lineoptim 1.1.0

A line optimization package for electrical conductors.

LineOptim - Electric Power Line Parameter Optimization

lineoptim is an open-source package for electric power line simulation and optimization. It provides the tools for simulating, visualizing and optimizing electric power lines and is designed to scale with larger and nested networks.

Features

• Line Simulation: Simulate electric power lines with multiple loads and sub-lines. Get voltage drop, current power at any point in the line.
• Optimization: Optimize electric power lines for wanted voltage drop and optimal conductor size
• Visualization: Visualize electric power lines and their parameters

Installation

pip install lineoptim

Usage

import lineoptim as lo
import torch

# Create a line
v_nominal = torch.tensor([400.0, 400.0, 400.0])  # nominal voltage

line_params = {
    "name": "Main power line 1",
    "position": 0,
    "resistivity": torch.tensor([0.12, 0.12, 0.12]),  # resistivity,
    "reactance": torch.tensor([0.0, 0.0, 0.0]),
    "v_nominal": v_nominal,
}

main_line = lo.Line(**line_params)

main_line.add("Load 1", 100, active_power=20000, v_nominal=v_nominal, power_factor=0.9)
main_line.add("Load 2", 200, active_power=20000, v_nominal=v_nominal, power_factor=0.9)
main_line.add("Load 3", 300, active_power=20000, v_nominal=v_nominal, power_factor=0.9)

sub_line = lo.Line('Sub-line 1', 400, v_nominal=v_nominal, resistivity=torch.tensor([0.145, 0.145, 0.145]))

main_line.add(**sub_line.dict())

network = lo.Network()  # create network
network.add(main_line)  # add line to network

network.optimize(epochs=200, lr=0.01, max_v_drop=5.0)  # optimize network on 5% voltage drop at line ends

main_line.save_to_json('resources/example_line.json')  # save line configuration as json

Contributing

Contributions are welcome! For feature requests, bug reports or submitting pull requests, please use the GitHub Issue Tracker.

License

lineoptim is licensed under the open source MIT Licence