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IEEE-Transactions-on-Power-Systems_TPWRS.md

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TPWRS (IEEE Transactions on Power Systems)

  • Du, Y., Huang, Q., Huang, R., Yin, T., Tan, J., Yu, W. and Li, X., 2021. Physics-Informed Evolutionary Strategy Based Control for Mitigating Delayed Voltage Recovery. IEEE Transactions on Power Systems, 37(5), pp.3516-3527. [ www ] ( ES )
    • "The proposed physics-informed guided meta ES-based learning framework is deployed on a local high performance computing cluster with a Linux operation system of 520 nodes. Each node has a dual-socket Intel Haswell E5-2670V3 CPU with 64 GB DDR4 memory and 12 cores per socket running at 2.3 GHz."
      • T. Salimans, J. Ho, X. Chen, S. Sidor, and I. Sutskever, “Evolution strategies as a scalable alternative to reinforcement learning,” 2017, arXiv:1703.03864.
      • H. Mania, A. Guy, and B. Recht, “Simple random search provides a competitive approach to reinforcement learning,” in Proc. 32nd Int. Conf. Neural Inf. Process. Syst., 2018, pp. 1805–1814.
      • N. Maheswaranathan, L. Metz, G. Tucker, D. Choi, and J. Sohl-Dickstein, “Guided evolutionary strategies: Augmenting random search with surrogate gradients,” in Proc. Int. Conf. Mach. Learn., 2019, pp. 4264–4273.