• Title/Summary/Keyword: Daily Operation

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Local-Generator-Based Virtual Power Plant Operation Algorithm Considering Operation Time

  • Park, Sung-Won;Park, Yong-Gi;Son, Sung-Yong
    • Journal of Electrical Engineering and Technology
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    • v.12 no.6
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    • pp.2127-2137
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    • 2017
  • A virtual power plant (VPP) is a system that virtually integrates power resources based on the VPP participating customer (VPC) unit and operates as a power plant. When VPP operators manage resources to maximize their benefits, load reduction instructions may focus on more responsive VPCs, or those producing high profitability, by using VPC resources with high operation efficiency. VPCs may thus encounter imbalance problems during operation. This imbalance in operation time would bring more participation for some VPCs, causing potential degradation of their resources. Such an operation strategy would be not preferable for VPP operators in managing the relationship with VPCs. This issue impedes both continual VPC participation and economical and reliable VPP operation in the long term. An operation algorithm is therefore proposed that considers the operation time of VPC generators for mandatory reduction of power resource consumption. The algorithm is based on constraints of daily and annual operation times when VPP operators of local generators perform capacity-market power transactions. The algorithm maximizes the operator benefit through VPP operations. The algorithm implements a penalty parameter for imbalances in operation times spent by VPC generators in fulfilling their obligations. An evaluation was conducted on VPP operational effects by applying the algorithm to the Korean power market.

Evaluation of Travel Time Reliability using Daily Traffic Volumes (일교통량을 이용한 통행시간 신뢰도 평가)

  • Oh, Heungun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.5
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    • pp.631-638
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    • 2023
  • This paper is to introduce methodologies of travel time reliability evaluation using daily traffic volumes. The methodologies include desirable speed concept, the relation between averaged daily speeds and daily traffic volumes, the standardized way in integration of travel time deviations obtained from continuous highway sections. The study began with traffic data collection from a freeway line with long lasting congestion. And then, provided establishment of the relation between averaged daily speeds and daily traffic volumes, and usability of Point estimate method (PEM) to integrate travel time deviations of sections. Based on the relation between averaged daily speeds and daily traffic volumes, it is identified that travel time reliability begins to decrease around LOS (Level of Service) C even before LOS D or F. It may be concluded that travel time reliability could be evaluated based on daily traffic volumes in highway sections using standardized PEM. The methodologies introduced in the paper, could be useful in practicing evaluation of travel time reliability during the works of highway operation or highway planning.

Performance Characteristics of Water-to-Air Heat Pump under Partial Load Heating Operation (물-공기 히트펌프 시스템의 부분부하 난방운전 특성)

  • Cho, Yong;Lee, Nam Young;Kim, Yong Yeol;Kim, Dea Geun;Jung, Eung Tai
    • 한국신재생에너지학회:학술대회논문집
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    • 2010.06a
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    • pp.170.1-170.1
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    • 2010
  • Performance of water-to-air heat pump using raw water has been analyzed under part load heating operation in March, 2010. The water source heat pump of 30 RT was installed for 24 hours cooling and heating ventilation, and the gravity inflow water from Daechung dam is used as the heat source. The daily averaged water and air temperatures are $5.7^{\circ}C$ and $9.9^{\circ}C$ respectively, and the heat pump is operated under part load condition for 7.5 hours in 24 hours. The daily averaged heat pump COP calculated with heat transferred from the brine water is 2.49 and the monthly averaged COP is 2.25 in March. Based on the database of the California Energy Commission, the monthly averaged COPs of air source heat pumps installed in U.S.A. are 1.97 in March and 2.03 in April. Therefore it is confirmed again that the performance of the heat pump using raw water is better than that of air source heat pumps.

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Comparison of streamflow runoff model in Korea for applying to reservoir operation (저수지 운영을 위한 한국 하천 유출 모형의 비교)

  • Noh, Jae-Kyoung;Lee, Jae-Nam
    • Korean Journal of Agricultural Science
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    • v.38 no.3
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    • pp.513-524
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    • 2011
  • To evaluate the applicability of inflow runoff model to reservoir operation in Korea, DAWAST model and TPHM model which are conceptual lumped daily runoff model and were developed in Korea, were selected and applied to simulate inflows to Daecheong multipurpose dam with watershed area of 4,134 $km^2$, and water storages in Geryong reservoir with watershed area of 15.1 $km^2$ and total water storage of 3.4 M $m^3$. Evaluating inflows on an yearly, monthly, ten-day, and daily basis, inflows by DAWAST model showed balanced scatters around equal value line. But inflow by TPHM model showed high in high flows. Annual mean water balance by DAWAST model was rainfall of 1,159.9 mm, evapotranspiration of 622.1 mm, and inflow of 644.6 mm, from which rainfall was 104.8 mm less than sum of evapotranspiration and inflow, and showed unbalanced result. Water balance by TPHM model showed satisfactory result. Reservoir water storages were shown to simulate on a considerable level from applying DAWAST and TPHM models to simulate inflows to Geryong reservoir. But it was concluded to be needed to improve DAWAST and TPHM model together from imbalance of water balance and low estimation in high flow.

