• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.2
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• pp.279-286
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• 2013

The recent power shortages due to surge in demand for electricity highlights the importance of smart grid technologies for efficient use of power. The experimental content for vulnerability against availability of smart meter, an essential component in smart grid networks, has been reported. Designing availability protection mechanism to boost the realization possibilities of the secure smart grid is essential. In this paper, we propose a mechanism to detect the availability infringement attack for smart meter and also to find anomaly nodes through analyzing smart grid structure and traffic patterns. The proposed detection mechanism uses approximate entropy technique to decrease the detection load and increase the detection rate with few samples and utilizes the signal information(CIR or RSSI, etc.) that the anomaly node can not be changed to find the anomaly nodes. Finally simulation results of proposed method show that the detection performance and the feasibility.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.173-178
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• 2020

As the fourth industrial revolution, in which people, objects, and information are connected as one, various fields such as smart energy, smart cities, artificial intelligence, the Internet of Things, unmanned cars, and robot industries are becoming the mainstream, drawing attention to big data. Among them, Smart Grid is a technology that maximizes energy efficiency by converging information and communication technologies into the power grid to establish a smart grid that can know electricity usage, supply volume, and power line conditions. Smart meters are equient that monitors and communicates power usage. We start with the goal of building a virtual smart grid and constructing a virtual environment in which real-time data is generated to accommodate large volumes of data that are small in capacity but regularly generated. A major role is given in creating a software/hardware architecture deployment environment suitable for the system for test operations. It is necessary to identify the advantages and disadvantages of the software according to the characteristics of the collected data and select sub-projects suitable for the purpose. The collected data was collected/loaded/processed/analyzed by the Hadoop ecosystem-based big data platform, and used to predict power demand through deep learning.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.93-94
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• 2011

This paper analyzes the shaft torsion of a doubly-fed induction generator (DFIG) for a wind farm collector system fault. When a fault occurs, the active power of the DFIG cannot be transmitted to the grid and thus accelerates the rotation of both the blade and the rotor. Due to the different inertia of these, the angle of deviation fluctuates and the shaft torsion is occurred. This becomes much severe when the rotational speed of the blade exceeds a threshold, which activating the pitch control to reduce the mechanical power. The torque, which can be sixty times larger than that in the steady state, may destroy the shaft. The shaft torsion phenomena are simulated using the EMTP-RV simulator. The results indicate that when a wind farm collector system fault occurs, a severe shaft torsion is occurred due to the activation of the pitch control.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1368-1375
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• 2013

The Smart Grid, which can monitor or diagnose the power grid in real time to operate efficiently, has been pushed ahead systematically as one of alternatives to solve these issues by combining the advanced Information Communication Technology and the electrical network. Hence, the electric company which introduces smart grid technology can read remotely the electrical meter readings by means of two-way communication between the meter and the central system. This enabled the customer and the utility to take part in reasonable electrical energy utilization. AMI became one of the core foundations in realizing the Smart Grid. It is hard to test the entire process of AMI system before the full deployment because it covers the broad objects from the customer to the utility operation system and requires mass data handling and management. Therefore, we design an efficient AMI network model and a simulator for performance evaluation required to simulate the network model similar to the real environment. This tool supports to evaluate the efficiency of the AMI network equipments and deployment. Additionally, it estimates the appropriate number of deployments and the proper capabilities.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.4
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• pp.639-653
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• 2013

Smart grid is a network of computers and power infrastructure that monitor and manage energy usage efficiently. Recently, the smart grid demonstration projects around the world, including the United States, Europe, Japan, and the technology being developed. The protection of the many components of the grid against cyber-threats has always been critical, but the recent Smart grid has been threatened by a variety of cyber and physical attacks. We model and analyze advanced metering infrastructure(AMI) in smart grid. Using attack countermeasure tree(ACT) we show qualitative and probabilistic security analysis of AMI. We implement using SHARPE(Symbolic Hierarchical Automated Reliability and Performance Evaluator) tool and calculate probability, ROA, ROI, Structure Importance, Birnbaum Importance.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1248-1258
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• 2019

This paper presents a moth-flame optimization (MFO)-based maximum power point tracking (MPPT) method for photovoltaic (PV) systems. The MFO algorithm is a new optimization method that exhibits satisfactory performance in terms of exploration, exploitation, local optima avoidance, and convergence. Therefore, the MFO algorithm is quite suitable for solving multiple peaks of PV systems under partial shading conditions (PSCs). The proposed MFO-MPPT is compared with four MPPT algorithms, namely the perturb and observe (P&O)-MPPT, incremental conductance (INC)-MPPT, particle swarm optimization (PSO)-MPPT and whale optimization algorithm (WOA)-MPPT. Simulation and experiment results demonstrate that the proposed algorithm can extract the global maximum power point (MPP) with greater tracking speed and accuracy under various conditions.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.495-501
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• 2017

The introduction of smart grid, which is an innovative application of digital processing and communications to the power grid, might lead to more and more cyber threats originated from IT systems. In other words, The Energy Management System (EMS) and other communication networks interact with the power system on a real time basis, so it is important to understand the interaction between two layers to protect the power system from potential cyber threats. This paper aims to identify and clarify the cyber security risks and their interaction with the power system in Smart Grid. In this study, the optimal power flow (OPF) and Power Flow Tracing are used to assess the interaction between the EMS and the power system. Through OPF and Power Flow Tracing based analysis, the physical and economic impacts from potential cyber threats are assessed, and thereby the quantitative risks are measured in a monetary unit.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.44-48
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• 2015

The smart grid is a next-generation power grid to create a new value-added information technology. Power providers and consumers exchange information in real-time bi-directional, and optimize energy efficiency with using the smart grid. This paper describes the concept of demand response of the communication system used in the protocol, implementation of demand response systems with demand response scenarios for power reduction through the air conditioning control.

• Journal of Industrial Technology
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• v.30 no.A
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• pp.9-15
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• 2010

Recently, Smart Grid is a emerging topic in power and communication industry. Smart Grid refers to a evolution of the electricity supply infrastructure that monitors, protects, and intelligently optimize the operation of the interconnected elements including various type of generators, power grid, building/home automation system and end-use consumers. In order to successful implementation of Smart Grid, energy management function will be the key factor that coordinates and optimally controls the various loads according to the operating condition and environments, and the load patterns in residential and commercial building will be required as fundamental element for load management. In this study, we collects many types of energy usage data of electric appliances, analyze their load curves, and make the general load patterns for electrical appliance.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.989-995
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• 2017

As is known to all that the output of wind power generation has a character of randomness and volatility because of the influence of natural environment conditions. At present, the research of wind power prediction mainly focuses on point forecasting, which can hardly describe its uncertainty, leading to the fact that its application in practice is low. In this paper, a wind power range prediction model based on the multiple output property of BP neural network is built, and the optimization criterion considering the information of predicted intervals is proposed. Then, improved Particle Swarm Optimization (PSO) algorithm is used to optimize the model. The simulation results of a practical example show that the proposed wind power range prediction model can effectively forecast the output power interval, and provide power grid dispatcher with decision.