• 전기학회논문지
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• 제61권6호
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• pp.783-790
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• 2012

Electric Vehicles(EVs) and Plug-in Hybrid Electric Vehicles(PHEVs) which have the grid connection capability, represent an important power system issue of charging demands. Analyzing impacts EVs charging demands of the power system such as increased peak demands, developed by means of modeling a stochastic distribution of charging and a demand dispatch calculation. Optimization processes proposed to determine optimal demand distribution portions so that charging costs and demand can possibly be managed. In order to solve the problems due to increasing charging demand at the peak time, alternative electricity rate such as Time-of-Use(TOU) rate has been in effect since last year. The TOU rate would in practice change the tendencies of charging time at the peak time. Nevertheless, since it focus only minimizing costs of charging from owners of the EVs, loads would be concentrated at times which have a lowest charging rate and would form a new peak load. The purpose of this paper is that to suggest a scenario of load leveling for a power system operator side. In case study results, the vehicles as regular load with time constraints, battery charging patterns and changed daily demand in the charging areas are investigated and optimization results are analyzed regarding cost and operation aspects by determining optimal demand distribution portions.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1511-1518
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• 2017

Renewable energy hybrid systems look into the process of choosing the finest arrangement of components and their sizing with suitable operation approach to deliver effective, consistent and cost effective energy source. This paper presents hybrid renewable energy system (HRES) solar photovoltaic, downdraft biomass gasifier, and fuel cell based generation system. HRES electrical power to supply the electrical load demand of academic research building sited in $23^{\circ}12^{\prime}N$ latitude and $77^{\circ}24^{\prime}E$ longitude, India. Fuzzy logic programming discover the most effective capital and replacement value on components of HRES. The cause regarding fuzzy logic rule usage on HOMER pro (Hybrid optimization model for multiple energy resources) software program finds the optimum performance of HRES. HRES is designed as well as simulated to average energy demand 56.52 kWh/day with a peak energy demand 4.4 kW. The results shows the fuel cell and battery bank are the most significant modules of the HRES to meet load demand at late night and early morning hours. The total power generation of HRES is 23,794 kWh/year to the supply of the load demand is 20,631 kWh/year with 0% capacity shortage.

• 설비공학논문집
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• 제25권6호
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• pp.310-316
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• 2013

This study was designed to investigate a method for short-term, real-time energy demand prediction, to cope with changing loads for the effective operation and management of buildings. Through a case study, a novel methodology for real-time energy demand prediction with the use of weather forecasting data was suggested. To perform the input and output operations of weather data, and to calculate solar radiation and EnergyPlus, the BCVTB (Building Control Virtual Test Bed) was designed. Through the BCVTB, energy demand prediction for the next 24 hours was carried out, based on 4 real-time weather data and 2 solar radiation calculations. The weather parameters used in a model equation to calculate solar radiation were sourced from the weather data of the KMA (Korea Meteorological Administration). Depending on the local weather forecast data, the results showed their corresponding predicted values. Thus, this methodology was successfully applicable to anywhere that local weather forecast data is available.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권3호
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• pp.528-550
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• 2024

Warehousing demand prediction is an essential part of the supply chain, providing a fundamental basis for product manufacturing, replenishment, warehouse planning, etc. Existing forecasting methods cannot produce accurate forecasts since warehouse demand is affected by external factors such as holidays and seasons. Some aspects, such as consumer psychology and producer reputation, are challenging to quantify. The data can fluctuate widely or do not show obvious trend cycles. We introduce a new model for warehouse demand prediction called MAGRU, which stands for Multi-layer Attention with GRU. In the model, firstly, we perform the embedding operation on the input sequence to quantify the external influences; after that, we implement an encoder using GRU and the attention mechanism. The hidden state of GRU captures essential time series. In the decoder, we use attention again to select the key hidden states among all-time slices as the data to be fed into the GRU network. Experimental results show that this model has higher accuracy than RNN, LSTM, GRU, Prophet, XGboost, and DARNN. Using mean absolute error (MAE) and symmetric mean absolute percentage error(SMAPE) to evaluate the experimental results, MAGRU's MAE, RMSE, and SMAPE decreased by 7.65%, 10.03%, and 8.87% over GRU-LSTM, the current best model for solving this type of problem.

• International Journal of Naval Architecture and Ocean Engineering
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• 제10권5호
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• pp.529-544
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• 2018

Ship owners now demand a new design approach for the rudder that considers detailed design information such as maneuverability and environmental loads etc. on a quantified basis. In this paper, we developed the concept of a safe operation capability chart for the design of a rudder area. The chart can be used as the basis of design considering the maneuverability and environmental loads. To confirm the applicability of the safe operation capability chart for use as the basis of design, four different rudders are assumed in this work. First, it is determined whether or not it is appropriate to design a rudder by applying a conventional design approach based on IMO maneuvering tests. The proposed concept is reviewed for use as the basis of the design by investigating the effect of rudder area on capability charts that are plotted according to the rudder under various environmental conditions.