Optimal Reservoir Operation Models for Paddy Rice Irrigation with Weather Forecasts (I) - Generating Daily Rainfall and Evaporation Data- (기상예보를 고려한 관개용 저수지의 최적 조작 모형(I) -일강수량.일증발량 자료발생-)

  • 김병진;박승우
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.36 no.1
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    • pp.63-72
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    • 1994
  • The objective of the study is to develop weather generators for daily rainfall and small pan evaporation and to test the applicability with recorded data. Daily rainfall forecasting model(DRFM) was developed that uses a first order Markov chain to describe rainfall seque- nces and applies an incomplete Gamma function to predict the amount of precipitation. Daily evaporation forecasting model(DEFM) that adopts a normal distribution function to generate the evaporation for dry and wet days was also formulated. DRFM and DEFM were tested with twenty year weather data from eleven stations using Chi-square and Kolmogorov and Smirnov goodness of fit tests. The test results showed that the generated sequences of rainfall occurrence, amount of rainfall, and pan evaporation were statistically fit to recorded data from eleven, seven, and seven stations at the 5% level of significance. Generated rainfall data from DRFM were very close in frequency distri- bution patterns to records for stations all over the country. Pan evaporation for rainy days generated were less accurate than that for dry days. And the proposed models may be used as tools to provide many mathematical models with long-term daily rainfall and small pan evaporation data. An example is an irrigation scheduling model, which will be further detailed in the paper.

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Demonstration study of desalination system with renewable energy (신재생에너지를 이용한 해수담수시스템 실증 연구)

  • Joo, Hong-Jin;Hwang, In-Seon;Joo, Moon-Chang;Kwak, Hee-Youl
    • 한국신재생에너지학회:학술대회논문집
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    • 2010.06a
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    • pp.197.1-197.1
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    • 2010
  • This study was carried out to evaluate the operating performances of the evaporation desalination system with solar energy. This system was designed to use evacuated solar collector as the heat source, supplying the required heat energy and photovoltaic power as the electric source, supplying required power to pumps in the desalination system. The 5kW photovoltaic power generation system to make the electricity, the single-stage fresh water generator with plate heat exchanger, and remote control and monitoring system. Solar desalination system was designed and installed in Jeju-island, Korea in 2006, after about 4 years of operation, usability and stability of solar desalination system was guaranteed. The system comprises of the desalination unit which was designed to have daily fresh water capacity of $2m^3$, a $120m^2$ evacuated tubular solar collector to supply the heat, a $6m^3$ heat storage tank, and a 5.2kW photovoltaic power generation to supply the electricity to hydraulic pumps for the heat medium fluids. On a clear day, average daily solar irradiance in Jeju-island was measured to be $500W/m^2$ and the daily fresh water yield showed to be more than 500 liters under this condition. After around three years of a long term operation of the system from January 2007 to August 2009, average daily freshwater yield was analyzed to be around $330{\ell}$. The relationship equation between solar irradiance and freshwater yield was found to be y=1.1806x - 107.89.

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The Optimal Scheduling and Operational characteristics on Battery Energy Storage System (전지전력저장설비의 최적운용 및 운전특성에 관한 연구)

  • Song, Kil-Yeong;Oh, Kwang-Hae;Kim, Yong-Ha;Rho, Dae-Seok
    • Proceedings of the KIEE Conference
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    • 1993.07a
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    • pp.102-105
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    • 1993
  • The objective of this study is to solve the operation scheduling problem of plural battery energy storage systems (BESS), and to find useful intonation from its result. Unlike conventional energy storage system, BESS has on hardware characteristics such as high efficiency, fast-acting response and operational loss. Considering rate constraints of thermal unit power as well as hardware characteristics of BESS, the operation scheduling has an intricated problem. In order to solve this optimization problem, we use successive approximations dynamic programming. In two types of operation, the proposed algorithm is applied to test system. one is daily optimal operation, the other weekly optimal operation.

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Daily peak load forecasting considering the load trend and temperature (수요경향과 온도를 고려한 1일 최대전력 수요예측)

  • 최낙훈;손광명;이태기
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.15 no.6
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    • pp.35-42
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    • 2001
  • Since daily peak load forecasted data are essential to economic operation and power monitor, the technique of accurate forecasting is needled. The chief advantage of forecasting technique using neural network and fuzzy theory is high accuracy and operative implicity but the loaming time is long, and it makes large forecasting error when the load changes rapidly. This paper has resented a new forecasting technique to improve those faults and the forecasting technique prove to be valid by forcasted results.

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Development of Rainfall-Runoff forecasting System (유역 유출 예측 시스템 개발)

  • Hwang, Man Ha;Maeng, Sung Jin;Ko, Ick Hwan;Ryoo, So Ra
    • Proceedings of the Korea Water Resources Association Conference
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    • 2004.05b
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    • pp.709-712
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    • 2004
  • The development of a basin-wide runoff analysis model is to analysis monthly and daily hydrologic runoff components including surface runoff, subsurface runoff, return flow, etc. at key operation station in the targeted basin. h short-term water demand forecasting technology will be developed fatting into account the patterns of municipal, industrial and agricultural water uses. For the development and utilization of runoff analysis model, relevant basin information including historical precipitation and river water stage data, geophysical basin characteristics, and water intake and consumptions needs to be collected and stored into the hydrologic database of Integrated Real-time Water Information System. The well-known SSARR model was selected for the basis of continuous daily runoff model for forecasting short and long-term natural flows.

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A Generation and Accuracy Evaluation of Common Metadata Prediction Model Using Public Bicycle Data and Imputation Method

  • Kim, Jong-Chan;Jung, Se-Hoon
    • Journal of Korea Multimedia Society
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    • v.25 no.2
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    • pp.287-296
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    • 2022
  • Today, air pollution is becoming a severe issue worldwide and various policies are being implemented to solve environmental pollution. In major cities, public bicycles are installed and operated to reduce pollution and solve transportation problems, and operational information is collected in real time. However, research using public bicycle operation information data has not been processed. This study uses the daily weather data of Korea Meteorological Agency and real-time air pollution data of Korea Environment Corporation to predict the amount of daily rental bicycles. Cross- validation, principal component analysis and multiple regression analysis were used to determine the independent variables of the predictive model. Then, the study selected the elements that satisfy the significance level, constructed a model, predicted the amount of daily rental bicycles, and measured the accuracy.