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|A social network off the grid (real repo at https://gitlab.com/staltz/manyverse)|
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|PyPSA-Eur: A Sector-Coupled Open Optimisation Model of the European Energy System|
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|MatConvNet implementation for incorporating a 3D Morphable Model (3DMM) into a Spatial Transformer Network (STN)|
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|Torch7 implementation of Grid LSTM as described here: http://arxiv.org/pdf/1507.01526v2.pdf|
|Grid Cells||128||5 years ago||apache-2.0||Python|
|Implementation of the supervised learning experiments in Vector-based navigation using grid-like representations in artificial agents, as published at https://www.nature.com/articles/s41586-018-0102-6|
|Tgrid||112||6||15 days ago||160||November 21, 2023||mit||TypeScript|
|TypeScript Grid Computing Framework supporting RFC (Remote Function Call)|
|Zos||73||11||19 hours ago||187||May 11, 2022||53||apache-2.0||Go|
|Autonomous operating system|
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|Implementing YOLO using ResNet as the feature extraction network|
|Pysster||62||4 years ago||10||October 22, 2019||2||mit||Python|
|pysster: Learning Sequence And Structure Motifs In Biological Sequences Using Convolutional Neural Networks|
PyPSA-Eur is an open model dataset of the European energy system at the transmission network level that covers the full ENTSO-E area. The model is suitable both for operational studies and generation and transmission expansion planning studies. The continental scope and highly resolved spatial scale enables a proper description of the long-range smoothing effects for renewable power generation and their varying resource availability.
The model is described in the documentation and in the paper PyPSA-Eur: An Open Optimisation Model of the European Transmission System, 2018, arXiv:1806.01613. The model building routines are defined through a snakemake workflow. Please see the documentation for installation instructions and other useful information about the snakemake workflow. The model is designed to be imported into the open toolbox PyPSA.
WARNING: PyPSA-Eur is under active development and has several limitations which you should understand before using the model. The github repository issues collect known topics we are working on (please feel free to help or make suggestions). The documentation remains somewhat patchy. You can find showcases of the model's capabilities in the Joule paper The potential role of a hydrogen network in Europe, another paper in Joule with a description of the industry sector, or in a 2021 presentation at EMP-E. We do not recommend to use the full resolution network model for simulations. At high granularity the assignment of loads and generators to the nearest network node may not be a correct assumption, depending on the topology of the underlying distribution grid, and local grid bottlenecks may cause unrealistic load-shedding or generator curtailment. We recommend to cluster the network to a couple of hundred nodes to remove these local inconsistencies. See the discussion in Section 3.4 "Model validation" of the paper.
The dataset consists of:
A sector-coupled extension adds demand and supply for the following sectors: transport, space and water heating, biomass, industry and industrial feedstocks, agriculture, forestry and fishing. This completes the energy system and includes all greenhouse gas emitters except waste management and land use.
This diagram gives an overview of the sectors and the links between them:
Each of these sectors is built up on the transmission network nodes from PyPSA-Eur:
For computational reasons the model is usually clustered down to 50-200 nodes.
Already-built versions of the model can be found in the accompanying Zenodo repository.
We strongly welcome anyone interested in contributing to this project. If you have any ideas, suggestions or encounter problems, feel invited to file issues or make pull requests on GitHub.