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Systems","sub_category":"Grid Management and Microgrid","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"\u003cp align=\"center\"\u003e\n    \u003cimg alt=\"Vessim Logo\" src=\"docs/assets/logo.png\" width=\"250\" /\u003e\n\u003c/p\u003e\n\nVessim is a **co-simulation testbed for carbon-aware systems**. \nIt allows you to simulate the interaction of computing systems with local energy systems, including renewable energy sources, energy storage, and the public grid.\nVessim can connect domain-specific simulators for power generation and batteries with real software and hardware.\n\n**Check out the [documentation](https://vessim.readthedocs.io/en/latest/)!**\n\n## What can I do with Vessim?\n\nVessim helps you to understand and optimize how your (distributed) computing system interacts with (distributed) renewable energy sources and battery storage.\n\n- **Carbon-aware applications**: Develop applications that automatically reduce their energy consumption when the grid is powered by fossil fuels, and increase activity when renewable energy is abundant.\n- **Energy system composition**: Experiment with adding solar panels, wind turbines, or batteries to see how they would affect your energy costs and carbon emissions.\n- **Plan for outages and extreme events**: Simulate power outages or renewable energy fluctuations to understand risks and test backup strategies.\n- **Quality assurance**: Apply Vessim in continuous integrating testing to validate software roll-outs in a controlled environment.\n\nVessim can run simulations faster than real-time, includes historical datasets for realistic scenarios, and can simulate multiple microgrids in parallel. \nYou can test scenarios using historical data or connect real applications and hardware to simulated energy systems.\n\n\n## Example\n\nThe scenario below simulates a microgrid consisting of a simulated computing system (drawing 700W), \na solar power plant (modelled based on a dataset provided by [Solcast](https://solcast.com/)), and a battery. \nThe *vs.CsvLogger* periodically stores the energy system state in a CSV file.\n\n```python\nimport vessim as vs\n\nenvironment = vs.Environment(sim_start=\"2022-06-15\", step_size=300)  # 5 minute step size\n\nmicrogrid = environment.add_microgrid(\n    name=\"datacenter\",\n    actors=[\n        vs.Actor(name=\"server\", signal=vs.StaticSignal(value=-700)),  # negative = consumes power\n        vs.Actor(name=\"solar_panel\", signal=vs.Trace.load(\"solcast2022_global\", column=\"Berlin\", params={\"scale\": 5000})),  # 5kW maximum\n    ],\n    storage=vs.SimpleBattery(capacity=100),\n)\n\n# Write results to CSV\nenvironment.add_controller(vs.CsvLogger(\"./results.csv\"))\n\nenvironment.run(until=24 * 3600)  # 24h simulated time\n```\n\nCheck out the [tutorials](https://vessim.readthedocs.io/en/latest/tutorials/1_basic_example/) and [`examples/`](examples/)!\n\n\n## Installation\n\nYou can install the [latest release](https://pypi.org/project/vessim/) of Vessim\nvia [pip](https://pip.pypa.io/en/stable/quickstart/):\n\n```\npip install vessim\n```\n\nIf you require software-in-the-loop (SiL) capabilities, you should additionally install the `sil` extension:\n\n```\npip install vessim[sil]\n```\n\n\n## Datasets\n\nVessim comes with ready-to-user datasets for solar irradiance and average carbon intensity provided by\n\n\u003cp float=\"left\"\u003e\n  \u003cimg src=\"docs/assets/solcast_logo.png\" width=\"120\" /\u003e\n  \u003cspan\u003e and \u003c/span\u003e\n  \u003cimg src=\"docs/assets/watttime_logo.png\" width=\"120\" /\u003e\n\u003c/p\u003e\n\nWe're working on documentation on how to include custom datasets for your simulations.\n\n\n## Publications\n\nIf you use Vessim in your research, please cite our paper:\n\n- Philipp Wiesner, Ilja Behnke, Paul Kilian, Marvin Steinke, and Odej Kao. \"[Vessim: A Testbed for Carbon-Aware Applications and 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