Vessim is a 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.
Use Vessim to:
- Test carbon-aware applications: Develop software that automatically reduces energy consumption when the grid runs on fossil fuels and increases activity when renewable energy is abundant.
- Optimize energy infrastructure: Experiment with adding solar panels, wind turbines, or batteries to see how they would affect your energy costs and carbon emissions.
- Plan for extreme events: Simulate power outages or renewable energy fluctuations to understand risks and test backup strategies.
- Validate software changes: Test how new deployments or configuration changes will affect energy consumption before rolling them out to production.
Vessim can run simulations faster than real-time, includes historical datasets for realistic scenarios, and can simulate multiple microgrids in parallel. You can test scenarios using historical data or connect real applications and hardware to simulated energy systems.
Check out the official documentation!
The scenario below simulates a microgrid consisting of a simulated computing system (which consistently draws 700W), 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 in a CSV file.
import vessim as vs
environment = vs.Environment(sim_start="2022-06-15", step_size=300) # 5 minute step size
microgrid = environment.add_microgrid(
name="datacenter",
actors=[
vs.Actor(name="server", signal=vs.ConstantSignal(value=-700)), # negative = consumes power
vs.Actor(name="solar_panel", signal=vs.Trace.load("solcast2022_global", column="Berlin", params={"scale": 5000})), # 5kW maximum
],
storage=vs.SimpleBattery(capacity=100),
)
# Write results to CSV
monitor = vs.Monitor([microgrid], outdir="./results")
environment.add_controller(monitor)
environment.run(until=24 * 3600) # 24hYou 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, e.g. via:
uv pip install -e ".[dev,sil]"
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.
- Vessim X Vidur: We are working on integrating Vessim into the LLM simulator Vidur.
- Software-in-the-loop API: We will soon release a new API for SiL simulations with new examples and better documentation.
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.
If you use Vessim in your research, please cite our paper:
- Philipp Wiesner, Ilja Behnke, Paul Kilian, Marvin Steinke, and Odej Kao. "Vessim: A Testbed for Carbon-Aware Applications and Systems." 3rd Workshop on Sustainable Computer Systems (HotCarbon). 2024.
For details in Vessim's software-in-the-loop simulation methodology, refer to our journal paper:
- Philipp Wiesner, Marvin Steinke, Henrik Nickel, Yazan Kitana, and Odej Kao. "Software-in-the-Loop Simulation for Developing and Testing Carbon-Aware Applications." Software: Practice and Experience, 53 (12). 2023.
For BibTeX citations and more related papers, please refer to the documentation.