Electricity Systems: Difference between revisions

add datasets
(starting dataset and tool migration)
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ML can contribute on all fronts by informing the research, deployment, and operation of electricity system technologies. Such contributions include accelerating the development of clean energy technologies, improving forecasts of demand and clean energy, improving electricity system optimization and management, and enhancing system monitoring. These contributions require a variety of ML paradigms and techniques, as well as close collaborations with the electricity industry and other experts to integrate insights from operations research, electrical engineering, physics, chemistry, the social sciences, and other fields.
 
== Readings and online courses ==
 
=== Primers on electricity systems ===
* Wood, A.J. et al., [https://www.wiley.com/en-ca/Power+Generation%2C+Operation%2C+and+Control%2C+3rd+Edition-p-9780471790556 Power Generation, Operation, and Control.] (2013)
* Kirschen,D D.S., and Strbac, G. [https://www.academia.edu/8171173/Fundamentals_of_power_system_economics Fundamentals of Power System Economics, Volume 1] (2004).
 
=== Online courses ===
 
* [https://www.coursera.org/learn/electric-power-systems Coursera Electric Power Systems online course]
 
=== Primers on specific sub-topics ===
== Community ==
 
=== Journals andMajor conferences ===
 
* [https://pes-gm.org/2020/ IEEE Power & Energy Society General Meeting]
* [https://pscc2020.pt/ Power Systems Computation Conference]
* [https://attend.ieee.org/powertech-2019/ IEEE Power & Energy Society’s PowerTech]
* Also see additional conferences by [https://www.ieee.org/conferences/index.html IEEE] and the [https://www.ieee-pes.org/meetings-and-conferences IEEE Power & Energy Society]
 
=== Major journals ===
 
* [https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=59 IEEE Transactions on Power Systems]
* [https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165411 IEEE Transactions on Smart Grid]
 
=== Societies and organizations ===
 
* [https://www.ieee.org/ Institute of Electrical and Electronics Engineers (IEEE)], particularly the [https://www.ieee-pes.org/meetings-and-conferences IEEE Power & Energy Society]
 
=== Past and upcoming events ===
* [https://us.energypolicy.solutions/docs/ Energy Policy Simulator] from [https://energyinnovation.org/ Energy Innovation LLC]
* [https://github.com/invenia/OPFSampler.jl/ Optimal Power Flow (OPF) Sampler Package]
*[https://greeningthegrid.org/toolkits Greening the Grid toolkit]
*[https://powertac.org/ PowerTAC testing platform]
 
== Data ==
* [https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/IHBANG SubseasonalRodeo]
* [https://www.kaggle.com/c/ams-2014-solar-energy-prediction-contest American Meteorological Society 2013-2014 Solar Energy Prediction Contest]
*[https://www.google.com/get/sunroof/data-explorer/ Google Project Sunroof] (detailed estimates of solar potential based on sunlight and roof space) [TODO not sure if this belongs here]
 
=== Demand data ===
 
* [https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/1ZNLUY Rural Electricity Demand in India (REDI) Dataset]
 
=== GHG emissions data ===
 
* [https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-methane?tab=overview Global methane data]
* US Environmental Protection Agency's Continuous Emissions Monitoring data ([https://ampd.epa.gov/ampd/ tool] or [ftp://newftp.epa.gov/DMDnLoad/emissions/ FTP site])
* [https://github.com/tmrowco/electricitymap-contrib#data-sources ElectricityMap] data sources
 
=== Accelerated science for materials ===
 
* [https://materialsproject.org/ The Materials Project]
* [http://www2.fiz-karlsruhe.de/icsd_home.html Inorganic Crystal Structure Database]
* [https://www.cas.org/products/scifinder SciFinder] (paid)
* [https://archive.ics.uci.edu/ml/datasets/ UCI Machine Learning Repository datasets, e.g. “Concrete Compressive Strength”]
 
=== Other ===
 
* Also see listings on satellite imagery [TODO]
 
== Selected problems ==