Improving the Performance of DC Microgrids byb Utilizing Adaptive Takagi-Sugeno Model Predictive Control
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...
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my.uthm.eprints.105972024-01-15T07:29:55Z http://eprints.uthm.edu.my/10597/ Improving the Performance of DC Microgrids byb Utilizing Adaptive Takagi-Sugeno Model Predictive Control Hui Hwang Goh, Hui Hwang Goh Jiahui Kang, Jiahui Kang Dongdong Zhang, Dongdong Zhang Hui Liu, Hui Liu Wei Dai, Wei Dai Tonni Agustiono Kurniawan, Tonni Agustiono Kurniawan Kai Chen Goh, Kai Chen Goh T Technology (General) 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. 2023 Article PeerReviewed text en http://eprints.uthm.edu.my/10597/1/J16555_c7818bca77313d74b1f271e103f264db.pdf Hui Hwang Goh, Hui Hwang Goh and Jiahui Kang, Jiahui Kang and Dongdong Zhang, Dongdong Zhang and Hui Liu, Hui Liu and Wei Dai, Wei Dai and Tonni Agustiono Kurniawan, Tonni Agustiono Kurniawan and Kai Chen Goh, Kai Chen Goh (2023) Improving the Performance of DC Microgrids byb Utilizing Adaptive Takagi-Sugeno Model Predictive Control. CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 9 (4). pp. 1472-1481. |
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T Technology (General) Hui Hwang Goh, Hui Hwang Goh Jiahui Kang, Jiahui Kang Dongdong Zhang, Dongdong Zhang Hui Liu, Hui Liu Wei Dai, Wei Dai Tonni Agustiono Kurniawan, Tonni Agustiono Kurniawan Kai Chen Goh, Kai Chen Goh Improving the Performance of DC Microgrids byb Utilizing Adaptive Takagi-Sugeno Model Predictive Control |
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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. |
format |
Article |
author |
Hui Hwang Goh, Hui Hwang Goh Jiahui Kang, Jiahui Kang Dongdong Zhang, Dongdong Zhang Hui Liu, Hui Liu Wei Dai, Wei Dai Tonni Agustiono Kurniawan, Tonni Agustiono Kurniawan Kai Chen Goh, Kai Chen Goh |
author_facet |
Hui Hwang Goh, Hui Hwang Goh Jiahui Kang, Jiahui Kang Dongdong Zhang, Dongdong Zhang Hui Liu, Hui Liu Wei Dai, Wei Dai Tonni Agustiono Kurniawan, Tonni Agustiono Kurniawan Kai Chen Goh, Kai Chen Goh |
author_sort |
Hui Hwang Goh, Hui Hwang Goh |
title |
Improving the Performance of DC Microgrids byb Utilizing Adaptive Takagi-Sugeno Model Predictive Control |
title_short |
Improving the Performance of DC Microgrids byb Utilizing Adaptive Takagi-Sugeno Model Predictive Control |
title_full |
Improving the Performance of DC Microgrids byb Utilizing Adaptive Takagi-Sugeno Model Predictive Control |
title_fullStr |
Improving the Performance of DC Microgrids byb Utilizing Adaptive Takagi-Sugeno Model Predictive Control |
title_full_unstemmed |
Improving the Performance of DC Microgrids byb Utilizing Adaptive Takagi-Sugeno Model Predictive Control |
title_sort |
improving the performance of dc microgrids byb utilizing adaptive takagi-sugeno model predictive control |
publishDate |
2023 |
url |
http://eprints.uthm.edu.my/10597/1/J16555_c7818bca77313d74b1f271e103f264db.pdf http://eprints.uthm.edu.my/10597/ |
_version_ |
1789427597617135616 |