power-flow-data

v0.1.0

Power system network data formats and topology. Use when parsing bus, generator, and branch data for power flow analysis.

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Install the skill "power-flow-data" (wu-uk/energy-ac-optimal-power-flow-power-flow-data) from ClawHub.
Skill page: https://clawhub.ai/wu-uk/energy-ac-optimal-power-flow-power-flow-data
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Purpose & Capability
Name and description (power-flow data handling) match the SKILL.md content: examples and helper functions for reading MATPOWER/PGLib JSON network files. No unrelated credentials, binaries, or installs are requested.
Instruction Scope
Runtime instructions are limited to reading and parsing network JSON, computing summaries, and interpreting bus/gen/branch arrays. The guide does not ask the agent to read unrelated files, access environment secrets, or transmit data to external endpoints.
Install Mechanism
No install spec and no code files — the skill is instruction-only, so nothing is written to disk or downloaded during installation.
Credentials
The skill declares no required environment variables or credentials; the examples access only local files (e.g., 'network.json') which is appropriate for the purpose.
Persistence & Privilege
always is false and the skill does not request persistent/system-wide changes or access to other skills' configurations. Autonomous invocation is allowed, which is the platform default and is not combined with other red flags.
Assessment
This skill appears safe and self-contained for parsing MATPOWER/PGLib JSON network files. Before installing, confirm you will only point it at trusted network JSON files (loading unknown large JSON can expose bugs or malicious payloads). For very large networks consider streaming parsers or chunked processing to avoid high memory use. Validate that files contain the expected keys (baseMVA, bus, gen, branch, etc.) to prevent runtime errors.

Like a lobster shell, security has layers — review code before you run it.

latestvk9799ac45c6q20v4175htr01dn84w5j5
71downloads
0stars
1versions
Updated 1w ago
v0.1.0
MIT-0

Power Flow Data Guide

Network data follows the MATPOWER format, a standard for power system test cases. The data comes from the PGLib-OPF benchmark library (github.com/power-grid-lib/pglib-opf).

⚠️ Important: Handling Large Network Files

Network JSON files can be very large (100K+ lines for realistic grids). Never read line-by-line with sed, head, or similar tools — this wastes time and context.

Always use Python's JSON parser directly:

import json

# This is fast even for multi-MB files
with open('network.json') as f:
    data = json.load(f)

# Quick summary (do this first!)
print(f"Buses: {len(data['bus'])}")
print(f"Generators: {len(data['gen'])}")
print(f"Branches: {len(data['branch'])}")
print(f"Total load: {sum(b[2] for b in data['bus']):.1f} MW")

Quick file size check (if needed):

wc -l network.json   # Line count
du -h network.json   # File size

Network Topology Concepts

Bus Types

Power system buses are classified by what is specified vs. solved:

TypeCodeSpecifiedSolvedDescription
Slack3V, θ=0P, QReference bus, balances power
PV2P, VQ, θGenerator bus with voltage control
PQ1P, QV, θLoad bus

Per-Unit System

All electrical quantities normalized to base values:

baseMVA = 100  # Typical base power

# Conversions
P_pu = P_MW / baseMVA
Q_pu = Q_MVAr / baseMVA
S_pu = S_MVA / baseMVA

Loading Network Data

import json
import numpy as np

def load_network(filepath):
    """Load network data from JSON."""
    with open(filepath) as f:
        data = json.load(f)

    return {
        'baseMVA': data['baseMVA'],
        'bus': np.array(data['bus']),
        'gen': np.array(data['gen']),
        'branch': np.array(data['branch']),
        'gencost': np.array(data['gencost']),
        'reserve_capacity': np.array(data['reserve_capacity']),  # MW per generator
        'reserve_requirement': data['reserve_requirement']       # MW total
    }

Reserve Data

Network files may include operating reserve parameters:

FieldTypeDescription
reserve_capacityarrayMaximum reserve each generator can provide (MW)
reserve_requirementfloatMinimum total system reserves required (MW)
reserve_capacity = np.array(data['reserve_capacity'])  # r_bar per generator
reserve_requirement = data['reserve_requirement']      # R: system requirement

Bus Number Mapping

Power system bus numbers may not be contiguous. Always create a mapping:

# Create mapping: bus_number -> 0-indexed position
bus_num_to_idx = {int(buses[i, 0]): i for i in range(n_bus)}

# Map generator to bus index
gen_bus = [bus_num_to_idx[int(g[0])] for g in gens]

Identifying Bus Connections

def get_generators_at_bus(gens, bus_idx, bus_num_to_idx):
    """Find which generators connect to a bus (0-indexed)."""
    gen_indices = []
    for i, gen in enumerate(gens):
        gen_bus = bus_num_to_idx[int(gen[0])]  # Use mapping
        if gen_bus == bus_idx:
            gen_indices.append(i)
    return gen_indices

def find_slack_bus(buses):
    """Find the slack bus index (0-indexed)."""
    for i, bus in enumerate(buses):
        if bus[1] == 3:  # Type 3 = slack
            return i
    return None

Branch Data Interpretation

Each branch represents a transmission line or transformer:

def get_branch_info(branch, bus_num_to_idx):
    """Extract branch parameters."""
    return {
        'from_bus': bus_num_to_idx[int(branch[0])],  # Use mapping
        'to_bus': bus_num_to_idx[int(branch[1])],    # Use mapping
        'resistance': branch[2],          # R in pu
        'reactance': branch[3],           # X in pu
        'susceptance': branch[4],         # B in pu (line charging)
        'rating': branch[5],              # MVA limit
        'in_service': branch[10] == 1
    }

Computing Total Load

def total_load(buses):
    """Calculate total system load in MW."""
    return sum(bus[2] for bus in buses)  # Column 2 = Pd

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