Three Phase Grid Inverter logo

Three Phase Grid Inverter

Community
npuzsy
three-phase-grid-inverter

Use when working on Simulink or Simscape Electrical three-phase grid-connected inverter models, including SPWM/SVPWM, T-type or NPC three-level bridges, grid-side voltage/current waveform balance, gate routing, sector tables, and switching-state validation.

Overview

Publishernpuzsy
Repositorysimulink-power-electronics
Skill namethree-phase-grid-inverter
Stars
101
Forks
6
Bundled files
5
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by npuzsy on GitHub. Read the source before you install it.

Installation

Install the Three Phase Grid Inverter AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/npuzsy/simulink-power-electronics/tree/master/subskills/three-phase-grid-inverter
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/npuzsy/simulink-power-electronics.git /tmp/simulink-power-electronics
mkdir -p .claude/skills
cp -r /tmp/simulink-power-electronics/subskills/three-phase-grid-inverter .claude/skills/three-phase-grid-inverter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Three Phase Grid Inverter in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Three Phase Grid Inverter on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Three Phase Grid Inverter is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Three-Phase Grid Inverter

Overview

Use this active subskill for three-phase grid-connected inverter work. It contains the populated knowledge in this repository: T-type/NPC three-level SVPWM, state-vector table checks, gate mapping, From/Goto routing risks, and simulation-backed waveform validation.

Use the root simulink-power-electronics workflow first, then load this subskill when the model is in scope.

Resource Map

  • Read references/svpwm-three-level.md for T-type or NPC three-level SVPWM logic, sector handling, and gate mapping.
  • Read references/table7-state-vectors.md when auditing or rebuilding the 36 small-sector state-vector table.
  • Read references/vsg-control-notes.md for VSG (Virtual Synchronous Generator) control implementation, PI tuning experience, power calculation verification, and feedforward formulas specific to grid-connected inverters.
  • Use scripts/svpwm_diagnostics.m when MATLAB/Simulink can run and the model exposes state, gate, and voltage signals.
  • Use scripts/print_table7_state_vectors.py when a deterministic JSON or Markdown copy of the reference table is needed.
  • Also read the root ../../references/control-algorithm-debugging.md for general control algorithm debugging methodology and signal-tracing procedures.

In Scope

  • three-phase grid-connected inverters
  • two-level inverter diagnostics when the same gate-routing and waveform evidence workflow applies
  • T-type or NPC three-level bridges
  • SPWM, SVPWM, and closely related discontinuous PWM checks
  • phase/line voltage balance, current balance, DC offset, and phase-sum checks
  • controller-to-plant gate ordering and legal switching states
  • VSG (Virtual Synchronous Generator) grid-forming inverter control
  • PI controller tuning, anti-windup mechanisms, and feedforward design
  • S-Function based control algorithm implementation and debugging
  • Power calculation verification (P/Q) with Clarke/Park transform coefficients

Out Of Scope

Use a different subskill or the root workflow for:

  • motor-drive torque/speed control
  • DC-DC converter regulation
  • rectifier/PFC-specific behavior
  • battery or BMS modeling
  • HVDC/FACTS studies
  • MMC or flying-capacitor balancing not covered by the existing three-level inverter notes

Workflow Additions

  1. Confirm grid-side reference frame, phase sequence, measurement polarity, and analysis window before interpreting waveforms.
  2. Identify the active modulation path: SPWM, SVPWM, disabled reference path, or commented subsystem.
  3. Log controller state vectors, final gate vectors, plant-side gate inputs, and phase/line voltage or current measurements.
  4. For three-level SVPWM, compare every large sector and small sector against table7-state-vectors.md; partial sector-I checks are not enough.
  5. For T-type/NPC gate mapping, confirm the physical switch order before applying N/O/P assumptions.
  6. Validate after startup transient unless startup behavior is the target.

Evidence Checks

  • controller gate vector equals plant-side gate input
  • no illegal switch state appears in any bridge leg
  • phase and line RMS values are balanced in the selected steady-state window
  • phase sum, DC offset, and current polarity match the model objective
  • sector/state-vector counts are plausible for the modulation method and operating point

Scripts

For a conventional three-level SVPWM model with accessible logging points, add this subskill's scripts directory to the MATLAB path and call:

matlab
cfg = struct();
cfg.model = "YourModel";
cfg.svpwmSubsystem = "YourModel/SVPWM";
cfg.stateBlock = "YourModel/SVPWM/Subsystem1";
cfg.gateBlock = "YourModel/SVPWM/Subsystem3";
cfg.voltageBlocks = ["YourModel/Voltage Measurement2", "YourModel/Voltage Measurement3", "YourModel/Voltage Measurement4"];
cfg.stopTime = "0.10";
report = svpwm_diagnostics(cfg);

For the bundled table reference:

bash
python3 subskills/three-phase-grid-inverter/scripts/print_table7_state_vectors.py --format markdown
python3 subskills/three-phase-grid-inverter/scripts/print_table7_state_vectors.py --format json

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Three Phase Grid Inverter AI skill do?

Use when working on Simulink or Simscape Electrical three-phase grid-connected inverter models, including SPWM/SVPWM, T-type or NPC three-level bridges, grid-side voltage/current waveform balance, gate routing, sector tables, and switching-state validation.

Why use Three Phase Grid Inverter on TypingMind?

Because you install it once and use it with any model. Three Phase Grid Inverter is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Three Phase Grid Inverter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/npuzsy/simulink-power-electronics/tree/master/subskills/three-phase-grid-inverter. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Three Phase Grid Inverter?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Three Phase Grid Inverter?

As many as you like. As long as a model supports skills, you can use Three Phase Grid Inverter with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Three Phase Grid Inverter AI skill free?

Yes. It is published on GitHub by npuzsy under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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