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power-flow-data

Analyze MATPOWER power system data to extract topology and operating metrics.

Updated Jan 15, 2026
Search Tags:#json-parsing#matpower#power-flow#grid-data#bus-gen-branch#per-unit#load-flow
One-click install
npx skills add https://github.com/KaiserWhoLearns/skillsbench --skill power-flow-data
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: power-flow-data
Source: https://github.com/KaiserWhoLearns/skillsbench/tree/main/tasks/grid-dispatch-operator/environment/skills/power-flow-data
Command: npx skills add https://github.com/KaiserWhoLearns/skillsbench --skill power-flow-data

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Power system data often comes in MATPOWER format, which is cumbersome to parse and analyze without a clear guide. This skill provides practical instructions to efficiently load and interpret bus, generator, and branch data for power-flow studies.

Core Features & Use Cases

  • MATPOWER format support: bus, gen, branch, and gencost data with per-unit system guidance.
  • Efficient loading approach for large networks using Python's json parser rather than line-by-line reads.
  • Utilities for mapping non-contiguous bus numbers and identifying the slack bus.

Quick Start

Load a MATPOWER-formatted network.json and follow the guide to compute basic topology and system loads.

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 MATPOWER power-flow data using Python?▼

To parse MATPOWER power-flow data, load a network.json file using Python's json parser and NumPy arrays to extract bus, gen, and branch tables into structured outputs.

What is the best way to load large MATPOWER network files?▼

The best way to load large MATPOWER network files is using Python's json parser for bulk loading rather than line-by-line reads, which efficiently processes topology and operating metrics.

How do I identify slack buses and PV/PQ classifications in grid data?▼

Identifying slack buses and PV/PQ classifications in grid data requires analyzing the extracted bus tables from the MATPOWER format to locate key elements based on their operating type.

Do I need NumPy to compute per-unit conversions for load-flow data?▼

Yes, you need NumPy arrays to compute per-unit conversions for load-flow data, as the parsing process relies on standard data fields like baseMVA, bus, gen, and branch.

Can I map non-contiguous bus numbers when analyzing power system topology?▼

You can map non-contiguous bus numbers when analyzing power system topology by applying utilities designed to handle MATPOWER-formatted bus data and identify key grid elements.

Does this approach work with gencost data and per-unit system guidance?▼

Yes, this approach works with gencost data and per-unit system guidance, supporting standard MATPOWER format fields to compute basic topology and system loads.

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