Duy Đức

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アイランドモードマイクログリッドにおける電力共有の新しい制御戦略【Powered by NICT】

IEEE Conference Proceedings, 2017

Control of power sharing in an island microgrid using virtual impedance

In this paper, a reactive power sharing strategy that uses droop controller combined with virtual... more In this paper, a reactive power sharing strategy that uses droop controller combined with virtual impedance and estimating the voltage drop due to the line impedance to improve significantly improves the reactive power control and sharing accuracy. Because of, with a given minimum allowable voltage of system, the voltage droop slope cannot be made arbitrarily large, so this paper presents a better way to improve the reactive power control and sharing accuracy is to incorporate the line voltage drop effect into the power control. This can be realized by adding the coefficient slopes of the voltage into droop control, to estimate the voltage drop due to line impedance and effect of local loads. Finally, considering the different locations of loads in a multibus microgrid. The proposed reactive power cosharing strategy has been tested in simulation Matlab/Simulink.

Application of native signal sequences for recombinant proteins secretion in Pichia pastoris

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Application of Marker Assisted Backcrossing to Pyramid Salinity Tolerance ( Saltol ) into Rice Cultivar- Bac Thom 7

Vietnam is one of the most vulnerable countries to climate change in Asia. Rice is a principle fo... more Vietnam is one of the most vulnerable countries to climate change in Asia. Rice is a principle food in Vietnam and plays an important role in economy of the country. However, rice yield and its cultivating areas are adversely affected from the threats of devastation caused by the rise of sea level. Using marker assisted backcrossing (MABC) to develop a new salt tolerance rice variety is one of the feasible methods to cope with these devastating changes. To improve rice salt tolerance in Bac Thom 7 cultivar, FL478 was used as a donor parent to introgress the saltol QTL conferring salt tolerance into Bac Thom 7. Three backcrosses were conducted to transfer positive alleles of saltol from FL478 into Bac Thom 7. The plants number IL-30 and IL-32 in BC 3 F 1 population expected recurrent genome recovery of up to 99.2%, 100%, respectively. These selected lines that carried the saltol alleles were screened in field for their agronomic traits. All improved lines had saltol allele similar to the donor parent FL478, whereas their agronomic performances were the same as the original Bac Thom 7. We show here the success of improving rice salt tolerance by MABC and the high efficiency of selection in early generations. In the present study, MABC accelerated the development of superior qualities in the genetic background of Bac Thom 7.

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A new control strategy of power sharing in islanded microgrids

This paper proposes a new control sharing technique for parallel three-phase inverters in an isla... more This paper proposes a new control sharing technique for parallel three-phase inverters in an islanded microgrid. The new control technique combining the adaptive impedance controller and the communication among the parallel inverters to accurately share real power and reactive power when there is a distinct difference between line impedances and the loads change in the microgrid. In this technique, the communication information is used to update the virtual impedance to compensate the voltage drop. If the interruption occurs, the stand-alone control mode is independently applied to quickly re-establish the balanced state. Therefore, the accuracy of the power sharing in this technique is within the allowed system limits. The communication network between the inverters and the control center is shown in Fig. 2 and the real and reactive power sharing controller is shown in Fig. 3. The simulation results have indicated that the proposed technique is better than the traditional droop control in terms of the accuracy and stability. Therefore, the new proposed technique can be a favorably alternative model for real power and reactive power sharing control of parallel inverters in a islanded microgrid.

Control of power in an island microgrid using adaptive droop control

In this paper, proposed an adaptive droop controller using compensate for the mismatch in voltage... more In this paper, proposed an adaptive droop controller using compensate for the mismatch in voltage drops across line impedance, to enhance reactive power sharing accuracy in island microgrid. Communication is used to facilitate the tuning of adaptive controller for the change of load. The method will ensure in accurate reactive power sharing even the communication is interrupted if the load does not change during this time. If the load changes while the communication is interrupted, the accurate sharing is reduced, but the proposed method is better than the conventional droop control method. In addition, the accuracy reactive power sharing base on the proposed method is not affected by the time delay in the communication channel. The feasibility and effectiveness of the proposed method are demonstrated by using simulation on Matlab/Simulink.

