energy-py-linear

combined heat & power (CHP) generators,
electric vehicle smart charging.

Assets can be optimized to either maximize profit or minimize carbon emissions.

Energy balances are performed on electricity, high & 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.

We can optimize an electric battery operating in wholesale price arbitrage using epl.Battery:

import energypylinear as epl

#  2.0 MW, 4.0 MWh battery
asset = epl.battery.Battery(power_mw=2, capacity_mwh=4, efficiency=0.9)

results = asset.optimize(
  electricity_prices=[100.0, 50, 200, -100, 0, 200, 100, -100],
  freq_mins=60,
  initial_charge_mwh=1,
  final_charge_mwh=3
)

You can find documentation of how to optimize other assets in how-to/optimize-assets, and Python examples in energy-py-linear/examples/examples.

Site API

The site API allows optimizing multiple assets at once:

import energypylinear as epl

site = epl.Site(assets=[
  epl.Battery(power_mw=2.0, capacity_mwh=4.0),
  epl.Generator(
    electric_power_max_mw=100,
    electric_power_min_mw=30,
    electric_efficiency_pct=0.4
  ),
  epl.evs.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]
      ]
=======
A Python library for optimizing energy assets with mixed-integer linear programming:

- electric batteries,
- combined heat & power (CHP) generators,
- electric vehicle smart charging.

Assets can be optimized to either maximize profit or minimize carbon emissions.  

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

## Setup

Requires Python 3.10+:

```shell
$ pip install energypylinear