energy-py-linear

A Python library for optimizing energy assets with mixed-integer linear programming:

• electric batteries,
• combined heat & power (CHP) generators,
• electric vehicle smart charging,
• heat pumps,
• renewable (wind & solar) generators.

Assets & sites can be optimized to either maximize profit or minimize carbon emissions, or a user defined custom objective function.

Energy balances are performed on electricity, high, and low temperature heat.

Setup

Requires Python 3.10+:

$ pip install energypylinear

Quick Start

Asset API

The asset API allows optimizing a single asset at once:

import energypylinear as epl

#  2.0 MW, 4.0 MWh battery
asset = epl.Battery(
    power_mw=2,
    capacity_mwh=4,
    efficiency_pct=0.9,
  electricity_prices=[100.0, 50, 200, -100, 0, 200, 100, -100],
  export_electricity_prices=40
)

simulation = asset.optimize()

Site API

The site API allows optimizing multiple assets together:

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,
  electricity_prices=[100, 50, 200, -100, 0],
  high_temperature_load_mwh=[105, 110, 120, 110, 105],
  low_temperature_load_mwh=[105, 110, 120, 110, 105]
)

simulation = site.optimize()