Multi-objective models for biomass supply chain planning with economic and carbon footprint consideration

Energy Reports, Nov 1, 2021

Abstract This paper focuses on designing multi-objective biomass supply chain planning models tha... more Abstract This paper focuses on designing multi-objective biomass supply chain planning models that aim to simultaneously minimize the total cost and the carbon footprint from the transportation. Stochastic and fuzzy models were developed for making strategic (optimal plant locations) and tactical decisions (material flows, truck types, etc.), while capturing the uncertainty of the demand. An epsilon-constraint method was applied to generate optimal solutions from these models. Managerial insights are provided based on a practical case study at a biomass plant in the Lower Northern region of Thailand; nine biomass plant candidates, nine rice husks suppliers and eight trucks were considered in the case study. A sensitivity analysis has been conducted to compare the results from the two models. The stochastic model can take into account all the scenarios of demand, while the fuzzy model can handle only a certain level of demand defined by a centroid value. The stochastic model needs to take into account a large number of variables and constraints, and therefore, requires more runtime to define an optimal solution, as compared to the fuzzy model. The trade-off between the operating cost and carbon emissions from both the models are provided with managerial insights.

Control of power inverter in islanded microgrids based on online line impedance estimation

In this paper, proposed an adaptive droop control method using estimated the line impedance in re... more In this paper, proposed an adaptive droop control method using estimated the line impedance in real time and compensate for the mismatch in voltage drops across line impedance, to enhance reactive power sharing accuracy in island microgrids. The block of line parameter estimation using the current and voltage parameters in the microgrid and estimation algorithm recursive least squares method (LSM). The Second-order generalized integrator-phase-locked loop (SOGI-PLL) is used to monitor such amplitude voltage phases and frequency at the point of common coupling (PCC) of the inverters. The line parameters are a mixture of resistance and reactance and has been estimated in real time. Therefore, the adaptive droop control method is more real, providing good performance under all conditions of load and line. The feasibility and effectiveness of the proposed method are demonstrated by using simulation on Matlab/Simulink.

Supply chain model for renewable energy resource from biomass in Vietnam

2018 5th International Conference on Industrial Engineering and Applications (ICIEA), Apr 1, 2018

Biomass is an important renewable energy resource. Typically, a biomass supply chain is often ver... more Biomass is an important renewable energy resource. Typically, a biomass supply chain is often very large and complex due to the large number of facilities within the supply chain and uncertain factors considered. In this research, a mathematical model that can be used to determine the number and locations of biomass plants is proposed. The objective is to minimize the factory fixed cost, transportation cost, purchasing cost, and inventory cost. The model is applied to a case study in Vietnam, where every region in Vietnam is considered in biomass supply chain planning. First, all data related to demand, available biomass quantity, and various costs are collected and analyzed. Second, a mixed integer model is used to model and solve the problem with uncertain demand and available biomass quantity with seasonal effect. The result from the model gives the best potential biomass plant locations in every region. Also, the result reports the amount of biomass used and inventoried in each time period.

A Dynamic Route-Planning System Based on Industry 4.0 Technology

Algorithms, Nov 25, 2020

Due to the availability of Industry 4.0 technology, the application of big data analytics to auto... more Due to the availability of Industry 4.0 technology, the application of big data analytics to automated systems is possible. The distribution of products between warehouses or within a warehouse is an area that can benefit from automation based on Industry 4.0 technology. In this paper, the focus was on developing a dynamic route-planning system for automated guided vehicles within a warehouse. A dynamic routing problem with real-time obstacles was considered in this research. A key problem in this research area is the lack of a real-time route-planning algorithm that is suitable for the implementation on automated guided vehicles with limited computing resources. An optimization model, as well as machine learning methodologies for determining an operational route for the problem, is proposed. An internal layout of the warehouse of a large consumer product distributor was used to test the performance of the methodologies. A simulation environment based on Gazebo was developed and used for testing the implementation of the route-planning system. Computational results show that the proposed machine learning methodologies were able to generate routes with testing accuracy of up to 98% for a practical internal layout of a warehouse with 18 storage racks and 67 path segments. Managerial insights into how the machine learning configuration affects the prediction accuracy are also provided.

