).
Generate realistic overhead wiring connecting transformers to poles, and poles to individual houses, simulating physical sag and connections.
Electrical Grid Simulation Setup:
Assign initial load profiles to each house (randomized or based on provided data).
Configure the electrical network model (nodes, branches, loads) in a backend simulator (e.g., OpenDSS).
Establish data streams for real-time power flow and consumption from each smart meter.
3D Scene Composition and Rendering:
Integrate all generated 3D assets (streets, houses, poles, wires, transformers) into a unified 3D scene (e.g., using Three.js/React Three Fiber).
Implement interactive elements: clickable houses to display smart meter data.
Enable camera controls for pan, zoom, and orbit.
Visualize electricity flow through wires (e.g., animated textures or color changes).
Smart Meter Data Integration & Display:
Develop a mechanism to simulate or ingest live smart meter data for each house.
Upon clicking a house, display a pop-up or overlay with live electricity consumption (e.g., kWh, Amps, Voltage).
Anomaly Detection for Power Theft:
Continuously monitor total load on each transformer and compare it with the sum of reported loads from connected smart meters.
Implement an AI/ML model to detect discrepancies (e.g., if transformer load > sum of house loads, flag as potential theft).
Visualize detected anomalies in the 3D scene (e.g., highlighting the affected branch/houses in red).
Output & Reporting:
Generate a report detailing detected anomalies, their locations, and estimated stolen power.
Allow export of the 3D scene or simulation data.
Examples
Good Scenario: Balanced Load
User Input:
"صمم لي منطقة حضرية بثلاثة شوارع، كل شارع به 20 منزلًا حديثًا، أعمدة كهرباء ومحولات. الفرع الأول والثاني بأحمال متوازنة، الفرع الثالث به تجاوز."
(Design an urban neighborhood with 3 streets, each with 20 modern houses, electricity poles, and transformers. First and second branches have balanced loads, third branch has an overload/theft.)
Agent Action:
Generates 3D scene with 3 streets, 60 houses, poles, wires, transformers.
Simulates power flow. All smart meters report loads that sum up correctly to transformer readings for branches 1 and 2.
For branch 3, the sum of smart meter readings is significantly less than the transformer's measured load.
Highlights branch 3 in red, and provides a report indicating a detected power theft of X kWh.
User can click on any house to see its live smart meter data.
Bad Scenario: Unrealistic Input
User Input:
"صمم لي مدينة طائرة تعمل بالكهرباء السحرية."
(Design a flying city powered by magic electricity.)
Agent Action:
Identifies that the request falls outside the scope of realistic electrical grid simulation and architectural constraints.
Responds with:
"عذرًا، هذه المهارة مصممة لمحاكاة شبكات الكهرباء الحضرية الواقعية. لا يمكنني تصميم مدينة طائرة تعمل بالكهرباء السحرية. يرجى تقديم طلبات ضمن نطاق محاكاة الشبكة الكهربائية الحضرية."
(Sorry, this skill is designed for realistic urban electricity grid simulations. I cannot design a flying city powered by magic electricity. Please provide requests within the scope of urban electricity grid simulation.)
Anti-patterns
Attempting to generate highly detailed interior models for all houses without explicit request.
Ignoring real-world electrical engineering principles in simulation (e.g., Kirchhoff's laws).
Failing to provide clear visual feedback for anomalies.
Generating generic urban architecture instead of regional modern styles.
Creating a non-interactive 3D scene when interactivity is crucial for analysis.
Verification
Is the 3D scene visually coherent and representative of a modern urban neighborhood?
Are all specified elements (streets, houses, poles, wires, transformers) present and correctly connected?
Is the electricity flow simulation realistic and consistent with physical laws?
Are smart meters clickable, and do they display accurate, live data?
Does the anomaly detection system correctly identify power theft scenarios?
Is the 3D scene interactive (zoom, pan, orbit) and performant?
Can the agent handle variations in street layouts, house counts, and load profiles?
