• Journal of Power Electronics
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• v.15 no.4
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• pp.1006-1017
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• 2015

This paper presents a finite control set model predictive control (FCS-MPC) strategy for the AC/DC matrix converter used in grid-connected battery energy storage system (BESS). First, to control the grid current properly, the DC current is also included in the cost function because of input and output direct coupling. The DC current reference is generated based on the dynamic relationship of the two currents, so the grid current gains improved transient state performance. Furthermore, the steady state error is reduced by adding a closed-loop. Second, a Luenberger observer is adopted to detect the AC input voltage instead of sensors, so the cost is reduced and the reliability can be enhanced. Third, a switching state pre-selection method that only needs to evaluate half of the active switching states is presented, with the advantages of shorter calculation time, no high dv/dt at the DC terminal, and less switching loss. The robustness under grid voltage distortion and parameter sensibility are discussed as well. Simulation and experimental results confirm the good performance of the proposed scheme for battery charging and discharging control.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.2
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• pp.85-91
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• 2015

With the increasing popularity of Smart Grid infrastructure, it is much easier to collect energy usage data using AMI (Advanced Measuring Instrument) from residential housing, buildings and factories. Several researches have been done to improve an energy efficiency by analyzing the collected energy usage data. However, it is not easy to store and analyze the energy data using a traditional relational database management system since the data size grows exponentially with an increasing popularity of Smart grid infrastructure. In this paper, we are proposing a Hadoop based Big data system to store and analyze energy usage data. Based on our limited experiments, Hadoop based energy data analysis is three times faster than that of a relational database management system based approach with the current system.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1864-1872
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• 2014

Maloperation of protective relays is one of the major causes for cascading tripping in WANS. Another line trip followed by a previous line trip may occur due to overloading of the line, because of the load redistribution or unwanted trip of a backup relay due to change in the flow of fault current. Evaluation of each line is required by considering both of these effects. A new index named Line Security Index (LSI) is proposed in this paper which combines both Vulnerability Index (VI) and Protectability Index (PI) to completely evaluate the security of individual lines and their importance in the power grid. Computer simulations have been performed on the Korean power grid data to establish the feasibility of the proposed idea.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.686-689
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• 2004

Computational grids are emerging as a new infrastructure for internet-based parallel and distributed computing. Grid systems are enables the sharing, exchanging, discovery and aggregation of resources which distributed multiple administrative domains, organizations and enterprises. Accounting information service is one of the main obstacles to widespread adoption of the grid. But, most of grid portals do not support accounting information service. In this paper, we design an accounting information service and build a web-based grid portal including account management service and accounting information service.

• ETRI Journal
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• v.37 no.1
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• pp.197-202
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• 2015

A smart grid is a modernized electrical grid that uses information about the behaviors of suppliers and consumers in an automated fashion to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity. In the operation of a smart grid, demand side management (DSM) plays an important role in allowing customers to make informed decisions regarding their energy consumption. In addition, it helps energy providers reduce peak load demand and reshapes the load profile. In this paper, we propose a new DSM scheduling scheme that makes use of the day-ahead pricing strategy. Based on the Rubinstein-Stahl bargaining model, our pricing strategy allows consumers to make informed decisions regarding their power consumption, while reducing the peak-to-average ratio. With a simulation study, it is demonstrated that the proposed scheme can increase the sustainability of a smart grid and reduce overall operational costs.

• International Journal of Advanced Culture Technology
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• v.2 no.2
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• pp.7-10
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• 2014

In order to develop smart grid communications infrastructure, a high level of interconnectivity and reliability among its nodes is required. Sensors, advanced metering devices, electrical appliances, and monitoring devices, just to mention a few, will be highly interconnected allowing for the seamless flow of data. Reliability and security in this flow of data between nodes is crucial due to the low latency and cyber-attacks resilience requirements of the Smart Grid. In particular, Artificial Intelligence techniques such as Fuzzy Logic, Bayesian Inference, Neural Networks, and other methods can be employed to enhance the security gaps in conventional IDSs. A distributed FPGA-based network with adaptive and cooperative capabilities can be used to study several security and communication aspects of the smart grid infrastructure both from the attackers and defensive point of view. In this paper, the vital issue of security in the smart grid is discussed, along with a possible approach to achieve this by employing FPGA based Radial Basis Function (RBF) network intrusion.