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Comparison of ultrasound assisted extraction and enzyme assisted extraction of betacyanin from red dragon fruit peel

E3S web of conferences, 2020

This article was intended to extract betacyanin from the peel of red dragon fruit (Hylocereus pol... more This article was intended to extract betacyanin from the peel of red dragon fruit (Hylocereus polyrhizus) and used it as a natural colorant. In this study, enzyme and ultrasound techniques for the extraction of betacyanin from dried dragon fruit peel were compared. The ultrasonic power and sonication time levels were varied between 0.5, 1.5, 2.5, 3.5, and 4.5 W/g; and 2.5, 5.0, 7.5, 10.0, and 12.5 min. The enzyme concentrations were 0.25, 0.75, 1.25, 1.75, 2.25, and 2.75 %v/w. The results revealed that the maximum betacyanin content obtained by the optimal UAE condition (3.5 W/g and 7.5 min) was 0.3402 mg/g, and 9.47 % higher than that by the EAE method. The first-order kinetic extraction was used to describe the mechanism of extraction of betacyanin from red dragon fruit peels. The initial extraction rate (h) and extraction rate constant (k) of the UAE model were 30.80 and 27.81 % higher than those of the enzyme assisted extraction (EAE) model. The UAE treated only 5.0 min to obtain the highest level of betacyanin (0.323 mg/g), whereas the EAE took up to 20 min to achieve the maximal value (0.309 mg/g). The research clearly shows that the UAE method is a useful method for extracting betacyanin from dried red dragon fruit peel.

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Advanced Methodologies for Biomass Supply Chain Planning

Processes, Sep 26, 2019

Renewable energy resources have received increasing attention due to environmental concerns. Biom... more Renewable energy resources have received increasing attention due to environmental concerns. Biomass, one of the most important renewable energy resources, is abundant in agricultural-based countries. Typically, the biomass supply chain is large due to the huge amount of relevant data required for building the model. As a result, using a standard optimization package to determine the solution for the biomass supply chain model might not be practical. In this study, the focus is on developing and applying advanced methodologies that can be used to determine a solution for the biomass supply chain model efficiently. The decisions related to plant selection, and distribution of biomass from suppliers to plants require optimization. The methodologies considered in this research are based on stochastic programming, parameter search, and simulation-based optimization. Computational results and managerial insights based on case studies from different regions of Vietnam are provided. The results show that parameter search is suitable for small problems only, while stochastic programming is suitable for small and medium problems. For large problem, simulation-based optimization performs better when considering the quality of the solution and the run time, although, this method does not guarantee an optimal solution. It provides good solutions where the gaps to the optimal solutions are between 0.59% and 8.41%.

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Machine Learning Model for a Dynamic Path Planning Problem

Journal of physics, Oct 1, 2020

Due to an advancement in Industry 4.0 technology, various autonomous systems have been developed ... more Due to an advancement in Industry 4.0 technology, various autonomous systems have been developed in order to increase the operational efficiency. This paper considers an application of Industry 4.0 technology to an autonomous transportation operation. The paper focuses on applying a machine learning technique to a dynamic path planning problem where real-time randomized obstacle locations are considered. The routes or the solutions from the dynamic path planning problem are determined by an A-star algorithm, which are then used to build machine learning models based on an artificial neural network. The models were developed to discover the relationship between the input and output of the dynamic path planning problem. The structure of the network which is defined by the number of intermediate layers and the number of nodes is provided, where the overall accuracy is used to evaluate the setting efficiency. The proposed methodology was tested with a problem that consists of 7 types of paths, and the number of randomized obstacles fluctuated from 1 to 8. The paths were generated based on a layout of a consumer product warehouse. The proposed model succeeded in predicting the robot paths with 98.5% prediction accuracy.

Wideband Re-synthesis of Narrowband Speech Using Discriminative Piecewise Linear Transformation

Journal of Signal Processing, 2013

Artificial Bandwidth Extension (ABE) is a technique that attempts to regenerate the wideband sign... more Artificial Bandwidth Extension (ABE) is a technique that attempts to regenerate the wideband signal (0-8 kHz) from a narrowband signal (300-3.4 kHz) in order to improve the speech quality of today's telephone systems. By employing the well-known source-filter model, ABE can be divided into 2 sub-problems, namely extension of the excitation signal and extension of the spectral envelope. Since the extension of spectral envelope has a more significant effect on perceived speech quality as compared to that of the excitation signal [1], more efforts have been put into this problem. Several approaches to the problem of extending the spectral envelope have already been proposed. Although speech quality is improved as compared to the narrowband speech, a clear gap between the regenerated speech and original wideband speech could still be seen. In this paper, we propose a new approach to this problem by introducing a discriminative model into SPLICE [2], and describe its performance.

