• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2016년도 춘계학술발표대회
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• pp.567-570
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• 2016

전력수요 예측은 설비투자, 수급 안정, 구매전력비 등에 직결되는 중요한 요소이며 국가 경제에 미치는 영향이 크다. 특히 인구가 밀집한 대도시의 경우 정치, 교육, 문화, 경제적 활동들이 전력사용과 밀접한 연관이 있어 안정적인 전력공급을 위한 정확한 전력수요 예측이 필요하다. 최근 평균기온 및 국내총생산을 독립변수로 활용하여 다중회귀모형을 구성한 연구가 전국 단위 전력수요 예측에 유용한 결과를 보여주었다. 하지만 좀 더 작은 단위 지역의 전력수요를 예측할 때에는 지역마다 제반 여건에 따른 전력사용 용도가 다르므로, 그 지역의 전력수요와 상관관계가 높은 다른 변수들을 함께 고려해야 할 필요가 있다. 본 논문은 서울시 자치구별 월 단위 전력수요 예측을 위하여 과거 전력수요량을 독립변수, 평균기온, 지역내총생산, 자치구별 인구, 세대수, 지하철 승 하차 인원을 종속변수로 설정한 다중회귀모형을 구성하였다. 이를 기반으로 다양한 실험을 통해 자치구별 월간 전력수요 예측을 진행하였으며, 그 결과 이전보다 향상된 정확도를 얻을 수 있었다.

• KIEE International Transactions on Power Engineering
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• 제5A권1호
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• pp.62-69
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• 2005

The optimal design of transmission system expansion planning is an important part of the overall planning task of electric power system under competitive electricity market environments. One of main keys of the successful grid expansion planning comes from optimal reliability level/criteria decision, which should be given for constraint in the optimal expansion problem. However, it's very difficult to decide logically the optimal reliability criteria of a transmission system as well as generation system expansion planning in a society. This paper approaches a methodology for deciding the optimal reliability criteria for an optimal transmission system expansion planning. A deterministic reliability criteria, BRR (Bus Reserve Rate) is used in this study. The optimal reliability criteria, BRR/sup */, is decided at minimum cost point of total cost curve which is the sum of the utility cost associated with construction cost and the customer outage cost associated with supply interruptions for load considering bus reserve rate at load buses in long term forecasting. The characteristics and effectiveness of this methodology are illustrated by the case study using IEEE-RTS.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 C
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• pp.1668-1670
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• 2003

This paper deals with a development of the high precise measuring device of resistive leakage current for the deterioration and diagnosis of ZnO arresters. The resistive leakage current increasing with time leads to a thermally unstable state that may even experience a disaster. So, the resistive leakage current can be used as an indicator to discriminate whether the ZnO arrester blocks is in good state or in bad. The resistive leakage current measuring system with an analysis program operated with micro-processor using the time delay addition method was designed and fabricated. The proposed measuring systems for the resistive leakage current can effectively be used to develop the techniques of forecasting the deterioration of ZnO arresters in electric power systems.⨀ᔌ?؀㔳㤮㈻Ԁ䭃䑎䷗ᜒं6〰Ԁ䭃䑎䴀

• 한국시스템다이내믹스연구
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• 제6권1호
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• pp.99-123
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• 2005

Although the generation market is competitive, the power market is easily exercised the market power by one generator due to its special futures such as a limited supplier, large investment cost, transmission constraints and loss. Specially, as Korea Electric industry restructuring is similar US competitive wholesale electricity market structure which discovered the several evidences of market power abuse, when restructuring is completed the possibility that market power will be exercised is big. Market power interferes with market competitions and efficiency of system. The goal of this study is to investigate the market price effects of the potential market power and the proposed market power mitigation strategy in Korean market using the forecasting wholesale electricity market model. This modeling is developed based on the system dynamics approach. it can analyze the dynamic behaviors of wholesale prices in Korean market. And then it is expanded to include the effect of market condition changed by 'strategic behavior' and 'real time pricing.' This model can generate the overall insights regarding the dynamic impact of output withholding by old gas fire power plant bon as a marginal plant in Korean market at the macro level. Also it will give the energy planner the opportunity to create different scenarios for the future for deregulated wholesales market in Korea.