• Journal of Power Electronics
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• v.15 no.1
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• pp.235-245
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• 2015

This paper proposes a reactive current assignment and control strategy for a doubly-fed induction generator (DFIG) based wind-turbine generation system under generic grid voltage sag or swell conditions. The system's active and reactive power constrains during grid faults are investigated with both the grid- and rotor-side convertors (GSC and RSC) maximum ampere limits considered. To meet the latest grid codes, especially the low- and high-voltage ride-through (LVRT and HVRT) requirements, an adaptive reactive current control scheme is investigated. In addition, a torque-oscillation suppression technique is designed to reduce the mechanism stress on turbine systems caused by intensive voltage variations. Simulation and experiment studies demonstrate the feasibility and effectiveness of the proposed control scheme to enhance the fault ride-through (FRT) capability of DFIG-based wind turbines during violent changes in grid voltage.

• Journal of Power Electronics
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• v.14 no.6
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• pp.1081-1092
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• 2014

Renewable energy is being spotlighted as the electric power generating source for the next generation. Due to an increase in renewable energy systems in the grid system, their impact on the grid has become non-negligible. Thus, many countries in the world, including Europe, present their own grid codes for grid power conversion devices. In order to experiment with these grid codes, grid fault test equipment is required. This paper proposes both equipment and a control method, which are constructed with a 7-level cascaded H-bridge converter, that are capable of generating various grid faults. In addition, the Pulse Width Modulation (PWM) method for multilevel converters is compared and analyzed. The proposed structure, the control method, and the PWM method are verified through simulation and experimental results.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.513-520
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• 2018

Since Paris Climate Change Conference in 2015, many policies to reduce the emission of greenhouse gas have been accelerating, which are mainly related to renewable energy resources and micro-grid. Presently, the technology development and demonstration projects are mostly focused on diversifying the power resources by adding wind turbine, photo-voltaic and battery storage system in the island-type small micro-grid. It is expected that the large-scaled micro-grid projects based on the regional district and town/complex city, e.g. the block type micro-grid project in Daegu national industrial complex will proceed in the near future. In this case, the economic cost or the carbon emission can be optimized by the efficient operation of energy mix and the appropriate construction of electric and heat supplying facilities such as cogeneration, renewable energy resources, BESS, thermal storage and the existing heat and electricity supplying networks. However, when planning a large residential town or city, the concrete plan of the energy infrastructure has not been established until the construction plan stage and provided by the individual energy suppliers of water, heat, electricity and gas. So, it is difficult to build the efficient energy portfolio considering the characteristics of town or city. This paper introduces an energy mix optimization(EMO) method to determine the optimal capacity of thermal and electric resources which can be applied in the design stage of the real large-scaled residential town or city, and examines the feasibility of the proposed method by applying the real heat and electricity demand data of large-scale residential towns with thousands of households and by comparing the result of HOMER simulation developed by National Renewable Energy Laboratory(NREL).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.27-35
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• 2019

There is a growing interest in various microgrid solutions that supply electricity 24 hours a day to off-grid areas where are not connected with the main grid, and Korea has many positive effects by constructing overseas microgrids as a country operating the emission trading scheme. Since it is not clear how to obtain load curves that is one of the inputs of the HOMER used to design a microgrid optimization plan, or it is necessary to examine whether electricity is supplied to the peak load level of the areas where have not received the electricity benefits from the viewpoint of the demand management, a methodology should be developed to know the load composition ratio and the shape of the daily load curve. In this paper, the relative coefficient and average load information for each load group obtained from the survey are used besides peak load and total average load. A mathematical model is proposed to derive the load composition ratio in the form of a Quadratic Programming and the load forecasting is performed using simple linear regression with future indicators. The effectiveness of the proposed method is confirmed for the Philippine island region supported by Korea Energy Agency and the Asian Development Bank.