• Title/Summary/Keyword: Demand-Supply Model

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Application of MODSIM Model for Construction and Analysis of Supply and Demand System (물수급체계 구축과 분석을 위한 MODSIM 모형의 적용성 검토)

  • Oh, Ji-Hwan;Kim, Yeon-Su;Ryoo, Kyong Sik
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.404-404
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    • 2019
  • 우리나라는 수자원장기종합계획과 유역종합치수계획의 수립을 통해 수자원의 개발, 안정적인 공급과 효율적인 배분, 홍수재해방지 등을 위한 많은 노력을 해왔다. 최근에는 수자원의 관리효율화, 체계적 통합적으로 시행하고자 수자원법을 제정하여 수자원 관리의 체계를 개편하였으며, 향후 지자체 중심의 정량적인 물수급평가를 통해 현실적인 결과와 대안을 마련하는 것이 필요하다. 기존의 용수공급능력 평가와 물수급계획은 시 군 중심의 용수수요량을 바탕으로 중권역 단위로 확장하고, K-WEAP(Korea-Water Evaluation And Planing System) 모형을 활용하여 용수수급전망을 제시하고 있다. 이에 본 연구에서는 한강 권역을 중심으로 기존 계획에서 활용한 K-WEAP과 국내 외 활용도가 높은 MODSIM(Modified SIMYLD)을 활용하여 각 모형에 대한 입력자료, 내부 계산 알고리즘 및 분석방법 등 모형의 적용성을 검토하여 중권역 기반의 물수급 분석 결과를 비교 하였으며, 향후 모형 적용 시 고려사항 및 발생 가능한 오류를 최소화 할 수 있도록 하고자 하였다. 분석 결과, 기존 수자원장기종합계획에서 활용한 K-WEAP모형은 생 공 농업용수가 모두 동일우선순위이나, MODSIM모형에서는 수요지별 우선순위를 고려해야 하므로 상 하류간, 생활 공업, 농업으로 우선순위를 부여할 경우 물 부족량의 차이가 발생하였다. 우선순위 적용시 K-WEAP과 형과 MODSIM을 비교할 경우, 유사한 물부족량과 시점을 제공하고 있어 적용성과 분석결과의 일관성을 확인할 수 있었다. 또한 같은 물부족 결과를 제공하는 조건의 검토 수행 시간 측면과 모형구동 결과의 안정성에서 MODSIM이 더 우수한 것으로 분석되어 향후 지자체 중심의 세부적인 물수급평가를 위해서는 빠른 의사결정을 도울 수 있을 것으로 판단된다.

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Probabilistic evaluation of ecological drought in forest areas using satellite remote sensing data (인공위성 원격 감지 자료를 활용한 산림지역의 생태학적 가뭄 가능성에 대한 확률론적 평가)

  • Won, Jeongeun;Seo, Jiyu;Kang, Shin-Uk;Kim, Sangdan
    • Journal of Korea Water Resources Association
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    • v.54 no.9
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    • pp.705-718
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    • 2021
  • Climate change has a significant impact on vegetation growth and terrestrial ecosystems. In this study, the possibility of ecological drought was investigated using satellite remote sensing data. First, the Vegetation Health Index was estimated from the Normalized Difference Vegetation Index and Land Surface Temperature provided by MODIS. Then, a joint probability model was constructed to estimate the possibility of vegetation-related drought in various precipitation/evaporation scenarios in forest areas around 60 major ASOS sites of the Meteorological Administration located throughout Korea. The results of this study show the risk pattern of drought related to forest vegetation under conditions of low atmospheric moisture supply or high atmospheric moisture demand. It also identifies the sensitivity of drought risks associated with forest vegetation under various meterological drought conditions. These findings provide insights for decision makers to assess drought risk and develop drought mitigation strategies related to forest vegetation in a warming era.

Development of optimum pump operation technique for the damage rate reduction of water distribution system (상수도관망의 피해율 저감을 위한 가압장 최적운영기법 개발)

  • Kwon, Hyuk Jae
    • Journal of Korea Water Resources Association
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    • v.52 no.5
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    • pp.373-380
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    • 2019
  • In this study, the optimum pump operation technique is suggested to decrease the damage rate of water distribution system. Pump operation system was developed to achieve the effective pump operation. Pressure sensors which can communicate with pumps are installed at the end of water distribution system. Pump operation system can control the pressure of water pump according to data sent from the pressure sensors. Therefore, water distribution system can reduce the pressure and maintain enough pressure which can supply the demand of water users. For proving effectiveness of new system, reliability model was introduced to compare the results of damage rates between the maintaining high pressure and selective pressure in water pump. Unsteady analysis was conducted with several scenarios. And the results were used to calculate the probability of pipe breakage. From the results, it was found that new pump operation system can reduce the energy usage and probability of pipe breakage by applying to pumps.

