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power-flow-data

Parse and analyze MATPOWER network data from JSON files.

98|12|Updated May 15, 2026
Search Tags:#data parsing#network data#power system#MATPOWER format#power flow analysis
One-click install
npx skills add https://github.com/agentscope-ai/PawBench --skill power-flow-data-agentscope-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: power-flow-data
Source: https://github.com/agentscope-ai/PawBench/tree/main/data/pawbench-v1.0/assets/T129_skillsbench_energy-market-pricing/skills/power-flow-data
Command: npx skills add https://github.com/agentscope-ai/PawBench --skill power-flow-data-agentscope-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

This Skill assists in the efficient processing and analysis of large-scale power system network data, enabling the parsing and interpretation of complex data formats like MATPOWER.

Core Features & Use Cases

  • Standardized Data Format: Offers guidance on parsing power system test cases using the MATPOWER format.
  • Handling Large Files: Provides instructions for effectively handling large JSON files without inefficient line-by-line reading.
  • Network Topology: Offers detailed information on bus types and the per-unit system for electrical quantities.
  • Data Loading: Contains a Python function for loading network data from JSON files.
  • Use Case: This Skill can be utilized by energy professionals or researchers for power flow analysis by parsing bus, generator, and branch data.

Quick Start

Load power system network data from a JSON file using the 'load_network' function in the skill.

Frequently Asked Questions about power-flow-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I parse power system network data in MATPOWER format for power flow analysis?▼

You can parse MATPOWER format network data by loading bus, generator, and branch data from JSON files using a dedicated Python function designed for power flow analysis.

What is the best way to load large-scale power system network data without reading files line by line?▼

Loading large-scale power system network data efficiently requires using a Python function that parses the complete JSON file structure directly, avoiding inefficient line-by-line reading.

Does this approach to power flow analysis support interpreting bus types and the per-unit system?▼

Yes, interpreting power flow analysis data includes detailed information on network topology, specifically mapping bus types and converting electrical quantities using the per-unit system.

Can I use Python's json module to process large JSON files for power system test cases?▼

Yes, processing large power system test case JSON files utilizes Python's json module, providing specific instructions to handle large file parsing efficiently without line-by-line iteration.

What specific data components are extracted when parsing MATPOWER format files for network topology?▼

Parsing MATPOWER format files extracts bus, generator, and branch data components to construct the network topology, providing the essential structural inputs required for power flow analysis.

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