@inproceedings{cad718c931ab41c4941247636e533bf9,
title = "Microgrid Energy Management System based ANN of the Two-Step Structure",
abstract = "This paper proposes an energy management system(EMS) based artificial neural network(ANN) for hybrid AC/DC microgrid(MG), which is composed of distributed generation(DG), energy storage system(ESS), variable loads. An ANN is applied to derive the optimal operation mode of the MG and the power reference of the ESS by using the power data of unpredictable DGs and loads. The ANN controller used in EMS was trained by MATLAB deep learning tool box. The effectiveness of the proposed EMS based ANN was verified through the PSIM simulation.",
keywords = "distributed generator, energy management system, interlinking converter, microgrid",
author = "Kim, \{Tae Gyu\} and Hoon Lee and An, \{Chang Gyun\} and Kang, \{Kyung Min\} and Junsin Yi and Won, \{Chung Yuen\}",
note = "Publisher Copyright: {\textcopyright} 2021 KIEE \& EMECS.; 24th International Conference on Electrical Machines and Systems, ICEMS 2021 ; Conference date: 31-10-2021 Through 03-11-2021",
year = "2021",
doi = "10.23919/ICEMS52562.2021.9634545",
language = "English",
series = "ICEMS 2021 - 2021 24th International Conference on Electrical Machines and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "319--322",
booktitle = "ICEMS 2021 - 2021 24th International Conference on Electrical Machines and Systems",
}