PowerIO

PowerIO parses power system data into typed Rust models. Readers cover balanced transmission cases, multiconductor distribution cases, display files, and directory datasets. Writers, matrix builders, package tools, and problem instance builders consume those models.

Writing a case back to the format it was read from returns the original file bytes whenever the reader kept them. Converting to a different format writes what the target format can hold and reports every dropped field in Conversion::warnings.

.pio.json saves a parsed model together with the record of how it was parsed: schema versions, the source file and row each element came from, parser warnings, validation results, and optional operating points. Files for other tools stay in the format the tool reads: MATPOWER, PSS/E, OpenDSS, or any other supported format.

The Rust workspace also builds the command line interface, the Python package, and the C ABI. PowerIO.jl uses the C ABI.

Formats

Supported formats:

• MATPOWER .m
• PSS/E .raw revisions 33, 34, and 35
• PowerWorld .aux, plus read only .pwb binary cases; .pwd display files parse through the separate display API. Behavior and limits are in the format fidelity guide.
• GE PSLF .epc power flow cases
• PowerModels.jl network data JSON
• egret ModelData JSON
• pandapower pandapowerNet JSON
• PyPSA static CSV folders
• ARPA-E GO Competition Challenge 3 JSON input data
• surge .surge.json
• DeepMind OPFData dataset JSON from the published FullTop and N-1 datasets (all grid sizes use the same reader)
• GridFM .parquet

Distribution networks are supported in wire coordinates via powerio-dist:

• OpenDSS .dss
• PowerModelsDistribution.jl ENGINEERING data JSON
• The (draft) BMOPF JSON spec and schema of the IEEE BMOPF task force .json

If a required format is missing, open an issue with a sample file and its specification or submit a reader or writer.

Packages

Each workspace crate owns one layer:

powerio          # parser, Network model, source retaining writers, converters
powerio-matrix   # generic sparse matrices, sensitivity factors, graph projections
powerio-prob     # complete problem instances; optional matrix projections
powerio-dist     # multiconductor distribution model, dss/PMD/BMOPF converters
powerio-pkg      # .pio.json document metadata and model JSON
powerio-cli      # the `powerio` command and ratatui TUI
powerio-py       # PyO3 extension for the Python `powerio` package
powerio-capi     # C ABI for C, C++, Julia, and other foreign function interfaces
PowerIO.jl       # Julia bindings over the C ABI

The powerio Rust crate keeps parsing and conversion separate from matrix, TUI, and data frame dependencies. The Python package has no required third party packages; matrix and graph helpers use optional extras.

Docs site: https://powerio.dev. Language API map: languages guide.

Install

cargo add powerio
cargo add powerio-matrix
cargo add powerio-prob
cargo install powerio-cli

pip install powerio
pip install 'powerio[all]'     # scipy, numpy, networkx, polars extras
pip install 'powerio[gridfm]'  # polars for Parquet inspection
pip install 'powerio[pandas]'  # pandas, pyarrow compatibility reads (Python 3.10+)

julia -e 'using Pkg; Pkg.add(url="https://github.com/eigenergy/PowerIO.jl")'

Use

Rust

use powerio::{TargetFormat, parse_file};

let parsed = parse_file("case14.m", None)?;
let net = parsed.network;
let conv = net.to_format(TargetFormat::PowerModelsJson)?;

for warning in &conv.warnings {
    eprintln!("conversion warning: {warning}");
}

std::fs::write("case14.json", conv.text)?;

Python

import powerio as pio

case = pio.parse_file("case9.m")
bprime = case.bprime()            # MATPOWER Bp, scipy.sparse, needs powerio[matrix]
display = pio.parse_display_file("case.pwd")
raw, warnings = pio.convert_file("case9.m", "psse")

Julia

using PowerIO

case = parse_file("case9.m")
text = to_matpower(case)
json, warnings = to_format(case, "powermodels-json")

Command line interface (CLI)

powerio convert tests/data/case14.m --to psse35 -o case14.raw
powerio convert tests/data/case14.m --to pandapower-json -o case14.pp.json
powerio convert tests/data/case14.m --to pypsa-csv -o pypsa_case
powerio convert pypsa_case --from pypsa-csv --to matpower -o case14.m
powerio convert case.epc --from pslf --to matpower -o case.m
powerio convert case.surge.json --from surge-json --to matpower -o case.m
powerio convert goc3_case.json --from goc3-json --to matpower -o case.m
powerio convert example_0.json --from opfdata-json --to matpower -o solved_case.m
powerio package tests/data/case14.m -o case14.pio.json
powerio package goc3_case.json --from goc3-json -o goc3_case.pio.json
powerio verify tests/data/case30.m --kind bdoubleprime
powerio dcopf tests/data/case30.m -o out
powerio sensitivities tests/data/case30.m -o out --solver auto --drop-tolerance 1e-10
powerio gridfm tests/data/case14.m -o out
powerio

Features

Current Format Fidelity

Every network reader lowers to Network. The table separates writing back to the original file type from converting to a different file type.

