energy-py-linear

Optimizing energy systems using mixed integer linear programming.
https://github.com/ADGEfficiency/energy-py-linear

Category: Energy Systems
Sub Category: Energy System Modeling Frameworks

Keywords

batteries electric-vehicles energy optimization python renewable-energy solar wind

Last synced: about 2 hours ago
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Repository metadata

Optimize energy assets using mixed-integer linear programming

• Host: GitHub
• URL: https://github.com/ADGEfficiency/energy-py-linear
• Owner: ADGEfficiency
• License: gpl-3.0
• Created: 2019-01-15T21:59:41.000Z (over 6 years ago)
• Default Branch: main
• Last Pushed: 2025-03-30T09:36:42.000Z (about 1 month ago)
• Last Synced: 2025-04-17T21:21:54.186Z (14 days ago)
• Topics: batteries, electric-vehicles, energy, optimization, python, renewable-energy, solar, wind
• Language: Python
• Homepage:
• Size: 5.51 MB
• Stars: 93
• Watchers: 5
• Forks: 28
• Open Issues: 3
• Releases: 9
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

README.md

$ pip install energypylinear

import energypylinear as epl

#  2.0 MW, 4.0 MWh battery
asset = epl.Battery(
    power_mw=2,
    capacity_mwh=4,
    efficiency_pct=0.9,
    # different electricity prices for each interval
    # length of electricity_prices is the length of the simulation
    electricity_prices=[100.0, 50, 200, -100, 0, 200, 100, -100],
    # a constant value for each interval
    export_electricity_prices=40,
)

simulation = asset.optimize()

import energypylinear as epl

assets = [
    #  2.0 MW, 4.0 MWh battery
    epl.Battery(power_mw=2.0, capacity_mwh=4.0),
    #  30 MW open cycle generator
    epl.CHP(
        electric_power_max_mw=100, electric_power_min_mw=30, electric_efficiency_pct=0.4
    ),
    #  2 EV chargers & 4 charge events
    epl.EVs(
        chargers_power_mw=[100, 100],
        charge_events_capacity_mwh=[50, 100, 30, 40],
        charge_events=[
            [1, 0, 0, 0, 0],
            [0, 1, 1, 1, 0],
            [0, 0, 0, 1, 1],
            [0, 1, 0, 0, 0],
        ],
    ),
    #  natural gas boiler to generate high temperature heat
    epl.Boiler(),
    #  valve to generate low temperature heat from high temperature heat
    epl.Valve(),
]

site = epl.Site(
    assets=assets,
    # length of energy prices is the length of the simulation
    electricity_prices=[100, 50, 200, -100, 0],
    # these should match the length of the export_electricity_prices
    # if they don't, they will be repeated or cut to match the length of electricity_prices
    high_temperature_load_mwh=[105, 110, 120, 110, 105],
    low_temperature_load_mwh=[105, 110, 120, 110, 105],
)

simulation = site.optimize()

$ make test

Owner metadata

• Name: Adam Green
• Login: ADGEfficiency
• Email:
• Kind: user
• Description:
• Website: adgefficiency.com
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• Twitter:
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• Repositories: 78
• Last ynced at: 2024-06-11T15:43:25.030Z
• Profile URL: https://github.com/ADGEfficiency

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Last Year

• Watch event: 5
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Committers metadata

Last synced: about 18 hours ago

Committer domains:

• ip-172-31-22-172.ap-southeast-2.compute.internal: 1
• alush.co.uk: 1
• adgefficiency.com: 1

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Dependencies

Score: 6.173786103901937