Electricity Systems

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A schematic of selected opportunities to reduce greenhouse emissions from electricity systems using machine learning. From "Tackling Climate Change with Machine Learning."[1]

AI has been called the new electricity, given its potential to transform entire industries.[2] Interestingly, electricity itself is one of the industries that AI is poised to transform. Many electricity systems are awash in data, and the industry has begun to envision next-generation systems (smart grids) driven by AI and ML.[3][4][5]

Electricity systems are responsible for about a quarter of human-caused greenhouse gas emissions each year.[6] Moreover, as buildings, transportation, and other sectors seek to replace GHG-emitting fuels, demand for low-carbon electricity will grow. To reduce emissions from electricity systems, society must

  • Rapidly transition to low-carbon electricity sources (such as solar, wind, hydro, and nuclear) and phase out carbon-emitting sources (such as coal, natural gas, and other fossil fuels).
  • Reduce emissions from existing CO2-emitting power plants, since the transition to low-carbon power will not happen overnight.
  • Implement these changes across all countries and contexts, as electricity systems are everywhere.

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.[1] 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

Primers

  • Chapter 7: "Energy Systems" in the IPCC Fifth Assessment Report (2014)[7]: An overview of "issues related to the mitigation of greenhouse gas emissions (GHG) from the energy supply sector."
  • "Energy Primer: A Handbook for Energy Market Basics" by the U.S. Federal Energy Regulatory Commission (2020)[8]: A primer on wholesale electricity, natural gas, and oil/petroleum markets, as well as energy-related financial markets, in the United States.

Textbooks

  • "Electric Power Systems: A Conceptual Introduction" (2006)[9]: A textbook "intended to bridge the gap between formal engineering texts and more popularly accessible descriptions of electric power technology."
  • "Power Generation, Operation, and Control" (2013)[10]: A canonical reference on the engineering and economics of electric power systems.
  • "Fundamentals of Power System Economics" (2018)[11]: An introduction to electricity markets.

Other

Online courses and course materials

  • "Electric Power Systems" on Coursera: A course covering the "standards and policies of the electric utility industry," including "basic vocabulary used in the business" and an introduction of "the electric power system, from generation of the electricity all the way to the wall plug."
  • "Computational Methods for the Smart Grid": "[A]n introduction to recent advances in computational methods applied to sustainable energy and the smart grid... provid[ing] students with a broad background in state-of-the-art computational methods that repeatedly arise in these domains, such as machine learning, optimization, and control."

Community

Major conferences

Major journals

  • 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."
  • 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."

Major societies and 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."

Libraries and tools

Data

Electricity system data

Renewables forecasting contest data

Demand data

  • Rural Electricity Demand in India (REDI) Dataset: "The dataset contains detailed information on electricity demand in rural India. The dataset covers 10,000 households and 2,000 rural enterprises across 200 villages in Bihar, Uttar Pradesh, Odisha, and Rajasthan."

GHG emissions data

Other

  • Accelerated materials science datasets: Datasets that may be useful for research on solar fuels, next-generation battery conducting fluids, or other accelerated materials science applications in the electricity sector.
  • Satellite imagery datasets: Datasets that may be useful for applications such as power plant emissions detection, power grid mapping, solar panel mapping, etc.
  • Project Sunroof by Google: Detailed estimates of rooftop solar potential based on sunlight and roof space.

Selected problems

Under construction

References

  1. 1.0 1.1 Rolnick, David; Donti, Priya L.; Kaack, Lynn H.; Kochanski, Kelly; Lacoste, Alexandre; Sankaran, Kris; Ross, Andrew Slavin; Milojevic-Dupont, Nikola; Jaques, Natasha; Waldman-Brown, Anna; Luccioni, Alexandra (2019-11-05). "Tackling Climate Change with Machine Learning". arXiv:1906.05433 [cs, stat].
  2. "Andrew Ng: Artificial Intelligence is the New Electricity - YouTube". www.youtube.com.
  3. Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Rogers, Alex; Jennings, Nicholas R. (2012-04). "Putting the 'smarts' into the smart grid". Communications of the ACM. 55 (4): 86–97. doi:10.1145/2133806.2133825. ISSN 0001-0782. Check date values in: |date= (help)
  4. Machine Learning Techniques for Supporting Renewable Energy Generation and Integration: A Survey, Springer International Publishing
  5. "How artificial intelligence will affect the future of energy and climate". Brookings. 2019-01-10.
  6. IPCC. Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [O. Edenhofer, R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlomer, C. von Stechow, T. Zwickel, J.C. Minx, (eds.)]. 2014.
  7. Bruckner T., I.A. Bashmakov, Y. Mulugetta, H. Chum, A. de la Vega Navarro, J. Edmonds, A. Faaij, B. Fungtammasan, A. Garg, E. Hertwich, D. Honnery, D. Infield, M. Kainuma, S. Khennas, S. Kim, H.B. Nimir, K. Riahi, N. Strachan, R. Wiser, and X. Zhang, 2014: Energy Systems. In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Available at https://www.ipcc.ch/report/ar5/wg3/energy-systems/
  8. Federal Energy Regulatory Commission. "Energy Primer: A Handbook of Energy Market Basics." Federal Energy Regulatory Commission: Washington, DC, USA (2020). Available at https://www.ferc.gov/sites/default/files/2020-06/energy-primer-2020.pdf
  9. Von Meier, Alexandra. "Electric power systems." A Conceptual Introduction (2006).
  10. Wood, A. J., Wollenberg, B. F., & Sheblé, G. B. (2013). Power generation, operation, and control. John Wiley & Sons.
  11. Kirschen, D. S., & Strbac, G. (2018). Fundamentals of power system economics. John Wiley & Sons.