MATPOWER is a package of Matlab M-files for solving power flow and optimal power flow problems. It is intended as a simulation tool for researchers and educators that is easy to use and modify. MATPOWER is designed to give the best performance possible while keeping the code simple to understand and modify. It was initially developed as part of the PowerWeb project.

References in zbMATH (referenced in 76 articles )

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  1. Dandurand, Brian C.; Kim, Kibaek; Leyffer, Sven: A bilevel approach for identifying the worst contingencies for nonconvex alternating current power systems (2021)
  2. Jiang, Yuning; Kouzoupis, Dimitris; Yin, Haoyu; Diehl, Moritz; Houska, Boris: Decentralized optimization over tree graphs (2021)
  3. Li, Qinxue; Li, Shanbin; Xu, Bugong; Liu, Yonggui: Data-driven attacks and data recovery with noise on state estimation of smart grid (2021)
  4. Qu, Bogang; Wang, Zidong; Shen, Bo: Fusion estimation for a class of multi-rate power systems with randomly occurring SCADA measurement delays (2021)
  5. Roth, Jacob; Barajas-Solano, David A.; Stinis, Panos; Weare, Jonathan; Anitescu, Mihai: A kinetic Monte Carlo approach for simulating cascading transmission line failure (2021)
  6. Xavier, Álinson S.; Qiu, Feng; Ahmed, Shabbir: Learning to solve large-scale security-constrained unit commitment problems (2021)
  7. Zhang, Richard Y.; Lavaei, Javad: Sparse semidefinite programs with guaranteed near-linear time complexity via dualized clique tree conversion (2021)
  8. Zocca, Alessandro; Zwart, Bert: Optimization of stochastic lossy transport networks and applications to power grids (2021)
  9. Abhyankar, Shrirang; Betrie, Getnet; Maldonado, Daniel Adrian; Mcinnes, Lois C.; Smith, Barry; Zhang, Hong: PETSc DMNetwork: a library for scalable network PDE-based multiphysics simulations (2020)
  10. Bienstock, Dan; Escobar, Mauro; Gentile, Claudio; Liberti, Leo: Mathematical programming formulations for the alternating current optimal power flow problem (2020)
  11. Castrillón-Candás, Julio E.; Kon, Mark: Analytic regularity and stochastic collocation of high-dimensional Newton iterates (2020)
  12. Chowdhury, Nilanjan Roy; Belikov, Juri; Baimel, Dmitry; Levron, Yoash: Observer-based detection and identification of sensor attacks in networked CPSs (2020)
  13. Eltved, Anders; Dahl, Joachim; Andersen, Martin S.: On the robustness and scalability of semidefinite relaxation for optimal power flow problems (2020)
  14. Fokken, Eike; Göttlich, Simone; Kolb, Oliver: Optimal control of compressor stations in a coupled gas-to-power network (2020)
  15. Kardoš, Juraj; Kourounis, Drosos; Schenk, Olaf: Structure-exploiting interior point methods (2020)
  16. Khastieva, D.; Hesamzadeh, M. R.; Vogelsang, I.; Rosellón, J.: Transmission network investment using incentive regulation: a disjunctive programming approach (2020)
  17. Lesage-Landry, Antoine; Taylor, Joshua A.: A second-order cone model of transmission planning with alternating and direct current lines (2020)
  18. Md Ashfaqur Rahman: Torrit: A GUI-Based Power System Simulation Platform (2020) arXiv
  19. Meng, Min; Xiao, Gaoxi; Zhai, Chao; Li, Guoqi; Wang, Zhen: Distributed consensus of heterogeneous multi-agent systems subject to switching topologies and delays (2020)
  20. Montanari, Arthur N.; Moreira, Ercilio I.; Aguirre, Luis A.: Effects of network heterogeneity and tripping time on the basin stability of power systems (2020)

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