mlsanityData to 7 Oct 2026

Open Power System Data - Frictionless data for electricity system modelling

arXiv 1812.10405 ↗First posted 10 Dec 2018cs.CYcited by 16

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Abstract (arXiv)

The quality of electricity system modelling heavily depends on the input data used. Although a lot of data is publicly available, it is often dispersed, tedious to process and partly contains errors. We argue that a central provision of input data for modelling has the character of a public good: it reduces overall societal costs for quantitative energy research as redundant work is avoided, and it improves transparency and reproducibility in electricity system modelling. This paper describes the Open Power System Data platform that aims at realising the efficiency and quality gains of centralised data provision by collecting, checking, processing, aggregating, documenting and publishing data required by most modellers. We conclude that the platform can provide substantial benefits to energy system analysis by raising efficiency of data pre-processing, providing a method for making data pre-processing for energy system modelling traceable, flexible and reproducible and improving the quality of original data published by data providers.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Dec 2018.

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Citing papers per year: 2021: 2; 2022: 3; 2023: 2; 2024: 1; 2025: 2; 2026: 6.

16 papers.

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  1. 2025Explainable time-series forecasting with sampling-free SHAP for Transformerscited by 2
  2. 2021Label Assistant: A Workflow for Assisted Data Annotation in Image Segmentation Taskscited by 1
  3. 2022Sampling Strategies for Static Powergrid Modelscited by 1
  4. 2022EasyMLServe: Easy Deployment of REST Machine Learning Servicescited by 1
  5. 2023Renewable energy management in smart home environment via forecast embedded scheduling based on Recurrent Trend Predictive Neural Networkcited by 1
  6. 2023Variational Elliptical Processescited by 1
  7. 2026Spectral Adaptive Conformal Prediction for Structured Non-Exchangeable Datacited by 1
  8. 2021Smart Data Representations: Impact on the Accuracy of Deep Neural Networkscited by 0
  9. 2022Unsupervised energy disaggregation via convolutional sparse codingcited by 0
  10. 2024AutoPQ: Automating Quantile estimation from Point forecasts in the context of sustainabilitycited by 0
  11. 2025Revealing the empirical flexibility of gas units through deep clusteringcited by 0
  12. 2026A Multimodal Dataset for Large Language Model Applications in the Energy Domaincited by 0
4 more
  1. 2026Automated Extraction of Techno-Economic Data from 76,000 Energy System Studiescited by 0
  2. 2026SPECTRA: State-Space Exogenous Context and Temporal-Frequency Resolution Architecture for Probabilistic Energy Forecastingcited by 0
  3. 2026Ensemble Complexity in Photovoltaic Forecastingcited by 0
  4. 2026The Operational Value of Spatial Dependence in Renewable Forecast Scenarios for Single-Period Economic Dispatch: A Controlled Ablation Studycited by 0