Metadata-Version: 2.1
Name: TopologySuperpositionTheorem
Version: 0.0.1
Summary: A package for efficient combinatorial topological actions power flow computation based on the extended superposition theorem for powersystems
Home-page: https://github.com/marota/Topology_Superposition_Theorem
Author: Antoine MAROT
License: Mozilla Public License 2.0 (MPL 2.0)
Description: # Topology_Superposition_Theorem
        
        This is a package for efficient combinatorial topological actions power flow computation based on the extended superposition theorem for power systems.
        
        Here is the extended superposition theroem for topological changes. The resulting powerflows is a linear combination of unitary change power flows:
        
        𝑃𝐹(𝑇)=𝛼×𝑃𝐹(𝑇𝑟𝑒𝑓)+𝛽1×𝑃𝐹(𝑇𝑟𝑒𝑓∘𝜏1)+𝛽2×𝑃𝐹(𝑇𝑟𝑒𝑓∘𝜏2)
        
        with 𝑇=𝑇𝑟𝑒𝑓∘𝜏1∘𝜏2 and 𝛼=1−𝛽1−𝛽2
        
        We have 𝑇𝑟𝑒𝑓 as the reference topology from which we apply topological changes 𝜏1 and 𝜏2 in indifferent order to reach a target topology 𝑇. Finding the betas simply stems from solving a linear system of dimension the number of considered changes. Only minimal information from individual power flow state is needed for this, without knowledge of any underlying grid properties or complete adjacency matrix.
        
        For more information, see paper (under writing) and abstract in reference folder.
        
        # Get started
        
        you can install the package from pypi
        ```
        pip install topologysuperpositiontheorem
        ```
        
        you can them run the getting started notebook to get familiar with the package
Keywords: combinatorial powerflow topology power-systems
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.8
Description-Content-Type: text/markdown
