• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.229-256
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• 2023

The increase in telecommuting and household electricity demand due to the pandemic has led to significant changes in electricity demand patterns. This has led to difficulties in identifying KEPCO's PPA (power purchase agreements) and residential solar power generation and has added to the challenges of electricity demand forecasting and grid operation for power exchanges. Unlike other energy resources, electricity is difficult to store, so it is essential to maintain a balance between energy production and consumption. A shortage or overproduction of electricity can cause significant instability in the energy system, so it is necessary to manage the supply and demand of electricity effectively. Especially in the Fourth Industrial Revolution, the importance of data has increased, and problems such as large-scale fires and power outages can have a severe impact. Therefore, in the field of electricity, it is crucial to accurately predict the amount of power generation, such as renewable energy, along with the exact demand for electricity, for proper power generation management, which helps to reduce unnecessary power production and efficiently utilize energy resources. In this study, we reviewed the renewable energy generation forecasting system, its objectives, and practical applications to construct optimal aggregated power resources using data from 169 power plants provided by the Ministry of Trade, Industry, and Energy, developed an aggregation algorithm considering the settlement of the forecasting system, and applied it to the analytical logic to synthesize and interpret the results. This study developed an optimal aggregation algorithm and derived an aggregation configuration (Result_Number 546) that reached 80.66% of the maximum settlement amount and identified plants that increase the settlement amount (B1783, B1729, N6002, S5044, B1782, N6006) and plants that decrease the settlement amount (S5034, S5023, S5031) when aggregating plants. This study is significant as the first study to develop an optimal aggregation algorithm using aggregated power resources as a research unit, and we expect that the results of this study can be used to improve the stability of the power system and efficiently utilize energy resources.

• Journal of Energy Engineering
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• v.25 no.4
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• pp.93-102
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• 2016

Vehicle-to-Grid (V2G) system, bi-direction power trading technology, enables drivers possessing electric vehicle to sell the spare electricity charged in the vehicle to power distribution company. The drivers gain profit by charging electricity in the day time of high electricity rate. In this regard, the government is preparing the policies of building and supporting V2G infrastructure and demanding the potential consumers' preference for the V2G system. This paper attempts to analyze the consumers' preference using the data from obtained a survey of randomly selected 1,000 individuals. To this end, choice experiment, an economic technique, is employed here. The attributes considered in the study are residual amount of electricity, electricity trading hours, required plug-in time, and price measured as an amount additional to current gasoline vehicle price. The multinomial logit model, which requires the assumption of 'independence of irrelevant alternatives', is applied but the assumption could not be satisfied in our data. Thus, we finally utilized nested logit model which does not require the assumption. All the parameter estimates in the utility function are statistically significant at the 10% level. The estimation results show that the marginal willingness to pay (MWTP) for one hour increase in electricity trading hours is estimated to be KRW 1,601,057. On the other hand, a one percent reduction in residual amount of electricity and one hour reduction in required plug-in time in V2G system are computed to be KRW -91,911 and -470,619, respectively. The findings can provide policy makers with useful information for decision-making about introducing and managing V2G system.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.99-106
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• 2002

Researches on integration of design and construction information from earlier era focused on the conceptual data models. Development and prevalent use of commercial database management system led many researchers to design database schemas for enlightening of relationship between non-graphic data items. Although these researches became the foundation fur the proceeding researches. they did not utilize the graphic data providable from CAD system which is already widely used. 4D CAD concept suggests a way of integrating graphic data with schedule data. Although this integration provided a new possibility for integration, there exists a limitation in data dependency on a specific application. This research suggests a new approach on integration for design and construction information, 'Product Model Centered Integration Methodology'. This methodology achieves integration by preliminary research on existing methodology using 4D CAD concept. and by development and application of new integration methodology, 'Product Model Centered Integration Methodology'. 'Design Component' can be converted into digital format by object based CAD system. 'Unified Object-based Graphic Modeling' shows how to model graphic product model using CAD system. Possibility of reusing design information in latter stage depends on the ways of creating CAD model, so modeling guidelines and specifications are suggested. Then prototype system for integration management, and exchange are presented, using 'Product Frameworker', and 'Product Database' which also supports multiple-viewpoints. 'Product Data Model' is designed, and main data workflows are represented using 'Activity Diagram', one of UML diagrams. These can be used for writing programming codes and developing prototype in order to automatically create activity items in actual schedule management system. Through validation processes, 'Product Model Centered Integration Methodology' is suggested as the new approach for integration of design and construction information.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.867-879
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• 2020

