Description
Submitting Author: Jinning Wang (@jinningwang)
Package Name: AMS
One-Line Description of Package: Power system dispatch modeling and dispatch-dynamic co-simulation.
Repository Link (if existing): https://github.com/CURENT/ams
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Description
As part of CURENT Large-scale Testbed platform, AMS serves as power system production cost modeling. Our framework offers a modularized approach that seamlessly incorporates dynamics, enhancing traditional dispatch modeling methods. We create a versatile solution that bridges the gap between device-level and system-level models. The tool is developed to be extensible, scalable, compatible, and interoperable.
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Scope
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Check out our package scope page to learn more about our scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):- Data retrieval
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If your package is associated with an existing community please check below:
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Pangeo: My package adheres to the Pangeo standards listed in the pyOpenSci peer review guidebook
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Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:
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Who is the target audience and what are the scientific applications of this package?
Power system researchers and engineers. -
Are there other Python packages that accomplish similar things? If so, how does yours differ?
There are some Python packages cover part of our functions: PYPOWER, pandapower, and PyPSA.
Compared to existing tools that focus on fixed power system optimization problems, our package AMS enables customizing formulations thus enable rapid prototyping for renewables integration.
Additionally, with the built-in interface with dynamic simulator ANDES, AMS allows native interoperation between dynamics and dispatch, which significantly relieves the researchers manual efforts when conducting power system simulations. -
Any other questions or issues we should be aware of:
I also curate a list that collects open-source libraries for power system analysis, https://github.com/jinningwang/best-of-ps
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