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Line Impedance Estimation Based Adaptive Droop Control Method for Parallel Inverters
Le, Phuong Minh,Pham, Xuan Hoa Thi,Nguyen, Huy Minh,Hoang, Duc Duy Vo,Nguyen, Tuyen Dinh,Vo, Dieu Ngoc The Korean Institute of Power Electronics 2018 JOURNAL OF POWER ELECTRONICS Vol.18 No.1
This paper presents a new load sharing control for use between paralleled three-phase inverters in an islanded microgrid based on the online line impedance estimation by the use of a Kalman filter. In this study, the mismatch of power sharing when the line impedance changes due to temperature, frequency, significant differences in line parameters and the requirements of the Plug-and-Play mode for inverters connected to a microgrid has been solved. In addition, this paper also presents a new droop control method working with the line impedance that is different from the traditional droop algorithm when the line impedance is assumed to be pure resistance or pure inductance. In this paper, the line impedance estimation for parallel inverters uses the minimum square method combined with a Kalman filter. In addition, the secondary control loops are designed to restore the voltage amplitude and frequency of a microgrid by using a combined nominal value SOGI-PLL with a generalized integral block and phase lock loop to monitor the exact voltage magnitude and frequency phase at the PCC. A control model has been simulated in Matlab/Simulink with three voltage source inverters connected in parallel for different ratios of power sharing. The simulation results demonstrate the accuracy of the proposed control method.
Deep Deterministic Policy Gradient 알고리즘을 응용한 자전거의 자율 주행 제어
최승윤,Le Pham Tuyen,정태충 한국융합보안학회 2018 융합보안 논문지 Vol.18 No.3
DDPG(Deep Deterministic Policy Gradient)알고리즘은 인공신경망과 강화학습을 사용하여 학습하는 알고리즘이다. 최근많은 연구가 이루어지고 있는 강화학습과 관련된 연구 중에서도 DDPG 알고리즘은 오프폴리시로 학습하기 때문에 잘못된 행동이 누적되어 학습에 영향을 미치는 경우를 방지하는 장점이 있다. 본 연구에서는 DDPG 알고리즘을 응용하여 자전거를 자율주행 하도록 제어하는 실험을 진행하였다. 다양한 환경을 설정하여 시뮬레이션을 진행하였고 실험을 통해서 사용된 방법이시뮬레이션 상에서 안정적으로 동작함을 보였다. The Deep Deterministic Policy Gradient (DDPG) algorithm is an algorithm that learns by using artificial neural network s and reinforcement learning. Among the studies related to reinforcement learning, which has been recently studied, the D DPG algorithm has an advantage of preventing the cases where the wrong actions are accumulated and affecting the learn ing because it is learned by the off-policy. In this study, we experimented to control the bicycle autonomously by applyin g the DDPG algorithm. Simulation was carried out by setting various environments and it was shown that the method us ed in the experiment works stably on the simulation.
Line Impedance Estimation Based Adaptive Droop Control Method for Parallel Inverters
Phuong Minh Le,Xuan Hoa Thi Pham,Huy Minh Nguyen,Duc Duy Vo Hoang,Tuyen Dinh Nguyen,Dieu Ngoc Vo 전력전자학회 2018 JOURNAL OF POWER ELECTRONICS Vol.18 No.1
This paper presents a new load sharing control for use between paralleled three-phase inverters in an islanded microgrid based on the online line impedance estimation by the use of a Kalman filter. In this study, the mismatch of power sharing when the line impedance changes due to temperature, frequency, significant differences in line parameters and the requirements of the Plug-and-Play mode for inverters connected to a microgrid has been solved. In addition, this paper also presents a new droop control method working with the line impedance that is different from the traditional droop algorithm when the line impedance is assumed to be pure resistance or pure inductance. In this paper, the line impedance estimation for parallel inverters uses the minimum square method combined with a Kalman filter. In addition, the secondary control loops are designed to restore the voltage amplitude and frequency of a microgrid by using a combined nominal value SOGI-PLL with a generalized integral block and phase lock loop to monitor the exact voltage magnitude and frequency phase at the PCC. A control model has been simulated in Matlab/Simulink with three voltage source inverters connected in parallel for different ratios of power sharing. The simulation results demonstrate the accuracy of the proposed control method.
Dual-band isotropic metamaterial absorber based on near-field interaction in the Ku band
The Linh Pham,Hong Tiep Dinh,Dinh Hai Le,Xuan Khuyen Bui,Son Tung Bui,Hong Luu Dang,Anh Duc Phan,Dac Tuyen Le,Dinh-Lam Vu 한국물리학회 2020 Current Applied Physics Vol.20 No.2
We numerically and experimentally investigate single-band and dual-band isotropic metamaterial absorbers (IMAs) based on metallic disks. By optimizing the diameter of the metallic disks and the thickness of the dielectric substrate, the single-band IMA is observed at 16.2 GHz with absorptivity of 97%. When adding one diskpair to the structure, the dual-band IMA is obtained at 12.8 and 15.5 GHz due to the symmetry breaking. The physical mechanics is explained by near-field coupling effect and equivalent LC circuit model. The measurement results performed in the range 12–18 GHz show a good agreement with simulation and theoretical analysis. Our findings demonstrate a new approach to achieve dual-band and multi-band IMAs.
Thi My Ni PHAM,Thi Ngoc Thao PHAM,Ha Phuong Truc NGUYEN,Bao Tuyen LY,Truc Linh NGUYEN,Hoanh Su LE 한국유통과학회 2022 The Journal of Asian Finance, Economics and Busine Vol.9 No.5
Banking and finance is a broad term that incorporates a variety of smaller, more specialized subjects such as corporate finance, tax finance, and insurance finance. A virtual assistant that assists users in searching for information about banking and finance terms might be an extremely beneficial tool for users. In this study, we explored the process of searching for information, seeking opportunities, and developing a virtual assistant in the first stages of starting learning and understanding Vietnamese to increase effectiveness and save time, which is also an innovative business practice in Use-case Vietnam. We built the FIBA2020 dataset and proposed a pipeline that used Natural Language Processing (NLP) inclusive of Natural Language Understanding (NLU) algorithms to build chatbot applications. The open-source framework RASA is used to implement the system in our study. We aim to improve our model performance by replacing parts of RASA’s default tokenizers with Vietnamese tokenizers and experimenting with various language models. The best accuracy we achieved is 86.48% and 70.04% in the ideal condition and worst condition, respectively. Finally, we put our findings into practice by creating an Android virtual assistant application using the model trained using Whitespace tokenizer and the pre-trained language m-BERT.