As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.225-234
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• 2015

Nowadays a Virtual Power Plant (VPP) represents an aggregation of distributed energy resource such as Distributed Generation (DG), Combined Heat and Power generation (CHP), Energy Storage Systems (ESS) and load in order to operate as a single power plant by using Information and Communication Technologies, ICT. The VPP has been developed and verified based on a single virtual plant platform which is connected with a number of various distributed energy resources. As the VPP's distributed energy resources increase, so does the number of data from distributed energy. Moreover, it is obviously inefficient in the aspects of technique and cost that a virtual plant platform operates in a centralized manner over widespread region. In this paper the concept of the large-scale VPP which can reduce a error probability of system's load and increase the robustness of data exchange among distributed energy resources will be proposed. In addition, it can directly control and supervise energy resource by making small size's virtual platform which can make a optimal resource scheduling to consider of variable and sensitive load in the large-scale VPP. It makes certain the result is verified by simulation.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.10a
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• pp.99-100
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• 2004

AMBIDEXTER-NEC의 천이노심은 $^{Nat}Th$과 $^{Nat}U$의 주입만으로 전 출력의 Break-even 노심에 도달하기위한 중간 단계이다. 선행연구에서 수행한 전 출력노심인 평형노심의 핵종수밀도에 도달하기 위해서 평형노심에서의 기저물질, 잠재핵분열성물질, 핵분열물질의 수밀도를 각 SEU-기반, Pu-기반, ADS-기반에서 그대로 유지하여 초기노심을 구성하였다. 또 각 시나리오에 대해 최대첨두출력과 원자로의 안전성을 고려해 Excess Reactivity를 5mk 내에서 초기노심을 결정하였다. 각 노심은 주 핵분열성물질 $^{235}U$, $^{239}Pu$ 및 $^{233}U$의 핵반응단면적 특성에 따라 평균 전환율이 각각 0.95, 0.83 및 1 .21 로서 핵연료물질의 적절한 선택만으로도 전환로, 연소로 및 증식로로 설계할 수 있음을 보여준다. 이러한 $Th/^{233}U$, U/Pu 핵연료주기를 사용하는 AMBIDEXTER-NEC 용융염핵연료 원자로의 초기노심에서 시작한 천이노심은 평형노심에장전할 충분한 $^{233}U$ 양을 확보해야 하므로 천이노심의 목표는 평형노심 $^{233}U$의 요구량에 최소한의 기간에 가장 적은 외부주입을 통해 도달하는 것이다. 천이노심에서 임계가 유지되는 AMBIDEXTER-NEC 원자로시스템의 3군 핵종변환 코드인 HELIOS-SQUID-AMBIBURN 체제를 개발하였고 그림 1.에 나타내었다. 이 알고리즘은 각 초기노심 중원소의 미시단면적, 중원소를 제외한 원소들의 거시단면적, 임계도를 만족하는 중성자속 및 외부주입율을 계산하여 SQUID 및 AMBIBURN 입력자료를 제공한다. 또한 일정시간 중원소의 핵종농도, 외부주입율과 중성자속이 일정하다는 가정 하 에 반복수행 하고 SEU-기반과 Pu-기반의 경우에는 각각 핵변환을 거쳐 재순환되는 $^{233}U$ 및 $^{239}Pu$의 양을 바로 주입하는 최대재순환 경우와 평형노심 요구 장전량에 이를 때까지 시설 내 저장하는 최소재순환 경우로 상황을 모사하였다. 그림 2 는 각 시나리오별 초기노심에서부터 200FPD까지 단위 용융염 체적당 $^{233}U$의 수밀도 시간변화를 나타낸 것이다. 그림을 보면 50일 이후부터는 수밀도의 변화가 일정한 기울기를 보이고 있고 재처리공정에서 $^{233}Pa$를 분리하는 최소재순환의 경우에는 최대재순환보다 2-3%정도에 지나지않아 그림에서 나타내지않았다. SEU-기반 및 Pu-기반에서 $^{233}U$의 증가율이 각각 2.54E+13, 2.81E+13 #/cc/d 로 Pu 기반이 조금 더 큰 증가율을 나타내고 있지만 평형노심 농도 1.04E+20 #/cc/d 에 도달하기 위해서는 두 경우 모두 매우 긴 시간이 걸릴 것을 예상할 수 있다. 요컨대 250MWth AMBIDEXTER-NEC가 평형노심을 이루기 위해 필요로 하는 $^{233}U$을 생산하는데 제안한 SEU-기반, Pu-기반 시나리오는 천이노심주기기간이 전형적인 원자로 수명 3-40년 보다 매우 큰 것으로 나타났다. 따라서 장전될 $^{233}U$의 확보를 위한 최적옵션은 초기노심부터 ADS와 같은 외부생산시설로부터 전량을 공급 받아 운전하는 것이라 판단된다.