• 한국컴퓨터정보학회논문지
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• 제24권1호
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• pp.25-32
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• 2019

With the rapid development of artificial intelligence technology, the patenting activities related to the fields of AI is increasing worldwide. In particular, a share of patent filed in China has exploded in recent years and overtakes the numbers in the US. In the present study, we focus our attention on the patenting activity of China and the US. We analyzed 6,281 and 13,664 patent applications in the US and China respectively between 2008 and 2018, and belonging to the "G06F(Electric Digital Data Processing)", "G06N(Computer Systems Based on Specific Computational Models)", "H04L(Transmission of Digital Information)" and nine more relevant technological classes, as indicated by the International Patent Classification(IPC). Our analysis contributes to: first, the understanding of patent application trends from foreign countries filed in the US and China, 2) patent application status by applicants category such as companies, universities and individuals, 3) the development direction and forecasting vacant technology of AI according to main IPC code. Through the analysis of this paper, we can suggest some implications for patent research related to artificial intelligence in Korea. Plus, by analyzing the most recent patent data, we can provide important information for future artificial intelligence technology research.

• Journal of Astronomy and Space Sciences
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• 제31권2호
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• pp.149-157
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• 2014

As the prediction of geomagnetic storms is becoming an important and practical problem, conditions in the Earth's magnetosphere have been studied rigorously in terms of those in the interplanetary space. Another approach to space weather forecast is to deal with it as a probabilistic geomagnetic storm forecasting problem. In this study, we carry out detailed statistical analysis of solar wind parameters and geomagnetic indices examining the dependence of the distribution on the solar cycle and annual variations. Our main findings are as follows: (1) The distribution of parameters obtained via the superimposed epoch method follows the Gaussian distribution. (2) When solar activity is at its maximum the mean value of the distribution is shifted to the direction indicating the intense environment. Furthermore, the width of the distribution becomes wider at its maximum than at its minimum so that more extreme case can be expected. (3) The distribution of some certain heliospheric parameters is less sensitive to the phase of the solar cycle and annual variations. (4) The distribution of the eastward component of the interplanetary electric field BV and the solar wind driving function BV2, however, appears to be all dependent on the solar maximum/minimum, the descending/ascending phases of the solar cycle and the equinoxes/solstices. (5) The distribution of the AE index and the Dst index shares statistical features closely with BV and $BV^2$ compared with other heliospheric parameters. In this sense, BV and $BV^2$ are more robust proxies of the geomagnetic storm. We conclude by pointing out that our results allow us to step forward in providing the occurrence probability of geomagnetic storms for space weather and physical modeling.

• Asian Journal of Atmospheric Environment
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• 제8권1호
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• pp.25-34
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• 2014

In winter 2013, extreme air pollution by fine particulate matter ($PM_{2.5}$) in China attracted much public attention. In order to simulate the $PM_{2.5}$ pollution, the Community Multiscale Air Quality model driven by the Weather Research and Forecasting model was applied to East Asia in a period from 1 January 2013 to 5 February 2013. The model generally reproduced $PM_{2.5}$ concentration in China with emission data in the year 2006. Therefore, the extreme $PM_{2.5}$ pollution seems to be mainly attributed to meteorological (weak wind and stable) conditions rather than emission increases in the past several years. The model well simulated temporal and spatial variations in $PM_{2.5}$ concentrations in Japan as well as China, indicating that the model well captured characteristics of the $PM_{2.5}$ pollutions in both areas on the windward and leeward sides in East Asia in the study period. In addition, contribution rates of four anthropogenic emission sectors (power generation, industrial, residential and transportation) in China to $PM_{2.5}$ concentration were estimated by conducting zero-out emission sensitivity runs. Among the four sectors, the residential sector had the highest contribution to $PM_{2.5}$ concentration. Therefore, the extreme $PM_{2.5}$ pollution may be also attributed to large emissions from combustion for heating in cold regions in China.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 춘계학술대회
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• pp.629-631
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• 2015

