Lecture Notes on Optimal Power Flow (OPF)
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Abstract (arXiv)
These lecture notes cover the DC Optimal Power and AC Optimal Power Flow formulations, as well as the Economic Dispatch for Power Systems. Their aim is to supplement the study material for the course "31765: Optimization in modern power systems" at the Technical University of Denmark (DTU). The first edition of the present lecture notes was prepared for the academic year 2018-2019. Note that the material presented in these notes is a constant work in progress. Future editions will include OPF formulations based on semidefinite programming, detailed derivation of Locational Marginal Prices, and other topics. For any comments, errors, or omissions, you are welcome to contact me at "spchatz_at_elektro.dtu.dk". Special thanks to the students of the 31765 course for their remarks and suggestions to improve these lecture notes.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 2 Nov 2018.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 0; 2025: 1; 2026: 1.
5 papers.
- 2021Physics-Informed Neural Networks for Minimising Worst-Case Violations in DC Optimal Power Flowcited by 23
- 2022Unsupervised Optimal Power Flow Using Graph Neural Networkscited by 14
- 2022Minimizing Worst-Case Violations of Neural Networkscited by 3
- 2025DiffOPF: Diffusion Solver for Optimal Power Flowcited by 2
- 2026Constrained Reinforcement Learning Using Successor Representationscited by 0
- 2026Constrained Reinforcement Learning Using Successor Representations27 Jul 2026
- 2025DiffOPF: Diffusion Solver for Optimal Power Flow15 Oct 2025
- 2022Minimizing Worst-Case Violations of Neural Networks21 Dec 2022
- 2022Unsupervised Optimal Power Flow Using Graph Neural Networks17 Oct 2022
- 2021Physics-Informed Neural Networks for Minimising Worst-Case Violations in DC Optimal Power Flow28 Jun 2021