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Vessim

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Vessim is a versatile co-simulation testbed for carbon-aware applications and systems which connects domain-specific simulators for renewable power generation and energy storage with real software and hardware.

It simulates energy systems that interact with real or simulated computing systems for:

  • Carbon-aware applications: Simulated microgrids offer real-time visibility and control via APIs, enabling the development of novel applications that interact with their energy system.
  • Energy system composition: Examine how the integration of solar panels, wind energy, or batteries would affect the energy mix of your datacenters.
  • Digital Twins: Predict future system states in carbon-aware datacenters, aid decision-making, and assess risks during extreme events like power outages.
  • Quality Assurance: Apply Vessim in continuous integrating testing or use it to validate software roll-outs in a controlled environment.

Vessim can simulate large numbers of microgrids in parallel, comes with ready-to-use datasets, can execute simulated experiments faster than real-time, and is easily extendable with new simulators of any platform through Mosaik's TCP interface.

Check out the official documentation!

Example scenario

The scenario below simulates a microgrid consisting of a simulated computing system (which consistently draws 400W), a single producer (a solar power plant who's production is modelled based on a dataset provided by Solcast), and a battery. The Monitor periodically stores the energy system state.

import vessim as vs

environment = vs.Environment(sim_start="2022-06-15")

monitor = vs.Monitor()
environment.add_microgrid(
    actors=[
        vs.ComputingSystem(nodes=[vs.MockSignal(value=400)]),
        vs.Actor(
            name="solar_panel",
            signal=vs.HistoricalSignal.load("solcast2022_global", column="Berlin")
        ),
    ],
    controllers=[monitor],
    storage=vs.SimpleBattery(capacity=100),
    step_size=60,
)

environment.run(until=24 * 3600)  # 24h
monitor.to_csv("result.csv")

Installation

You can install the latest release of Vessim via pip:

pip install vessim

If you require software-in-the-loop (SiL) capabilities, you should additionally install the sil extension:

pip install vessim[sil]

For complex scenarios that involve custom co-simulation actors we recommend cloning and editing this depository directly.

Work in progress

Our team at the Distributed and Operating Systems group at TU Berlin is actively working to improve Vessim. We are currently working on the following aspects and features:

  • Calibration: We are working on a methodology for calibrating Vessim simulations on real hardware testbeds.
  • System Advisor Model (SAM): We are working on integrating NREL's SAM as a subsystem in Vessim, allowing for better simulation of solar arrays, wind farms, and other types of renewable energy generators.
  • Battery degradation: We are working on integrating NREL's BLAST-Lite for modeling battery lifetime and degradation
  • Vessim X Flower: We are working on integrating Vessim into the federated learning framework Flower.
  • Software-in-the-loop API: We will soon release a new API for SiL simulations with new examples and better documentation.

Datasets

Vessim comes with ready-to-user datasets for solar irradiance and average carbon intensity provided by

and

We're working on documentation on how to include custom datasets for your simulations.

Publications

If you use Vessim in your research, please cite our paper:

@inproceedings{wiesner2024vessim,
    title     = {Vessim: A Testbed for Carbon-Aware Applications and Systems},
    author    = {Wiesner, Philipp and Behnke, Ilja and Kilian, Paul and Steinke, Marvin and Kao, Odej},
    booktitle = {3rd Workshop on Sustainable Computer Systems (HotCarbon)},
    year      = {2024},
}

For details in Vessim's software-in-the-loop simulation methodology, refer to our journal paper:

@article{wiesner2023sil,
    author    = {Wiesner, Philipp and Steinke, Marvin and Nickel, Henrik and Kitana, Yazan and Kao, Odej},
    title     = {Software-in-the-loop simulation for developing and testing carbon-aware applications},
    journal   = {Software: Practice and Experience},
    year      = {2023},
    volume    = {53},
    number    = {12},
    pages     = {2362-2376},
    doi       = {https://doi.org/10.1002/spe.3275}
}