• Title/Summary/Keyword: Demand-Supply Model

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Analysis of Voltage Unbalance in the Electric Railway Depot Using Two-port Network Model (4단자 회로망 모델을 이용한 전기철도 차량기지의 전압불평형 해석)

  • Chang, Sang-Hoon;Oh, Kwang-Hae;Kim, Jung-Hoon
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.50 no.5
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    • pp.248-254
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    • 2001
  • The traction power demand highly varies with time and train positions and the traction load is a large-capacity current at single phase converted from 3-phase power system. Subsequently, each phase current converted from 3-phase power system cannot be maintained in balance any longer and thus the traction load can bring about imbalance in three-phase voltage. Therefore, the exact assessment of voltage unbalance must be carried out preferentially as well as load forecast at stages of designing and planning for electric railway system. The evaluation of unbalance voltage in areas, such as electric railway depots should be a prerequisite with more accuracy. The conventional researches on voltage unbalance have dealt with connection schemes of the transformers used in ac AT-fed electric railroads system and induced formulas to briefly evaluate voltage unbalance in the system(3). These formulas are still being used widely due to their easy applicabilities on voltage unbalance evaluation. Meanwhile, they don't take into account detailed characteristics of ac AT-fed electric railroads system, being founded on some assumptions. Accordingly. accuracy still remains in question. This paper proposes a new method to more effectively estimate voltage unbalance index. In this method, numerous diverted circuits in electric railway depots are categorized in three components and each component is defined as a two-port network model. The equivalent circuit for the entire power supply system is also described into a two-port network model by making parallel and/or series connections of these components. Efficiency and accuracy in voltage unbalance calculation as well can be promoted by simplifying the circuits into two-port network models.

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Forecasting of Iron Ore Prices using Machine Learning (머신러닝을 이용한 철광석 가격 예측에 대한 연구)

  • Lee, Woo Chang;Kim, Yang Sok;Kim, Jung Min;Lee, Choong Kwon
    • Journal of Korea Society of Industrial Information Systems
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    • v.25 no.2
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    • pp.57-72
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    • 2020
  • The price of iron ore has continued to fluctuate with high demand and supply from many countries and companies. In this business environment, forecasting the price of iron ore has become important. This study developed the machine learning model forecasting the price of iron ore a one month after the trading events. The forecasting model used distributed lag model and deep learning models such as MLP (Multi-layer perceptron), RNN (Recurrent neural network) and LSTM (Long short-term memory). According to the results of comparing individual models through metrics, LSTM showed the lowest predictive error. Also, as a result of comparing the models using the ensemble technique, the distributed lag and LSTM ensemble model showed the lowest prediction.

Development and validation of BROOK90-K for estimating irrigation return flows (관개 회귀수 추정을 위한 BROOK90-K의 개발과 검증)

  • Park, Jongchul;Kim, Man-Kyu
    • Journal of The Geomorphological Association of Korea
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    • v.23 no.1
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    • pp.87-101
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    • 2016
  • This study was conducted to develop a hydrological model of catchment water balance which is able to estimate irrigation return flows, so BROOK90-K (Kongju National University) was developed as a result of the study. BROOK90-K consists of three main modules. The first module was designed to simulate water balance for reservoir and its catchment. The second and third module was designed to simulate hydrological processes in rice paddy fields located on lower watershed and lower watershed excluding rice paddy fields. The models consider behavior of floodgate manager for estimating the storage of reservoir, and modules for water balance in lower watershed reflects agricultural factors, such as irrigation period and, complex sources of water supply, as well as irrigation methods. In this study, the models were applied on Guryangcheon stream watershed. R2, Nash-Sutcliffe efficiency (NS), NS-log1p, and root mean square error between simulated and observed discharge were 0.79, 0.79, 0.69, and 4.27 mm/d respectively in the model calibration period (2001~2003). Furthermore, the model efficiencies were 0.91, 0.91, 0.73, and 2.38 mm/d respectively over the model validation period (2004~2006). In the future, the developed BROOK90-K is expected to be utilized for various modeling studies, such as the prediction of water demand, water quality environment analysis, and the development of algorithms for effective management of reservoir.

