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Electricity Systems: Difference between revisions

 
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=== Enabling low-carbon electricity ===
 
*'''[[Electricity Supply Forecasting|Supply]] and, [[Energy Demand Forecasting|demand]] and [[Energy Price Forecasting|price]] forecasting''': The supply and demand of power must both be forecast ahead of time to inform electricity planning and scheduling. In more volatile energy systems, also forecasting of prices becomes relevant to utilize flexibility effectively. ML can help make these forecasts more accurate, improve temporal and spatial resolution, and quantify uncertainty.
*'''Improving [[Power System Optimization|power system optimization]]''': Scheduling algorithms on the power grid have trouble handling large quantities of solar, wind, and other time-varying electricity sources. ML can help improve electricity scheduling algorithms, control storage and flexible demand, and design real-time electricity prices that reduce CO<sub>2</sub> emissions.
*'''Improving [[Power System Planning|system planning]]''': Algorithms for planning new low-carbon energy infrastructure are often large and slow. ML can help speed up or provide proxies for these algorithms.
*[[Power System State Estimation|'''State estimation''']]: Many power distribution systems have few sensors, but are increasingly necessary to monitor due to the increase in rooftop solar power. ML can provide algorithms for understanding the state of distribution systems in "low-observability" scenarios where traditional state estimation algorithms may not suffice.
*'''[[Greenhouse Gas Emissions Detection|Greenhouse gas emissions mapping]]''': While some electricity system operators release publicly-available data on the emissions associated with fossil fuel generators, this data is not available in many cases. ML can help map greenhouse gas emissions using a combination of remote sensing and on-the-ground data.
*'''[[Non-Intrusive Load Monitoring|Non-Intrusive Load Monitoring (NILM)]]''': ML can be used to disaggregate the net-load measurements into their individual components. It finds application in disaggregating native load and PV generation measurements from the net-load measurements obtained at the feeder-lever or at the residential-level. Another aspect of energy disaggregation is non intrusive load monitoring, wherein the load measurement is disaggregated into different components representing the consumption of different household electric appliances.
 
== Background Readings ==
=== Major conferences ===
 
 
 
*'''ACM e-Energy''': "The International Conference on Future Energy Systems (ACM e-Energy) aims to be the premier venue for researchers working in the broad areas of computing and communication for smart energy systems (including the smart grid), and in energy-efficient computing and communication systems". Website [https://energy.acm.org/eenergy-conference/ here].
*'''IEEE Power & Energy Society General Meeting''': One of the [https://www.ieee-pes.org/meetings-and-conferences IEEE Power & Energy Society's] flagship annual conferences, held in North America. Website [https://pes-gm.org/ here].
*'''Power Systems Computation Conference''': A biennial conference held in Europe, focused on computational power system methods. Website [https://pscc-central.epfl.ch/ here].
*'''IEEE Transactions on Power Systems''': Covers the "requirements, planning, analysis, reliability, operation, and economics of electric generating, transmission, and distribution systems for general industrial, commercial, public, and domestic consumption." Journal website [https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=59 here].
*'''IEEE Transactions on Smart Grid''': "[A] cross disciplinary and internationally archival journal aimed at disseminating results of research on smart grid that relates to, arises from, or deliberately influences energy generation, transmission, distribution and delivery." Journal website [https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165411 here].
*'''IEEE Transactions on Sustainable Energy:''' This journal is aimed at disseminating results of research on the design, implementation, grid-integration, and control of sustainable energy technologies and systems that can be integrated into the power transmission and/or distribution grid. Journal website [https://www.ieee-pes.org/ieee-transactions-on-sustainable-energy here].
 
=== Major professional organizations ===
 
*'''IEEE Power & Energy Society''': "[T]he world's largest forum for sharing the latest in technological developments in the electric power industry, for developing standards that guide the development and construction of equipment and systems, and for educating members of the industry and the general public." Website [https://www.ieee-pes.org/ here].
*'''ACM Special Interest Group on Energy Systems and Informatics''': "ACM SIGEnergy is a professional forum for scientists, engineers, educators, and professionals for discussing energy systems and energy informatics. It brings together an inter-disciplinary group of computer scientists with diverse backgrounds [...] to discuss and address key challenges in future energy systems, and their impact on society." Website [https://energy.acm.org/ here].
 
== Libraries and Tools ==
 
*'''PowerTAC''': A power system simulation environment, available [https://powertac.org/ here].
*'''Energy Policy Simulator''': A tool to simulate the greenhouse gas emissions effects of various climate and energy policies, available [https://us.energypolicy.solutions/docs/ here].
*'''Optimal Power Flow (OPF) Sampler Package''': A Julia package to generate power grid data samples via optimal power flow methods, available [https://github.com/invenia/OPFSampler.jl/ here].
*'''Pyiso''': A Python client library for data from power grid balancing authorities in the United States, Canada, and Europe. Documentation [https://pyiso.readthedocs.io/en/latest here].
*'''List of Resources by ACM SIG Energy'''': A list of models, libraries, software and datasets curated by the [https://energy.acm.org/ ACM Special Interest Group on Energy Systems and Informatics], available [https://energy.acm.org/resources/ here].
* '''OPFLEarn.jl''': A [https://github.com/NREL/OPFLearn.jl Julia package] for creating datasets for machine learning approaches to solving AC optimal power flow (AC OPF).
 
== Data ==
*'''Pecan Street:''' Disaggregated energy and water data, available [https://www.pecanstreet.org/dataport/about/ here] (requires login)
*'''United States Environmental Protection Agency's Air Markets Program data''': Datasets from the US EPA's emissions trading programs. For instance, the Continuous Emissions Monitoring System dataset (also available via the EPA's [ftp://newftp.epa.gov/DMDnLoad/emissions/ FTP site]) provides hourly emissions and generation for many fossil fuel generators in the United States. Available [https://ampd.epa.gov/ampd/ here].
* '''Utility Transition Hub™ Data''': Datasets on US-based utility finances, investments, operations, emissions and the utilities' alignment and commitments for the 1.5°C goals. Available [https://utilitytransitionhub.rmi.org/data-download/ here].
 
=== Europe ===
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