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Thực trạng hành vi nguy cơ của bệnh không lây nhiễm ở người trưởng thành tại thành phố Huế năm 2017

Nghiên cứu mô tả cắt ngang trên 600 người trưởng thành 18-69 tuổi tại thành phố Huế năm 2017 nhằm... more Nghiên cứu mô tả cắt ngang trên 600 người trưởng thành 18-69 tuổi tại thành phố Huế năm 2017 nhằm mô tả thực trạng bốn yếu tố hành vi nguy cơ của bệnh không lây nhiễm: hút thuốc lá, uống rượu bia ở mức có hại, ăn ít rau quả và thiếu hoạt động thể lực. Bộ câu hỏi STEPS của Tổ chức Y tế Thế giới đã được sửa đổi và sử dụng cho nghiên cứu này. Kết quả cho thấy tỷ lệ hút thuốc là 28,3% (nam 56,6%, nữ 4,9%), uống rượu ở mức có hại là 14,0% (nam 23,9%, nữ 5,8%), ăn ít rau quả là 89,0% (nam 92,3%, nữ 86,3%) và thiếu hoạt động thể lực là 34,0% (nam 28,7%, nữ 38,4%). Các yếu tố hành vi nguy cơ của bệnh không lây nhiễm có liên quan đến giới tính (p<0,05). Nhìn chung, 96,0% người trưởng thành có từ một hành vi nguy cơ trở lên, trong đó tỷ lệ người có một đến hai hành vi nguy cơ là cao nhất, chiếm 79,5%. Giáo dục sức khỏe và các can thiệp khác để giảm các yếu tố hành vi nguy cơ của bệnh không lây nhiễm trong các nhóm nguy cơ cao được đề xuất

L'agricoltura nel Mediterraneo di fronte alle questioni globali

The world population is growing along with its demand for water, food and energy. Feeding the Pla... more The world population is growing along with its demand for water, food and energy. Feeding the Planet means considering agriculture a priority. The Mediterranean area, with its diverse populations and particular geography, is an interesting testing ground for implementing an ecology-based agriculture

Đề xuất S-hộp có tính chất mật mã tốt cho hoán vị của hàm băm Keccak

Journal of Science and Technology on Information security, 2020

Tóm tắt—Keccak là hàm băm giành được chiến thắng trong cuộc thi SHA-3 của Viện Tiêu chuẩn và Công... more Tóm tắt—Keccak là hàm băm giành được chiến thắng trong cuộc thi SHA-3 của Viện Tiêu chuẩn và Công nghệ Mỹ (NIST) tổ chức. Có nhiều tấn công thám mã khai thác bậc đại số thấp trong hoán vị của hàm băm này. Chính những kết quả này mà nhóm tác giả thiết kế Keccak đã tăng số vòng từ 18 lên 24 trong hoán vị của nó. Trên cơ sở đó, bài báo tập trung phân tích tính chất đại số của hoán vị Keccak-f trong hàm băm này, sau đó đề xuất một thành phần S-hộp mới có tính chất mật mã tốt để sử dụng trong hoán vị của hàm băm Keccak.—Keccak is the winner of the SHA-3 competition of National Institute of Standards and Technology (NIST). There are many cryptographic attacks that exploit the low algebraic degree in permutation of this hash function. Due to these results, the Keccak design team increased the number of rounds from 18 to 24 in its permutation. On that basis, the paper focuses on analyzing the algebraic properties of the Keccak-f permutation in this hash function, then proposes a new S-box w...

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Multi-objective models for biomass supply chain planning with economic and carbon footprint consideration

Energy Reports, 2021

An integrated methodology based on machine-learning algorithms for biomass supply chain optimization

International Journal of Logistics Systems and Management, 2021

A Hybrid Methodology Based on Machine Learning for a Supply Chain Optimization Problem

Journal of Physics: Conference Series, 2020

This paper presents an advanced methodology that integrates a machine learning methodology into a... more This paper presents an advanced methodology that integrates a machine learning methodology into an optimization process. The framework of an interactive machine learning algorithm was developed to meet the challenges in solving large-scale optimization problems. An artificial neural network (ANN) is used with the knowledge gained from solving previous problems with different scenarios to define a good starting point for a solution searching process. By using an initial solution, known as “warm start”, the search space can be reduced to get more opportunity to find an optimal solution. The applicability of the proposed method was evaluated by using it to determine the optimal facility locations for a biomass supply chain problem using a real case study from Central Vietnam. The supply chain planning model is based on an optimization model, where the goal is to maximize the benefits from meeting the electricity demand minus the total cost from facility cost, penalty cost from lost dem...

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