최근 전기 사용량의 실제 수요가 예측 수요를 벗어남에 따라 나타나는 전력 수급의 불안감을 해결하기 위하여 정부는 보다 효율적인 에너지 관리에 많이 노력을 하고 있다. 2011년 국내최초의 대규모 정전사태인 블랙아웃 사태이후 현재 우리나라의 전력 설비 예비율은 10% 이하로서 전력수급위기는 반복되고 있다. 또한, 에너지 관리 시스템에 대한 관심과 수요는 사회 전 분야로 확대되고 있다. 본 논문에서는 건물 내 전력수급을 최적화하기 위해 유무선 공유기와 DDNS(Dynamic Domain Name Service)를 이용하여 전기 소비 장치의 원격제어 및 모니터링을 위한 Presonal Energy Management System 설계한다. 향후, 원격제어 및 접속에 대한 사용자의 설정을 최소화할 수 있는 방안에 대한 추가적인 연구가 필요하다.

• 산업경영시스템학회지
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• 제41권1호
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• pp.84-93
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• 2018

In this paper, we propose an Elman recurrent neural network to predict and analyze a time series of power energy consumption. To this end, we consider the volatility of the time series and apply the sample variance and the detrended fluctuation analyses to the volatilities. We demonstrate that there exists a correlation in the time series of the volatilities, which suggests that the power consumption time series contain a non-negligible amount of the non-linear correlation. Based on this finding, we adopt the Elman recurrent neural network as the model for the prediction of the power consumption. As the simplest form of the recurrent network, the Elman network is designed to learn sequential or time-varying pattern and could predict learned series of values. The Elman network has a layer of "context units" in addition to a standard feedforward network. By adjusting two parameters in the model and performing the cross validation, we demonstrated that the proposed model predicts the power consumption with the relative errors and the average errors in the range of 2%~5% and 3kWh~8kWh, respectively. To further confirm the experimental results, we performed two types of the cross validations designed for the time series data. We also support the validity of the model by analyzing the multi-step forecasting. We found that the prediction errors tend to be saturated although they increase as the prediction time step increases. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric and the gas energies.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제1권3호
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• pp.133-142
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• 2012

쿠르노 모델은 경쟁적 전력시장을 게임이론 기반으로 모델링하기 위한 대표적인 모델이다. 이전 연구에서도 쿠르노 모델을 이용하여 전력시장을 모델링 하기 위한 다양한 시도가 이루어져 왔다. 쿠르노 모델은 몇 개의 주요 발전사업자들이 경쟁하고 그로 인해 시장지배력이 존재하는 과점 시장모델에 적합하다. 쿠르노 모델로 시장을 모델링함에 있어서는 우하향 하는 수요함수의 존재가 선결되어야 한다. 과점에서 시장참여자들은 시장지배력을 활용하여 그들의 이익을 극대화하려고 노력하지만, 우하향하는 시장수요함수에 의해 매출 역시 하락하기 때문에 적당한 지점에서 이러한 시장지배력의 행사를 제한하여야 한다. 스마트그리드에서는 실시간으로 변동하는 요금제와 다양한 전산기반 툴의 활용으로 인해 이러한 수요반응이 더욱 활성화될 것이고, 이 경우 쿠르노 모델은 수요반응 솔루션의 주요 모델로 활용될 것이다. 이에 본 논문은 실제 시장에서 계량경제학적인 접근으로 전력시장의 수요곡선을 추정하는 방법에 대해 제안한다.