KAB: Knowledge Augmented BERT2BERT Automated Questions-Answering system for Jurisprudential Legal Opinions

  • Alotaibi, Saud S.;Munshi, Amr A.;Farag, Abdullah Tarek;Rakha, Omar Essam;Al Sallab, Ahmad A.;Alotaibi, Majid
    • International Journal of Computer Science & Network Security
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    • v.22 no.6
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    • pp.346-356
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    • 2022
  • The jurisprudential legal rules govern the way Muslims react and interact to daily life. This creates a huge stream of questions, that require highly qualified and well-educated individuals, called Muftis. With Muslims representing almost 25% of the planet population, and the scarcity of qualified Muftis, this creates a demand supply problem calling for Automation solutions. This motivates the application of Artificial Intelligence (AI) to solve this problem, which requires a well-designed Question-Answering (QA) system to solve it. In this work, we propose a QA system, based on retrieval augmented generative transformer model for jurisprudential legal question. The main idea in the proposed architecture is the leverage of both state-of-the art transformer models, and the existing knowledge base of legal sources and question-answers. With the sensitivity of the domain in mind, due to its importance in Muslims daily lives, our design balances between exploitation of knowledge bases, and exploration provided by the generative transformer models. We collect a custom data set of 850,000 entries, that includes the question, answer, and category of the question. Our evaluation methodology is based on both quantitative and qualitative methods. We use metrics like BERTScore and METEOR to evaluate the precision and recall of the system. We also provide many qualitative results that show the quality of the generated answers, and how relevant they are to the asked questions.

Survey on Deep learning-based Content-adaptive Video Compression Techniques (딥러닝 기반 컨텐츠 적응적 영상 압축 기술 동향)

  • Han, Changwoo;Kim, Hongil;Kang, Hyun-ku;Kwon, Hyoungjin;Lim, Sung-Chang;Jung, Seung-Won
    • Journal of Broadcast Engineering
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    • v.27 no.4
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    • pp.527-537
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    • 2022
  • As multimedia contents demand and supply increase, internet traffic around the world increases. Several standardization groups are striving to establish more efficient compression standards to mitigate the problem. In particular, research to introduce deep learning technology into compression standards is actively underway. Despite the fact that deep learning-based technologies show high performance, they suffer from the domain gap problem when test video sequences have different characteristics of training video sequences. To this end, several methods have been made to introduce content-adaptive deep video compression. In this paper, we will look into these methods by three aspects: codec information-aware methods, model selection methods, and information signaling methods.

Estimation of Physical Climate Risk for Private Companies (민간기업을 위한 물리적 기후리스크 추정 연구)

  • Yong-Sang Choi;Changhyun Yoo;Minjeong Kong;Minjeong Cho;Haesoo Jung;Yoon-Kyoung Lee;Seon Ki Park;Myoung-Hwan Ahn;Jaehak Hwang;Sung Ju Kim
    • Atmosphere
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    • v.34 no.1
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    • pp.1-21
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    • 2024
  • Private companies are increasingly required to take more substantial actions on climate change. This study introduces the principle and cases of climate (physical) risk estimation for 11 private companies in Korea. Climate risk is defined as the product of three major determinants: hazard, exposure, and vulnerability. Hazard is the intensity or frequency of weather phenomena that can cause disasters. Vulnerability can be reflected in the function that explains the relationship between past weather records and loss records. The final climate risk is calculated by multiplying the function by the exposure, which is defined as the area or value of the target area exposed to the climate. Future climate risk is estimated by applying future exposure to estimated future hazard using climate model scenarios or statistical trends based on weather data. The estimated climate risks are developed into three types according to the demand of private companies: i) climate risk for financial portfolio management, ii) climate risk for port logistics management, iii) climate risk for supply chain management. We hope that this study will contribute to the establishment of the climate risk management system in the Korean industrial sector as a whole.

Optimization Process Models of Gas Combined Cycle CHP Using Renewable Energy Hybrid System in Industrial Complex (산업단지 내 CHP Hybrid System 최적화 모델에 관한 연구)