Application of the SCE-UA to Derive Zone Boundaries of a Zone Based Operation Rule for a Dam (저수지 수위 구간별 운영률의 구간 경계 도출을 위한 집합체 혼합진화 알고리즘의 적용)

  • Kang, Shinuk;Kang, Taeuk;Lee, Sangho
    • Journal of Korea Water Resources Association
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    • v.47 no.10
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    • pp.921-934
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    • 2014
  • The purpose of the study is to derive a long term reservoir operation method that is easy to understand and apply to practical use for dam operators. The zone based operation rule is a simple method to make operation decisions by criteria corresponding to storage zones. The reservoir storage levels dividing a reservoir, however, must be determined by some methods. We developed a reservoir operation model based on the zone based operation rule and the shuffled complex evolution algorithm (SCE-UA) was used to determine storage levels for zone division. The model was applied to Angat Dam in the Philippines that has trouble in water supply due to imbalance between supply and demand. We derived a zone based operation rule for Angat Dam and applied it to the reservoir simulation of Angat Dam using the historical inflow. The simulation results showed water supply deficit and power generation were improved by 34.5% and 21.2%, respectively, when compared with the historical records. The current study results may be used to derive a long term reservoir operation rule.

Demand Characteristics and Analysis of Changes in Spatial Accessibility of Public Sports Facilities (공공체육시설 수요특성 및 공간적 접근성 분석)

  • Kim, Seong-Hee;Kim, Yong-Jin
    • The Journal of the Korea Contents Association
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    • v.17 no.7
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    • pp.283-293
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    • 2017
  • This study analyzed the actual conditions of use of public sports facilities and characteristics of the users of the facilities through surveys and measured the spatial imbalance of the public sports facilities currently supplied by using gravity potential model. This study also suggests evaluation criteria that may be considered for efficient location selection by examining the change of accessibility to the facilities that meet the needs of users in the future. As the results of the questionnaire survey, unlike current usage, the users hoped for badminton, weight training and swimming. And we could confirm the demand for the expansion of the multi - purpose indoor gym which can carry out such activities in the areas. As the result of the analysis on the difference in accessibility of the public sports facility, there were some large variations in the regions. It was found that a balanced supply of facilities was needed in terms of equity. In particular, when analyzing by considering the population estimates of 2025, It is analyzed that the accessibility will be reduced to about 60% compared to that of 2015. In addition, it is evaluated as the best alternative in terms of overall efficiency that the location of the facilities should be in Munsan area where population growth is expected in the future.

A study on short-term wind power forecasting using time series models (시계열 모형을 이용한 단기 풍력발전 예측 연구)

  • Park, Soo-Hyun;Kim, Sahm
    • The Korean Journal of Applied Statistics
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    • v.29 no.7
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    • pp.1373-1383
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    • 2016
  • The wind energy industry and wind power generation have increased; consequently, the stable supply of the wind power has become an important issue. It is important to accurately predict the wind power with short-term basis in order to make a reliable planning for the power supply and demand of wind power. In this paper, we first analyzed the speed, power and the directions of the wind. The neural network and the time series models (ARMA, ARMAX, ARMA-GARCH, Holt Winters) for wind power generation forecasting were compared based on mean absolute error (MAE). For one to three hour-ahead forecast, ARMA-GARCH model was outperformed, and the neural network method showed a better performance in the six hour-ahead forecast.

Investigation of the Central Carbon Metabolism of Sorangium cellulosum: Metabolic Network Reconstruction and Quantification of Pathway Fluxes

  • Bolten, Christoph J.;Heinzle, Elmar;Muller, Rolf;Wittmann, Christoph
    • Journal of Microbiology and Biotechnology
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    • v.19 no.1
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    • pp.23-36
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    • 2009
  • In the present work, the metabolic network of primary metabolism of the slow-growing myxobacterium Sorangium cellulosum was reconstructed from the annotated genome sequence of the type strain So ce56. During growth on glucose as the carbon source and asparagine as the nitrogen source, So ce56 showed a very low growth rate of $0.23\;d^{-1}$, equivalent to a doubling time of 3 days. Based on a complete stoichiometric and isotopomer model of the central metabolism, $^{13}C$ metabolic flux analysis was carried out for growth with glucose as carbon and asparagine as nitrogen sources. Normalized to the uptake flux for glucose (100%), cells recruited glycolysis (51%) and the pentose phosphate pathway (48%) as major catabolic pathways. The Entner-Doudoroff pathway and glyoxylate shunt were not active. A high flux through the TCA cycle (118%) enabled a strong formation of ATP, but cells revealed a rather low yield for biomass. Inspection of fluxes linked to energy metabolism revealed that S. cellulosum utilized only 10% of the ATP formed for growth, whereas 90% is required for maintenance. This explains the apparent discrepancy between the relatively low biomass yield and the high flux through the energy-delivering TCA cycle. The total flux of NADPH supply (216%) was higher than the demand for anabolism (156%), indicating additional reactions for balancing of NADPH. The cells further exhibited a highly active metabolic cycle, interconverting $C_3$ and $C_4$ metabolites of glycolysis and the TCA cycle. The present work provides the first insight into fluxes of the primary metabolism of myxobacteria, especially for future investigation on the supply of cofactors, building blocks, and energy in myxobacteria, producing natural compounds of biotechnological interest.

