• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.1969-1982
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• 2015

The virtual inertia control (VIC) of wind turbine with directly-driven permanent-magnet synchronous generator (D-PMSG) can act similarly to the conventional synchronous generator in inertia response and frequency control, thereby supporting the system frequency stability. However, because the wind speed is inconstant and changeable to a certain extent and the D-PMSG is a complex nonlinear system, there are great difficulties in the virtual inertia optimal control of the D-PMSG. Based on the design principle of the active disturbance rejection control (ADRC), this paper presents a new VIC strategy for the D-PMSG from the perspective of power disturbance suppression in the system. The strategy helps fulfill the power grid disturbance estimation and compensation by means of the extended state observer (ESO) so as to improve the disturbance-resisting performance of the system. Compared with conventional proportional-derivative virtual inertia control (PDVIC), this method, which is of better adaptability and robustness, can not only improve the property of the D-PMSG responding to the system frequency but also reduce the influence of wind speed disturbance. The simulation and experiment results have verified the effectiveness and feasibility of the VIC based on the ADRC.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.8
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• pp.1099-1106
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• 2012

Microgrid is a new electrical energy system that composed of various generators, renewable energy, batteries and loads located near the electrical customers. When Microgrid is interconnected with large power system, Microgrid don't need to control the frequency. But in case of the outage or faults of power system, Microgrid should control the frequency to prevent the shutdown of Microgrid. This paper presents the frequency control methods using the droop function, being used by synchronous generators and EMS(Energy Management System). Using droop function, two battery systems could share the load based on locally measured signals without any communications between batteries. Also, we suggest that EMS should control the controllable distributed generators as P/Q control modes except batteries to overcome the weakness of droop function. Finally we suggest the two batteries systems to prolong the battery's life time considering the economical view. The validation of proposed methods is tested using PSCAD/EMTDC simulations and field test sites at the same time.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1254-1266
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• 2024

This study investigates the application of supercritical carbon dioxide (S-CO₂) direct-cycle micro modular reactors (MMRs) in primary frequency control (PFC), which is a scenario characterized by significant load fluctuations that has received less attention compared to secondary load-following. Using a modified GAMMA + code and a deep neural network-based turbomachinery off-design model, the authors conducted an analysis to assess the behavior of the reactor core and fluid system under different PFC scenarios. The results indicate that the acceptable range for sudden relative electricity output (REO) fluctuations is approximately 20%p which aligns with the performance of combined-cycle gas turbines (CCGTs) and open-cycle gas turbines (OCGTs). In S-CO₂ direct-cycle MMRs, the control of the core operates passively within the operational range by managing coolant density through inventory control. However, when PFC exceeds 35%p, system control failure is observed, suggesting the need for improved control strategies. These findings affirm the potential of S-CO₂ direct-cycle MMRs in PFC operations, representing an advancement in the management of grid fluctuations while ensuring reliable and carbon-free power generation.

• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.173-180
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• 2010

Information technology is being applied to the development of ubiquitous healthcare system, which provides both efficient patient care and convenient treatment regardless of patient's location. However, the increasing number of users and medical information give rise to the problem of user management and the infringement of privacy. In order to address this problem we propose a user access scheme based on the RBAC (Role Based Access Control) model. The preceding trust management model for Grid security, FAS(Federation Agent Server), was analyzed and extended to provide supplementary functions for role-based access control in u-Healthcare system. The RBAC model provides efficient user management and access control, but very vulnerable in case when one with valid role tries to leak confidential inner medical information. In order to resolve this problem, a RBAC-WS (Work Status with RBAC) model has been additionally developed which allows only qualified staffs to access the system while on duty. Th proposed RBAC and RBAC-WS model have been merged together and applied to the PACS (Picture Archiving and Communication System).

