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Systems","sub_category":"Energy System Modeling Frameworks","monthly_downloads":286,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"#################################\nExerPy: Exergy Analysis in Python\n#################################\n\nExerPy is a Python library designed to perform detailed exergy analysis of\nenergy conversion systems. It builds on the exergy analysis methodology\nimplemented in TESPy, while extending its capabilities to seamlessly integrate\nwith simulation tools such as Ebsilon Professional, Aspen Plus, and TESPy itself.\nExerPy enables engineers and researchers to identify inefficiencies and optimize\nthe performance of thermodynamic systems through automated workflows and\nconsistent data handling.\n\nWith its advanced features, ExerPy calculates both physical and chemical exergy,\nallowing users to analyze both individual components and entire systems. This\nhelps to identify where and why exergy losses occur, facilitating strategies to improve\nefficiency, reduce costs, and support sustainable energy usage.\n\n.. figure:: https://raw.githubusercontent.com/oemof/exerpy/refs/heads/main/docs/_static/images/logo_exerpy_big.svg\n    :align: center\n\n************\nKey Features\n************\n\n- **Comprehensive Exergy Analysis**: Calculate physical and chemical exergy, perform component-level and system-wide analysis.\n- **Flexible Integration**: Compatible with multiple simulation tools (Ebsilon Professional, Aspen Plus, TESPy).\n- **Advanced Component Library**: Pre-built components for common energy system elements (turbines, heat exchangers, etc.).\n- **Extensible Architecture**: Easy-to-use framework for implementing custom components and analysis methods.\n- **Robust Data Handling**: Consistent fluid property models and automated data extraction from simulation tools.\n- **Open Source**: MIT licensed, free for academic and commercial use.\n\n***************\nGetting Started\n***************\n\n============\nInstallation\n============\nYou can install the latest version of ExerPy using pip:\n\n.. code:: bash\n\n    pip install exerpy\n\n===================\nQuick Start Example\n===================\nHere's a simple example how to perform an exergy analysis using ExerPy:\n\nCustom json\n-----------\n\n.. code:: python\n\n    from exerpy import ExergyAnalysis\n\n    model_path = 'my_model.json'\n\n    ean = ExergyAnalysis.from_json(model_path, chemExLib='Ahrendts')\n\n    fuel = {\"inputs\": ['Fuel'], \"outputs\": []}\n    product = {\"inputs\": ['Power'], \"outputs\": []}\n\n    ean.analyse(E_F=fuel, E_P=product)\n    ean.exergy_results()\n\nExported tespy model\n--------------------\n\n.. code:: python\n\n    from exerpy import ExergyAnalysis\n\n    model_path = 'tespy_model_export.json'\n\n    ean = ExergyAnalysis.from_tespy(model_path, chemExLib='Ahrendts')\n\n    fuel = {\"inputs\": ['Fuel'], \"outputs\": []}\n    product = {\"inputs\": ['Power'], \"outputs\": []}\n\n    ean.analyse(E_F=fuel, E_P=product)\n    ean.exergy_results()\n\nYou can also use a tespy network object instead!\n\nEbsilon model\n-------------\n\n.. code:: python\n\n    from exerpy import ExergyAnalysis\n\n    model_path = 'my_model.ebs'\n\n    ean = ExergyAnalysis.from_ebsilon(model_path, chemExLib='Ahrendts')\n\n    fuel = {\"inputs\": ['Fuel'], \"outputs\": []}\n    product = {\"inputs\": ['Power'], \"outputs\": []}\n\n    ean.analyse(E_F=fuel, E_P=product)\n    ean.exergy_results()\n\nFor more detailed tutorials and examples, see the\n`online documentation \u003chttps://exerpy.readthedocs.io\u003e`__.\n\n********\nCitation\n********\n\nIf you use ExerPy in your scientific work, please consider citing it to support\nongoing development. You can cite ExerPy using the following BibTeX entry:\n\n.. code::\n\n    @software{ExerPy,\n         author = {Tomasinelli, Sergio and Witte, Francesco and Müller, Robert},\n         title = {{ExerPy}: Exergy Analysis in Python},\n         note = {Supervision: Prof. Dr.-Ing. Fontina Petrakopoulou}\n         url = {https://github.com/oemof/exerpy},\n         version = {0.0.7},\n         year = {2026}\n    }\n\n*******\nLicense\n*******\n\nMIT License\n\nCopyright (c) Sergio Tomasinelli\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["exergonomic","energy-system","cooling","heating","powerplant","process-engineering","refrigeration","thermodynamic-cycles"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/324891","html_url":"https://ost.ecosyste.ms/projects/324891"}