• KEPCO Journal on Electric Power and Energy
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• 제7권1호
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• pp.73-77
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• 2021

As the big data analysis technologies has been developed worldwide, the importance of asset management for electric power facilities based data analysis is increasing. It is essential to secure quality of data that will determine the performance of the RISK evaluation algorithm for asset management. To improve reliability of asset management, asset data must be preprocessed. In particular, the process of cleaning dirty data is required, and it is also urgent to develop an algorithm to reduce time and improve accuracy for data treatment. In this paper, the result of the development of an automatic cleaning algorithm specialized in overhead transmission asset data is presented. A data cleaning algorithm was developed to enable data clean by analyzing quality and overall pattern of raw data.

• 전기학회논문지
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• 제66권11호
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• pp.1605-1611
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• 2017

In this study, the characteristic lifetime of power facilities such as power transformers and GIS were investigated as the basis of power facility asset management. It is difficult to obtain the operation and failure data of the facilities in Korea. Therefore, the number of failures of the electric power facilities was calculated from the operation data and hazard rate shown in the overseas literatures, and the statistical analysis was performed using the Weibull distribution function. As a result of extracting and analyzing the data of the UK National Grid for power transformers, the characteristic lifetime (scale parameter) of 116.45 years was considered to be a very appropriate value for power transformer management and can be used as a comparative data of the analysis of the domestic transformers. As for the GIS, based on the Bays and Bay-Years data and the hazard rate according to the operation years of the 123kV GIS in Germany, it is found out that the characteristic lifetime of GIS is not so meaningful. It is necessary to decide a maintenance strategy and lifetime expectancy considering the characteristics of the design, materials and manufacturing process of GIS.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 추계학술대회 논문집 전력기술부문
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• pp.113-115
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• 2004

This year korea power system had recorded highest peak load for 6 times and finally it made new peak load 51,264MW at July 29th 3:00 PM. The new peak load is increased 8.2% from the last year peak load 47,385MW and korea power system entered 50,000MW load era. The Korea Power Exchange (KPX) snapped power system data at the peak load time using state estimation function in the EMS. And authors converted the power system data at peak load to PSS/E power flow format. Using this PSS/E peak load power flow data, this paper explains demand analysis result shun capacitor operation, voltage distribution at the peak load. And the paper shows the simulation result of 2 contingency analysis using the snapped PSS/E peak load data.

• Nuclear Engineering and Technology
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• 제49권4호
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• pp.850-854
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• 2017

Public acceptance of nuclear power is important for the government, the major stakeholder of the industry, because consensus is required to drive actions. It is therefore no coincidence that the governments of nations operating nuclear reactors are endeavoring to enhance public acceptance of nuclear power, as better acceptance allows stable power generation and peaceful processing of nuclear wastes produced from nuclear reactors. Past research, however, has been limited to epistemological measurements using methods such as the Likert scale. In this research, we propose big data analysis as an attractive alternative and attempt to identify the attitudes of the public on nuclear power. Specifically, we used common big data analyses to analyze consumer opinions via SNS (Social Networking Services), using keyword analysis and opinion analysis. The keyword analysis identified the attitudes of the public toward nuclear power. The public felt positive toward nuclear power when Korea successfully exported nuclear reactors to the United Arab Emirates. With the Fukushima accident in 2011 and certain supplier scandals in 2012, however, the image of nuclear power was degraded and the negative image continues. It is recommended that the government focus on developing useful businesses and use cases of nuclear power in order to improve public acceptance.

• 한국태양에너지학회 논문집
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• 제30권3호
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• pp.25-32
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• 2010

A real-time monitoring system was developed for transfer, receive, backup and analysis of wind power data at three wind farm(Hang won, Hankyung and Sung san) in Jeju. For this monitoring system a communication system analysis, a collection of data and transmission module development, data base construction and data analysis and management module was developed, respectively. These modules deal with mechanical, electrical and environmental problem. Especially, time series graphic is supported by the data analysis and management module automatically. The time series graphic make easier to raw data analysis. Also, the real-time monitoring system is connected with wind power forecasting system through internet web for data transfer to wind power forecasting system's data base.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.410-411
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• 2007

In this paper describe for development of conversion program by EMS data acquisition. Currently EMS output data has a arbitrary bus number and incorrect bus name. It is need to delvelop converting program for using this data to analysis real power system. Conversion consist of bus number and bus name convert, machine's MBASE, X''d, Machine ID, Area, Zone Code, adding tie-line and remove small genererator that was not consider in transient stability analysis. As result of this work, the efficiency of power system analysis is increase and the result input data is used for many analysis applications.

