• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.2
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• pp.319-328
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• 2013

Considerable number of major countries have put great efforts to leverage the efficiency of power consumption using Smart Grid in order to resolve the critical issues with drastical growing demands regarding electricity, the crisis of environmental pollution and so on. There has been increasing number of researches to construct Smart Grid in Korea as well. The threats of cyber terror attacks which might cause national crisises in terms of economy and society have been climbing up because of the fact that Smart Grid employs bi-directional communications embedding the cyber threats from existing/legacy communication networks. Consequently, it is required to build concrete response processes including investigation and analysis on cyber breaches into Smart Grid. However, the digital evidence acquisition techniques do not suffice to be deployed in Smart Grid systems despite of the fact that the techniques, against cyber breaches into well-known networks, have been studied in plenty of time. This work proposes a novel digital evidence acquisition scheme appropriate to Smart Grid systems through intensive investigation of the evidence acquisition requirements in Smart Grid and the historical evidence acquisition methods.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.8-19
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• 2020

We see an energy fucused smart city evolution of the UK along with the project of "Smart London Plan (SLP)." A theoretical logic of business model innovation has been discussed and a research framework of evolving energy focused smart city is formulated. The starting point is the silo system. In the second stage, the private investment in smart meters establishes a basement for next stages. As results, the UK's smart energy sector has evolved from smart meter installation through smart grid to new business models such as water-energy nexus and microgrid. Before smart meter installation of the government, the electricity system was centralized. However, after consumer engagement plan has been set to make them understand benefits that they can secure through smart meters, the customer behavior has been changed. The data analytics firm enables greater understanding of consumer behavior and it helps energy industry to be smart via controlling, securing and using that data to improve the energy system. In the third stage, distribution network operators (DNOs)' access to smart meter data has been allowed and the segmentation starts. In the fourth stage, with collaboration of Ofwat and Ofgem, it is possible to eliminate unnecessary duplication of works and reduce interest conflict between water and electricity. In the fifth stage, smart meter and grid has been integrated as an "adaptive" system and a transition from DNO to DSO is accomplished for the integrated operation. Microgrid is a prototype for an "adaptive" smart grid. Previous steps enable London to accomplish a platform leadership to support the increasing electrification of the heating and transport sector and smart home.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.109.1-109.1
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• 2011

KEPCO was operating power plants with diesel generators in 49 islands including Baekryeong-Do, and the generation capacity was about 66 MW in 2008. The cost of fuel is increasing by the international oil price inflation and continuous rise of oil price is predicted. For the stabilizing of electric power supply to the separate islands, renewable energy and fuel cell systems were considered. Hydrogen is made using renewable energy such as wind power and solar energy, and then a fuel cell system generates electricity with the stored hydrogen. Though the system efficiency is low, it is treated as the only way to secure the stable electric supply using renewable energy at this present. The analytic hierarchy process was used to select suitable candidate island for the system installation and 5 islands including Ulleung-Do were selected. Economic evaluation for the system composed of a kerosene generator, a wind power, an electrolysis, and a fuel cell system was conducted with levelized generation cost based on present value methode. As the result, the necessity of renewable energy combined generation system and micro grid composition in the candidated islands was confirmed. Henceforth, the development of an integration technology which connects micro grid to the total power grid will be needed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.5 s.122
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• pp.448-455
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• 2007

As Decentralized Generation(DG) becomes more reliable and economically feasible, it is expected that a higher application of DG units would be interconnected to the existing grids. This new market penetration of DG technologies is linked to a large number of factors like technologies costs and performances, interconnection issues, safety, market regulations, environmental issues or grid connection constrains. This paper describes the procedures and results for the mechanical, electrical, and environmental tests of MGT on actual grid-connection under Korean regulations. As one of the achievements, the simulation model of MGT was developed, so that it will be able to analyze or propose new distributed generation system using MGT. The field test was conducted in order to respond to a wide variety of needs for noise reduction and utilization and its performance was evaluated in consideration of its operational problems. The MGT is successfully supplying electricity to Korean grids with satisfying various regulations. The suggested strategy and experience for the evaluation of the distributed generation will be used for the introduction of other distributed generation technologies into the grid in the future.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.404-410
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• 2016