  • Oh, Kwang Min;Kim, Lae Hyun
    • Journal of Energy Engineering
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    • v.28 no.3
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    • pp.65-79
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    • 2019
  • The study attempted to estimate the optimal facility capacity by combining renewable energy sources that can be connected with gas CHP in industrial complexes. In particular, we reviewed industrial complexes subject to energy use plan from 2013 to 2016. Although the regional designation was excluded, Sejong industrial complex, which has a fuel usage of 38 thousand TOE annually and a high heat density of $92.6Gcal/km^2{\cdot}h$, was selected for research. And we analyzed the optimal operation model of CHP Hybrid System linking fuel cell and photovoltaic power generation using HOMER Pro, a renewable energy hybrid system economic analysis program. In addition, in order to improve the reliability of the research by analyzing not only the heat demand but also the heat demand patterns for the dominant sectors in the thermal energy, the main supply energy source of CHP, the economic benefits were added to compare the relative benefits. As a result, the total indirect heat demand of Sejong industrial complex under construction was 378,282 Gcal per year, of which paper industry accounted for 77.7%, which is 293,754 Gcal per year. For the entire industrial complex indirect heat demand, a single CHP has an optimal capacity of 30,000 kW. In this case, CHP shares 275,707 Gcal and 72.8% of heat production, while peak load boiler PLB shares 103,240 Gcal and 27.2%. In the CHP, fuel cell, and photovoltaic combinations, the optimum capacity is 30,000 kW, 5,000 kW, and 1,980 kW, respectively. At this time, CHP shared 275,940 Gcal, 72.8%, fuel cell 12,390 Gcal, 3.3%, and PLB 90,620 Gcal, 23.9%. The CHP capacity was not reduced because an uneconomical alternative was found that required excessive operation of the PLB for insufficient heat production resulting from the CHP capacity reduction. On the other hand, in terms of indirect heat demand for the paper industry, which is the dominant industry, the optimal capacity of CHP, fuel cell, and photovoltaic combination is 25,000 kW, 5,000 kW, and 2,000 kW. The heat production was analyzed to be CHP 225,053 Gcal, 76.5%, fuel cell 11,215 Gcal, 3.8%, PLB 58,012 Gcal, 19.7%. However, the economic analysis results of the current electricity market and gas market confirm that the return on investment is impossible. However, we confirmed that the CHP Hybrid System, which combines CHP, fuel cell, and solar power, can improve management conditions of about KRW 9.3 billion annually for a single CHP system.

The Development of an Aggregate Power Resource Configuration Model Based on the Renewable Energy Generation Forecasting System (재생에너지 발전량 예측제도 기반 집합전력자원 구성모델 개발)

  • Eunkyung Kang;Ha-Ryeom Jang;Seonuk Yang;Sung-Byung Yang
    • 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.

Groundwater-use Estimation Method Based on Field Monitoring Data in South Korea (실측 자료에 기반한 우리나라 지하수의 용도별 이용량 추정 방법)

  • Kim, Ji-Wook;Jun, Hyung-Pil;Lee, Chan-Jin;Kim, Nam-Ju;Kim, Gyoo-Bum
    • The Journal of Engineering Geology
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    • v.23 no.4
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    • pp.467-476
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    • 2013
  • With increasing interest in environmental issues and the quality of surface water becoming inadequate for water supply, the Korean government has launched a groundwater development policy to satisfy the demand for clean water. To drive this policy effectively, it is essential to guarantee the accuracy of sustainable groundwater yield and groundwater use amount. In this study, groundwater use was monitored over several years at various locations in Korea (32 cities/counties in 5 provinces) to obtain accurate groundwater use data. Statistical analysis of the results was performed as a method for estimating rational groundwater use. For the case of groundwater use for living purposes, we classified the cities/counties into three regional types (urban, rural, and urban-rural complex) and divided the groundwater facilities into five types (domestic use, apartment housing, small-scale water supply, schools, and businesses) according to use. For the case of agricultural use, we defined three regional types based on rainfall intensity (average rainfall, below-average rainfall, and above-average rainfall) and the facilities into six types (rice farming, dry-field farming, floriculture, livestock-cows, livestock-pigs, and livestock-chickens). Finally, we developed groundwater-use estimation equations for each region and use type, using cluster analysis and regression model analysis of the monitoring data. The results will enhance the reliability of national groundwater statistics.

Predicting Raw Material Price Fluctuation Using Signal Approach: Application to Non-ferrous Metals (신호접근법을 이용한 비철금속 상품가격변동 예측모형 연구)

  • Kim, Ji-Whan;Lee, Sang-Ho
    • Economic and Environmental Geology
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    • v.42 no.2
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    • pp.143-152
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    • 2009
  • Recent raw material prices fluctuation has been unexpectedly high and that made Korean economic activities to be depressed. Because most raw material supply in Korea depends upon oversea imports, unexpected raw material price fluctuation affects Korean industrial economies through macroeconomic variables. So Korean government enforces some political measures such as demand management and the supply-security assurance as long-range policies, and reservation and general early warning system as short-range policies. In short-range policies, it is necessary to be expected short term fluctuation. Up to recently, there have been many researches and most of those researches use parametric methods or time series analyses. Because those methods and analyses often generate inadequate relations among variables, it is possible that some consistent variables are left out or the results are misunderstood. This study, therefore, is aim to mitigate those methodological problems and find the relatively appropriate model for economic explanation. So that, in this paper, by using non-parametric signal approach method mitigating some shortages of previous researches and forecasting properly short-range prices fluctuation of non-ferrous materials are presented empirically.