A Study on Examining the Impact of Science and Technology Policy Mix on R&D Efficiency (과학기술정책조합이 R&D효율성에 미치는 영향 분석)

  • Woo, Chungwon;Chun, Dongphil
    • Journal of Korea Technology Innovation Society
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    • v.21 no.4
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    • pp.1268-1295
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    • 2018
  • This study examines the effects of policy mix on R&D efficiency in by using data from 2014 and 2016 Korean Innovation Survey. The DEA-Tobit analysis is used to estimate the impact of policy mix on relative R&D efficiency. As a result of the DEA analysis, the R&D efficiency of the Korean manufacturing industry firms is low, because the R&D investment has not been used effectively. According to the Tobit model, policy mix have a positive effect on R&D efficiency. In particular, the combination of market-oriented, market supply-oriented, and supply demand-oriented policy mix showed a positive relationship with R&D efficiency. R&D portfolio is necessary to improve R&D efficiencies and government has to facilitate a policy mix in view of the nature of firms and Consistency of policy tools.

A Study on the Estimation Method of Daily Load Curve for the Optimization Design and Economic Evaluation of Stand-alone Microgrids Based on HOMER Simulation in Off-Grid Limiting the Supply of Electricity (제한급전하는 오프그리드의 독립형 마이크로그리드 최적 설계 및 경제성 평가를 위한 일부하곡선 추정 방안에 관한 연구)

  • Nam, Yong-Hyun;Youn, Seok-Min;Kim, Jung-Hoon;Hwang, Sung-Wook
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.68 no.1
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    • pp.27-35
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    • 2019
  • There is a growing interest in various microgrid solutions that supply electricity 24 hours a day to off-grid areas where are not connected with the main grid, and Korea has many positive effects by constructing overseas microgrids as a country operating the emission trading scheme. Since it is not clear how to obtain load curves that is one of the inputs of the HOMER used to design a microgrid optimization plan, or it is necessary to examine whether electricity is supplied to the peak load level of the areas where have not received the electricity benefits from the viewpoint of the demand management, a methodology should be developed to know the load composition ratio and the shape of the daily load curve. In this paper, the relative coefficient and average load information for each load group obtained from the survey are used besides peak load and total average load. A mathematical model is proposed to derive the load composition ratio in the form of a Quadratic Programming and the load forecasting is performed using simple linear regression with future indicators. The effectiveness of the proposed method is confirmed for the Philippine island region supported by Korea Energy Agency and the Asian Development Bank.

A Study on the Priority of Site Selection for Hydrogen Vehicle Charging Facilities in Seoul Using a Market Demand Prediction Model (시장수요예측 모델을 활용한 서울시 수소차 충전시설의 입지선정 우선순위에 관한 연구)

  • Jin Sick, Kim;Kook Jin, Jang;Joo Yeoun, Lee;Myoung Sug, Jung
    • Journal of the Korean Society of Systems Engineering
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    • v.18 no.2
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    • pp.140-148
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    • 2022
  • Hydrogen is expected to be widely applied in most sectors within the current energy system, such as transportation and logistics, and is expected to be economically and technologically utilized as a power source to achieve vehiclebon emission reduction. In particular, the construction of hydrogen charging station infrastructure will not only support the distribution of hydrogen electric vehicles, but also play an important role in building a hydrogen logistics system. Therefore, This paper suggest additional charging infrastructure areas in Seoul with a focus on supply according to the annual average growth rate (CAGR), centering on Seoul, where hydrogen vehicles are most widely distributed. As of February 2022, hydrogen charging infrastructures were installed in Gangseo-gu, Gangdong-gu, Mapo-gu, Jung-gu, and Seocho-gu in downtown Seoul. Next, looking at the number of hydrogen vehicles by administrative dong in Seoul from 2018 to 2022, Seocho-gu has the most with 246 as of 2022, and Dongjak-gu has the highest average growth rate of 215.4% with a CAGR of 215.4%. Therefore, as a result of CAGR analysis, Dongjak-gu is expected to supply the most hydrogen vehicles in the future, and Seocho-gu currently has the most hydrogen vehicles, so it is likely that additional hydrogen charging infrastructure will be needed between Dongjak-gu and Seocho-gu.