• Journal of Bio-Environment Control
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• v.27 no.1
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• pp.27-33
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• 2018

This study was performed to review the domestic and international smart farm service model based on the convergence of agriculture and information & communication technology and derived various factors needed to improve the Korean smart greenhouse. Studies on modelling of crop growth environment in domestic smart farms were limited. And it took a lot of time to build research infrastructure. The cloud-based research platform as an alternative is needed. This platform can provide an infrastructure for comprehensive data storage and analysis as it manages the growth model of cloud-based integrated data, growth environment model, actuators control model, and farm management as well as knowledge-based expert systems and farm dashboard. Therefore, the cloud-based research platform can be applied as to quantify the relationships among various factors, such as the growth environment of crops, productivity, and actuators control. In addition, it will enable researchers to analyze quantitatively the growth environment model of crops, plants, and growth by utilizing big data, machine learning, and artificial intelligences.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.403-410
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• 2015

Since 1970, MRI has greatly been developing in terms of strength of magnetic field, the number of receipt channels, and short time of examination. With the development of digital systems and wireless network, hospitals have also acquired, saved, and managed digital images taken by various kinds of medical imaging equipment. However, domestic universities fail to provide practice training course independently thanks to expensive practice equipment and high maintenance cost, and rely on clinical training. Therefore, this study developed a MR patient diagnosis program based on Windows PC to help out students before their working in clinical filed. The designed Relational Database of MRI Simulator is made up of seven tables according to functions and data characteristics. Regarding the designed patient information, each stepwise function was classified by the patient registration method in clinical field. In addition, on the assumption of the basic information for diagnosis, each setting and content were classified. The menu by execution step was arrayed on the left side for easy view. For patient registration, a patient's name, gender, unique ID, birth date, weight, and other types of basic information were entered, and the patient's posture and diagnosis direction were set up. In addition, the body regions for diagnosis and Pulse Sequence were listed for selection. Also, Protocol name and other additional factors were allowed to be entered. The final window was designed to check diagnosis images, patient information, and diagnosis conditions. By learning how to enter patient information and change diagnosis conditions in this program, users will be able to understand more theories and terms learned in practice and thereby to shorten their learning time in actual clinical work.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.1051-1056
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• 2007

In current web-based systems, it is generally recognized that one way flow of information from providers to users can cause the static problem of document structure. Therefore, information update frequency and interaction between providers and users are quiet slow. Monopolized information can obstruct the free user's access and heterogeneous format and different protocols also make users difficult to retrieve and to collect information. To resolve these problems, in this study, we introduce the Web 2.0 to move toward the user's participation and share based on the social network and the OAI protocol to improve the free access and the interoperability on bibliographic information for Life Science and then design the bibliographic information network for life science. This network has four main functions such as: 1) Open Repository function that can make up user community for sharing and data exchange. Data such as article, seminar material, research note and research report are considered in design. 2) Open Collection function that can collect and store the metadata on distributed bibliographic information networks, 3) Open Access function that can manage the metadata in the open access environment, and 4) Administration function that can monitor the user activity and statistics and can inspect the registered data.