@article{Goh2023, 
author = {Hui Hwang Goh and Jiahui Kang and Dongdong Zhang and Hui Liu and Wei Dai and Tonni Agustiono Kurniawan and Kai Chen Goh},
title = {Improving the Performance of DC Microgrids by Utilizing Adaptive Takagi-Sugeno Model Predictive Control},
year = {2023},
journal = {CSEE Journal of Power and Energy Systems},
volume = {9},
number = {4},
pages = {1472-1481},
keywords = {DC microgrids (MG), model predictive control (MPC), pulsed power loads (PPLs), nonlinear power observer, Takagi-Sugeno (TS) fuzzy model},
url = {https://www.sciopen.com/article/10.17775/CSEEJPES.2021.08920},
doi = {10.17775/CSEEJPES.2021.08920},
abstract = {In naval direct current (DC) microgrids, pulsed power loads (PPLs) are becoming more prominent. A solar system, an energy storage system, and a pulse load coupled directly to the DC bus compose a DC microgrid in this study. For DC microgrids equipped with sonar, radar, and other sensors, pulse load research is crucial. Due to high pulse loads, there is a possibility of severe power pulsation and voltage loss. The original contribution of this paper is that we are able to address the nonlinear problem by applying the Takagi-Sugeno (TS) model formulation for naval DC microgrids. Additionally, we provide a nonlinear power observer for estimating major disturbances affecting DC microgrids. To demonstrate the TS-potential, we examine three approaches for mitigating their negative effects: instantaneous power control (IPC) control, model predictive control (MPC) formulation, and TS-MPC approach with compensated PPLs. The results reveal that the TS-MPC approach with adjusted PPLs effectively shares power and regulates bus voltage under a variety of load conditions, while greatly decreasing detrimental impacts of the pulse load. Additionally, the comparison confirmed the efficiency of this technique.}
}