• 대한전기학회논문지:전력기술부문A
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• 제53권5호
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• pp.257-265
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• 2004

The complex documentation involved in power system analysis software require a well-defined and friendly database system. We have developed an object-oriented database management system for power system analysis, and have described load flow analysis and transient stability analysis using object-oriented database(OODB). Database management systems are widely used and achieve high reliability of data management in the engineering fields. However relational database system have shortcomings in application to power system analysis. ill relational database, the data model is too simple for modeling complex data and database languages are very different from programming languages. Object-oriented techniques are sufficiently powerful to support data-modeling requirements of GUI applications. The GUI is implemented using C++ on a MS windows platform. The OODB supports data modeling requirements of GUI applications and the performance is well acceptable for Gill applications.

• Journal of Biosystems Engineering
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• 제20권3호
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• pp.205-216
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• 1995

A fast and inexpensive approximate analysis method to predict power output characteristics of the Stilting engines in a preliminary design stage was investigated. In basic equations proposed by Walker, typical temperatures of working fluids in expansion and compression spaces were treated as those of working fluids in heater and cooler respectively. While the temperature of working fluid in the expansion space was actually lower than that of working fluid in the heater, the temperature of working fluid in the compression space was higher than that of working fluids in the cooler. In this paper, the working fluid temperature of expansion space was treated as lower than the heater temperature and that of compression space was treated as higher than the cooler temperature. Also, according to them, the power output characteristics of the Stirling engine were evaluated with respect to the GPU-3 and 4-215 Stilting engines. The following conclusions were drawn from the analysis. 1. Using the available experimental data from the GPU-3 Stirling engine, it was shown that the approximate analysis predicts the brake power with a maximum error of 19 percent at 1, 000rpm and with a minimum error of 3 percent at 2, 000rpm. 2. The approximate analysis data which for the GPU-3 Stirling engine were much closer to the experimental data than those of adiabatic 2nd order and 3rd order analysis within 1, 500rpm to 2, 500rpm. 3. The approximate analysis data which for the GPU-3 and 4-215 Stilting engines were much closer to the experimental data than those of the Beal number analysis.

• 한국멀티미디어학회논문지
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• 제20권12호
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• pp.1960-1969
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• 2017

There have been ongoing researches to identify and analyze the patterns of electric power IoT data inside sensor nodes to supplement the stable supply of power and the efficiency of energy consumption. This study set out to propose an analysis process for electric power IoT data with the K-means algorithm, which is an unsupervised learning technique rather than a supervised one. There are a couple of problems with the old K-means algorithm, and one of them is the selection of cluster number K in a heuristic or random method. That approach is proper for the age of standardized data. The investigator proposed an analysis process of selecting an automated cluster number K through principal component analysis and the space division of normal distribution and incorporated it into electric power IoT data. The performance evaluation results show that it recorded a higher level of performance than the old algorithm in the cluster classification and analysis of pitches and rolls included in the communication bodies of utility poles.

• 한국안전학회지
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• 제27권5호
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• pp.219-223
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• 2012

For an off-site consequence analysis at nuclear power plant, MELCOR Accident Consequence Code System(MACCS) II code is widely used as a software tool. In this study, the algorithm of web-based off-site consequence analysis program(OSCAP) using the MACCS II code was developed for an Integrated Leak Rate Test (ILRT) interval extension and Level 3 probabilistic safety assessment(PSA), and verification and validation(V&V) of the program was performed. The main input data for the MACCS II code are meteorological, population distribution and source term information. However, it requires lots of time and efforts to generate the main input data for an off-site consequence analysis using the MACCS II code. For example, the meteorological data are collected from each nuclear power site in real time, but the formats of the raw data collected are different from each site. To reduce the efforts and time for risk assessments, the web-based OSCAP has an automatic processing module which converts the format of the raw data collected from each site to the input data format of the MACCS II code. The program also provides an automatic function of converting the latest population data from Statistics Korea, the National Statistical Office, to the population distribution input data format of the MACCS II code. For the source term data, the program includes the release fraction of each source term category resulting from modular accident analysis program(MAAP) code analysis and the core inventory data from ORIGEN. These analysis results of each plant in Korea are stored in a database module of the web-based OSCAP, so the user can select the defaulted source term data of each plant without handling source term input data.