• 정보보호학회논문지
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• 제23권2호
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• pp.279-286
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• 2013

최근 전력 수요의 급증으로 인한 전력난은 효율적 전력 사용을 위한 스마트그리드 기술의 중요성을 부각시키고 있다. 스마트그리드 네트워크의 필수구성요소인 스마트미터기의 가용성 취약점에 대한 실험적 내용이 보고되고 있다. 따라서 안전한 스마트그리드의 실현가능성을 위한 가용성 보호 메커니즘 고안이 필수불가결하다. 본 논문에서는 스마트그리드 구조 및 트래픽패턴의 특징 분석을 통해 스마트미터기에 대한 가용성 침해 공격을 탐지하고, 이상 트래픽을 발생하는 공격노드를 검출할 수 있는 메커니즘을 제안한다. 제안하는 탐지 메커니즘은 공격 탐지를 수행하는 시스템의 탐지 부하를 줄이고 적은 샘플 수에도 높은 탐지율을 제공하기 위해 근사엔트로피 기법을 사용한다. 또한 공격노드가 공격트래픽에서 변경할 수 없는 물리정보(CIR 또는 RSSI 등)를 이용하여 공격 탐지 및 공격노드 검출을 수행한다. 마지막으로 본 논문 제안 기법에 대한 시뮬레이션 결과, 탐지 성능과 실현가능성을 보인다.

• International journal of advanced smart convergence
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• 제9권4호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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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.

• 전기학회논문지
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• 제62권10호
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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.

• 정보보호학회논문지
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• 제23권4호
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• pp.639-653
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• 2013

스마트 그리드는 기존 전력망에 IT 기술을 접목하여 에너지 효율을 최적화하는 차세대 지능형 전력망으로 미국, 유럽, 일본 등 전 세계적으로 기술개발이 이루어지고 있으며 실증사업을 추진하고 있다. 최근 스마트 그리드에 대한 공격 사례가 증가되고 있으며 개인정보의 사용 및 유출의 피해가 높아지고 있다. 전력망이 더욱 복잡해지고 상호 연결됨에 따라 보안 분석과 평가에 대한 노력이 점차 중요해지고 있다. 본 논문에서는 스마트 그리드의 핵심 기술인 AMI(Advanced Metering Infrastructure)의 공격과 공격에 대한 대응책을 ACT(Attack Countermeasure Tree)를 이용하여 모델링 하였다. 보안 분석은 확률이 있는 경우와 확률이 없는 경우로 나누어서 수행하였다. 이러한 모델을 가지고 SHARPE(Symbolic Hierarchical Automated Reliability and Performance Evaluator)로 구현하여 다양한 경우의 확률과 ROA, ROI, Structure Importance, Birnbaum Importance에 대해 계산하였다.

• Journal of Power Electronics
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• 제19권5호
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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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• 제12권2호
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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.

• 한국위성정보통신학회논문지
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• 제10권1호
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• pp.44-48
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• 2015

스마트그리드는 전력망에 정보기술을 접목하여, 전력공급자와 소비자가 양방향으로 실시간 정보를 교환, 에너지효율을 최적화하며 새로운 부가가치를 창출하는 차세대 전력망이다. 본 논문에서는 스마트그리드 환경 하에서 수요반응 통신시스템에 사용되는 프로토콜을 알아보고 수용반응 프로토콜을 이용한 수요반응 시스템을 구현하고 에어컨 제어를 통한 전력감소를 하는 수요반응 시나리오를 실험하였다.

• 산업기술연구
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• 제30권A호
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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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• 제12권3호
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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.