PowerWorld .pwd carries display data rather than a network case, so it is outside this conversion table and uses parse_display_file / parse_display_bytes. The decoded vintages and per field evidence are maintainer notes at powerio/src/format/powerworld/FORMAT.md.

The distribution matrix (dss, PMD JSON, BMOPF JSON, per fixture) is generated under powerio-dist/docs/. Vendored test data keeps its own licenses next to the fixtures under tests/data/dist/.

Known limits for every format are documented in the format fidelity guide.

Matrices

powerio-matrix derives an IndexedNetwork with dense bus indices and builds:

• MATPOWER Bp/Bpp FDPF matrices
• DC bus susceptance matrix L = A diag(b) A^T and flow map matrices
• Nodal admittance matrix
• LACPF block matrix
• Signed incidence matrix
• PTDF and LODF sensitivity matrices, with dense and iterative solver paths
• Streamed CLI PTDF/LODF writes for iterative sensitivity exports
• Adjacency matrix and petgraph graph output

powerio-prob builds matrix free problem instances: DC OPF and AC OPF input data plus the GOC3 SCOPF instance. Its optional matrix feature adds sparse projections and DC OPF Matrix Market bundles.

Current conventions for signs, taps, phase shifts, per unit scaling, reference buses, and line parameters are documented in the matrices guide.

Normalized Form

Network::to_normalized returns a derived solver view:

• powers use per unit;
• voltage phase angles use radians;
• inactive elements are removed;
• tap == 0 becomes 1;
• surviving buses keep their source bus IDs;
• bus types reflect generator placement and reference buses.

The normalized copy carries no retained source text, so writing it emits the derived model rather than the original file.

Python exposes the normalized form as case.to_normalized(), the C ABI as pio_normalize, and Julia as to_normalized(case).

C ABI

powerio-capi exposes parse, query, conversion, JSON transport, normalization, .pio.json document handles, and numeric table extraction through pio_* functions. The public header is powerio-capi/include/powerio.h. Build with --features arrow to enable pio_to_arrow over the Arrow C Data Interface, and add --features matrix for sparse matrix COO tables. Matrix Arrow ABI v1 is COO plus explicit matrix_bus and matrix_branch axis map tables; language bindings assemble native sparse matrix types on their side. The optional prob feature exposes matrix free SCOPF problem instances.

PowerAgent

The optional MCP server exposes conversion, saving, summaries, parsing, normalization, matrix outputs, and display data.

pip install 'powerio[mcp]'
powerio-mcp

MCP clients can keep a case in .pio.json document JSON through the package transport:

parsed = parse(path="case9.m", transport="package")
pkg = parsed["package_json"]
summary(package_json=pkg)
matrix("bprime", package_json=pkg)
save(out_path="case9.raw", to_format="psse", package_json=pkg)
diagnostics(pkg)

PowerMCP bundles these tools with simulator servers and bridge tools.

.pio.json documents

.pio.json documents carry one balanced or multiconductor model payload with metadata: provenance, source maps, diagnostics, validation, summaries, lowering history, optional derived metadata, optional operating_points, and optional study commits. A GO Challenge 3 document stores the static first interval in model and the full replayable time series in operating_points; materializing one point returns a static document with the updates applied and the series cleared.

Rust uses powerio_pkg::NetworkPackage, Python uses the powerio.Package class, the C ABI uses pio_package_*, and the CLI writes documents with powerio package.

GridFM

The gridfm command writes Parquet datasets used by the LF Energy GridFM project:

powerio gridfm <case> -o <dir>

The command writes the tables consumed by gridfm-datakit and gridfm-graphkit under <dir>/<case>/raw/. Compatible cases can be stacked by scenario ID.

read_gridfm_dataset in powerio-matrix and pio.read_gridfm in Python reconstruct a Network from a dataset. The reconstructed network can be written to any supported balanced case format:

powerio convert out/case14/raw --from gridfm --to matpower -o case14.m

The --from gridfm path is lossy. The format fidelity guide lists the recovered fields and warnings.

Validation

The Rust test suite covers parsers, writers, format conversion, matrix builders, and normalization; the C ABI crate carries its own tests, and pytest covers the Python bindings. The benchmark validation suite compares selected outputs against PowerModels.jl, egret, ExaPowerIO.jl, and pandapower, and imports PowerIO's PyPSA CSV folders with PyPSA. Install the oracle stack from benchmarks/requirements.txt into the same Python 3.11+ venv that holds the local powerio wheel.

cargo fmt --all --check
cargo test
cargo test -p powerio-capi
bash scripts/ci-clippy.sh
pytest python/tests
bash benchmarks/run_validation.sh

Benchmark method, environment, and current tables are documented in the performance guide.

License

PowerIO is distributed under either of:

• Apache License, Version 2.0
• MIT license