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1626-1636
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• 2013

Nowadays, a rapid development in wind power technologies is occurring compared with other renewable energies. This advance in technology has facilitated a new generation of wind turbines with larger capacity and higher efficiency. As the height of the turbines and the distance between turbines increases, the monitoring and control of this new generation wind turbines presents new challenges. This paper presents the architectural design, simulation, and evaluation of hybrid communication networks for a large-scale wind turbine (WT). The communication network of WT is designed based on logical node (LN) concepts of the IEC 61400-25 standard. The proposed hybrid network architectures are modeled and evaluated by OPNET. We also investigate network performance using three different technologies: Ethernet-based, WiFi-based, and ZigBee-based. Our network model is validated by analyzing the simulation results. This work contributes to the design of a reliable communication network for monitoring and controlling a wind power farms (WPF).

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.394-405
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• 2020

The parameters of transmission lines have an influence on the electromagnetic environment surrounding the line. This paper proposes a method based on phasor measurement unit (PMU) and supervisory control and data acquisition (SCADA) to achieve online estimation of transmission line full parameters, such as resistance, reactance and susceptance. The proposed full parameter estimation method is compared with the traditional method of estimating resistance independently based on SCADA system. Then, the electromagnetic environment is analyzed based on the different parameter estimation methods. The example results illustrate that online estimation of transmission line full parameters is more accurate in the analysis of electromagnetic environment, which further confirms its necessity and significance in engineering application.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.689-700
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• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.5
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• pp.1201-1209
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• 2016

While the legacy electric grid evolving into the smart grid, various communication standards have been used for interoperability between many components. In this situation, the needs emerged for protocol conversion and mapping method for connecting the outside components to the operation center. In this paper, according to the surge of IEC 61850-based substation automation, we studied the protocol conversion gateway for linking legacy DNP3-based control center and IEC 61850-based substation automation. This paper is based on the IEEE 1815.1 standard for the protocol mapping. We suggested the direction of development the gateway and developed prototype for evaluate the proposed gateway. Also, we bring up a security problem and give a solution.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.294-302
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• 2022

Detection of fake news is a complex and a challenging task. Generation of fake news is very hard to stop, only steps to control its circulation may help in minimizing its impacts. Humans tend to believe in misleading false information. Researcher started with social media sites to categorize in terms of real or fake news. False information misleads any individual or an organization that may cause of big failure and any financial loss. Automatic system for detection of false information circulating on social media is an emerging area of research. It is gaining attention of both industry and academia since US presidential elections 2016. Fake news has negative and severe effects on individuals and organizations elongating its hostile effects on the society. Prediction of fake news in timely manner is important. This research focuses on detection of fake news spreaders. In this context, overall, 6 models are developed during this research, trained and tested with dataset of PAN 2020. Four approaches N-gram based; user statistics-based models are trained with different values of hyper parameters. Extensive grid search with cross validation is applied in each machine learning model. In N-gram based models, out of numerous machine learning models this research focused on better results yielding algorithms, assessed by deep reading of state-of-the-art related work in the field. For better accuracy, author aimed at developing models using Random Forest, Logistic Regression, SVM, and XGBoost. All four machine learning algorithms were trained with cross validated grid search hyper parameters. Advantages of this research over previous work is user statistics-based model and then ensemble learning model. Which were designed in a way to help classifying Twitter users as fake news spreader or not with highest reliability. User statistical model used 17 features, on the basis of which it categorized a Twitter user as malicious. New dataset based on predictions of machine learning models was constructed. And then Three techniques of simple mean, logistic regression and random forest in combination with ensemble model is applied. Logistic regression combined in ensemble model gave best training and testing results, achieving an accuracy of 72%.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.12
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• pp.1825-1836
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• 2008

Many applications in computer graphics require complex and highly detailed models. However it is often desirable to use approximations in place of excessively detailed models in order to control the processing time. Thus, we aim to develop a notion of optimal matrix to simplify surface which can rapidly obtain the high quality 2D patterns flattening 3D surface as follows. Firstly, two 3D bodies are modeled based on existing Size Korea data. Secondly, each model is divided by shell and block for its pattern draft. Thirdly, each block is flattened by grid and bridge method. Finally, we selected the optimal matrix and demonstrated the efficiency and quality of the proposed method. This proposed approach accommodates surfaces with darts, which are commonly used in the clothing industry to reduce the deformation of surface forming and flattening. The resulting optimal matrix could be an initiation of standardization for pattern flattening. It is expected that this method could facilitate much better approximation in both efficiency and precision.