energy-py-linear

Documentation: energypylinear.adgefficiency.com

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 can be optimized to either maximize profit or minimize carbon emissions, or for user defined custom objective functions. Custom constraints can be used to further constrain asset behaviour.

A site is a collection of assets that can be optimized together. Sites can use custom objectives and constraints.

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

Setup

Requires Python 3.11 or 3.12:

shell-session $ pip install energypylinear

Quick Start

Asset API

The asset API allows optimizing a single asset at once:

```python import energypylinear as epl

2.0 MW, 4.0 MWh battery

asset = epl.Battery( powermw=2, capacitymwh=4, efficiencypct=0.9, # different electricity prices for each interval # length of electricityprices is the length of the simulation electricityprices=[100.0, 50, 200, -100, 0, 200, 100, -100], # a constant value for each interval exportelectricity_prices=40, )

simulation = asset.optimize() ```

Site API

The site API allows optimizing multiple assets together:

```python import energypylinear as epl

assets = [ # 2.0 MW, 4.0 MWh battery epl.Battery(powermw=2.0, capacitymwh=4.0), # 30 MW open cycle generator epl.CHP( electricpowermaxmw=100, electricpowerminmw=30, electricefficiencypct=0.4 ), # 2 EV chargers & 4 charge events epl.EVs( chargerspowermw=[100, 100], chargeeventscapacitymwh=[50, 100, 30, 40], chargeevents=[ [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 electricityprices=[100, 50, 200, -100, 0], # these should match the length of the exportelectricityprices # if they don't, they will be repeated or cut to match the length of electricityprices hightemperatureloadmwh=[105, 110, 120, 110, 105], lowtemperatureloadmwh=[105, 110, 120, 110, 105], )

simulation = site.optimize() ```

Documentation

See more asset types & use cases in the documentation.

Test

shell $ make test