This paper proposed a program of an energy storage system(ESS) for peak shaving of high-speed railway substations The peak shaving saves cost of equipment and demand cost of the substation. To reduce the peak load, it is very important to know when the peak load appears. The past data based load profile forecasting method is easy and applicable to customers which have relatively fixed load profiles. And an optimal scheduling method of the ESS is helpful in reducing the electricity tariff and shaving the peak load efficiently. Based on these techniques, MS. NET based peak shaving program is developed. In case study, a specific daily load profile of the local substation was applied and simulated to verify performance of the proposed program.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.852-858
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• 2012

This paper describes evaluation results of the wind power penetration limit (WPPL) and the wind energy penetration (WEP) in the Mongolian central power system (MCPS). A wind power plant (WPP) in a power system possesses an output power limit because the power system must maintain a balance between the generation and consumption of electricity at all times in order to achieve an adequate level of quality. The instantaneous penetration limit (IPL) of wind generation at a load is determined as the minimum of the three technical constraints: the minimum output, the ramp rate capability, and the spinning reserve of the conventional generating units. In this paper, a WPPL is defined as the maximum IPL divided by the peak load. A maximal variation rate (VR) of wind power is a major factor in determining the IPL, WPPL, and WEP. This paper analyzes the effects of the maximal VR of wind power on the WPPL, WEP, and capacity factor (CF) in the MCPS. The results indicate that a small VR can facilitate a large amount of wind energy while maintaining a high CF with increased wind power penetration.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.27-34
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• 2014

The paper proposed a sizing method of an energy storage system(ESS) for peak shaving of high-speed railway substations based on load profile patterns of substations. A lithium based battery ESS was selected since it can produce high-power at high speed that peak shaving requires, and also takes up a relatively smaller space for installation. Adequate size of the ESS, minimum capacity which can technically meet a peak shaving target, was determined by collectively considering load patterns of a target substation, characteristics of the ESS to be installed, and optimal scheduling of the ESS. In case study, a local substation was considered to demonstrate the proposed sizing method. Also economic analysis with the determined size of ESS was performed to calculate electricity cost savings of the peak shaving ESS, and to offer pay-back period and return on investment.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.5
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• pp.414-424
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• 2015

In this research, we consider a smart grid network of electricity with multiple consumers connected to a monopolistic provider. Each consumer can be informed the real time price changes through the smart meter and updates his consumption schedule to minimize the energy consumption expenditures by which the required power demand should be satisfied under the given real time pricing scheme. This real-time decision making problem has been recently studied through game-theoretic approach. The present paper contributes to the existing literature by incorporating storage appliance into the set of available household appliances which has somewhat distinctive functions compared to other types of appliances and would be regarded to play a significant role in energy consumption scheduling for the future smart grid. We propose a game-theoretic algorithm which could draw the optimal energy consumption scheduling for each household appliances including storage. Results on simulation data showed that the storage contributed to increase the efficiency of energy consumption pattern in the viewpoint of not only individual consumer but also whole system.

• The KIPS Transactions:PartC
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• v.18C no.6
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• pp.397-404
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• 2011

Recently the existing one-way electricity system that combines information and communications technology to develop smart grid technology is made active. The core infrastructure of the smart grid, AMI smart meters to AMR system, the amount of power measured at the top to MDMS transmits data store. Smart meters utilizing information and communication technology to transfer data and power because of the existing security threats are expected, including the additional security threats. It exposes the privacy of consumers and industrial systems, such as paralysis is likely to result in the loss. In this paper to respond to these security threats in the environment smart grid. Also, We propose data transfer methods between smartmeter and MDMS and between home device and MDMS.

• 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.