• 한국수자원학회논문집
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• 제42권8호
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• pp.643-657
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• 2009

홍수기에 집중되는 유출량을 갈수기에 적절히 활용하기 위한 대표적인 구조물이 댐이다. 제한된 용수공급량을 적절히 분배해 용수수요량을 만족시키면서 미래 갈수기시 용수공급을 대비하여 댐 저류량을 조절하는 것이 댐 운영의 중요한 목적 중 하나이다. 본 연구에서는 갈수 시 댐 저류량에 따라 댐 계획방류량을 일정비율 줄여주는 Hedging Rule을 5단계로 적용하여 댐의 상시만수위 저류량에 대한 실제 저류량의 편차, 수요에 대한 용수공급 부족량, 그리고 하천유지용수 부족량을 목적함수로 하여 혼합정수 선형계획법(MILP, Mixed Integer Linear Programming)으로 저수지 연계운영모형을 구성하였다. 한강수계의 다목적댐인 충주, 횡성, 소양강 댐과 용수전용댐인 광동 댐, 그리고 발전용 댐이지만 비교적 큰 저류용량을 가진 화천 댐을 연계 운영 대상으로 하여, 수자원장기종합계획에 사용된 2003년 유출량 및 수요량 자료와 댐 운영 실무편람의 댐 계획방류량 자료를 10일 단위로 입력하여 GAMS/CPLEX를 이용해 최적화하였다. 그 결과 생공용수 수요량 99.99%, 농업용수 수요량 99.91%, 그리고 하천유지용수 수요량 100.00%를 충족시키면서도, 실제 2003년 운영자료에 비교하여 댐 저류효율이 10.04% 개선된 결과를 도출하였다.

• 수산해양기술연구
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• 제55권1호
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• pp.74-81
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• 2019

According to the recent presentation by the Korean Maritime Safety Tribunal, about 70% of marine accident occurs from fishing vessel, and 90% of cause of entire marine accidents attributes to human error. As fishing vessels require basic operations, fishing operations, other additional operations and techniques such as fish handling, cultivating excellent marine officer to prevent marine accident and develop industry is very important. A fisheries training ship is still very difficult to satisfy the demand for diversity of fishery training and sense of realism of the industry. As the result of employment expectation by category of business survey targeting 266 marine industry high school graduates who hope to board fishing vessels for the last four years, tuna purse seine was the highest with 132 cadets (49.6%), followed by offshore large purse seine (65 cadets, 22.4%), and tuna long line (35 cadets, 13.2%). The Korea Institute of Maritime and Fisheries Technology (KIMFT) has replaced old jigging and fish pot fishery training ships and proceeded developing and building multi-purpose fisheries training ships considering the demand of industry and the promotion of employment; however, the basic fishing method was set for a tuna purse seine. As a result of seakeeping model test, it can conduct the satisfiable operation at sea state 5, and survive at sea state 8.

• 한국항해학회지
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• 제22권4호
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• pp.1-14
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• 1998

There are three basic modes of operation of ships: liner, tramp and industrial operations. Industrial operations, where the owner of the cargo, i.e. the industrial carrier controls the ships, abound in the shipment of bulk commodities, such as oil, chemicals and ores. Industrial carriers strive to minimize the shipping cost of their cargoes. This paper is concerned with the operational optimization problem of a fleet owned by major international oil company. The major oil company is a holding corporation for a group of oil producing, transporting, refining, and marketing companies located in various countries throughout the world. The operational optimization problem of the fleet is divided into two-phases. The front end corresponds to the optimization of transporting crude oil, product mix, and the distribution of product oil to meet market demand. The back end tackles the operational optimization problem of the fleet to meet the transportation demand derived from the front end. A case study is carried out with the H major oil company problem composed by reflecting the practices of an international major oil company. The results are summarized and examined in the point of optimization for the total operation of the H major oil company and the operational optimization problem of the fleet. The paper concludes with the remark that the results of the study might be useful and applicable in practices of these related decision problems.

• 전기학회논문지
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• 제65권8호
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• pp.1347-1354
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• 2016

This paper presents optimal operational scheduling model and economic assessment of Li-ion battery energy storage systems installed in non-residential customers. The operation schedule of a BESS is determined to minimize electric bill, which is composed of demand and energy charges. Dynamic programming is introduced to solve the nonlinear optimization problem. Based on the optimal operation schedule result, the economics of a BESS are evaluated in the investor and the social perspective respectively. Calculated benefits in the investor or customer perspective are the savings of demand charge, energy charge, and related taxes. The social benefits include fuel cost savings of generating units, construction deferral effects of the generation capacity and T&D infra, and incremental CO2 emission cost impacts, etc. Case studies are applied to an large industrial customer that shows similarly repeated load patterns according to days of the week.

• 한국항공운항학회지
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• 제29권4호
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• pp.1-20
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• 2021

Due to the recent rapid increase in passenger and cargo air transport demand, the capacity of Jeju International Airport has been approaching its limit. Even though in COVID-19 crisis which has started from Nov 2019, Jeju International Airport still suffers from strong demand in terms of air passenger and cargo transportation. However, it is an undeniable fact that the delay has also increased in Jeju International Airport. In this study, we analyze the correlation between weather and delayed departure operation based on both datum collected from the historical airline operation information and aviation weather statistics of Jeju International Airport. Adopting machine learning techniques, we then analyze weather condition Jeju International Airport and construct a delay prediction model. The model presented in this study is expected to play a useful role to predict aircraft departure delay and contribute to enhance aircraft operation efficiency and punctuality in the Jeju International Airport.