• 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.

• Journal of The Korean Society of Agricultural Engineers
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• v.48 no.2
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• pp.27-35
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• 2006

Large dams are managed with operation standard and flood forecasting systems, while small dams do not have management method generally. Shortage of water resources and natural disasters due to drought and flood raised public concerns for management of small dams. Most of small dams are irrigation dams, which need diversified water uses. However, the lack of systematic management of small dams have caused serious water wastage and increased natural disasters. Storage management method and system were developed to solve these problems in small dams. The system was applied to Seongju dam for effective management. The storage management method was established considering hydrology simulation and statistical analysis using the system. This method can bring additional available water, even in the same conditions of the water demand and the supply conditions of watershed. It can improve the flood control capacity and water utilization efficiency by' the flexible operation of storage space.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.23-24
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• 2011

Recently, it is required EV(Electric Vehicles) charging infra construction for approaching to accelerate and to commercialize development of EV. In this study, it was introduced basic overview of EV and charging infra construction. and we're supposed rate of growth and reduction of the number of registered vehicles by considering about last 3 years and supposed automatic number. This paper was produced dissemination if demand of EV would constantly increase. We compared and analyzed the relationship of 5th power supply and power consumption.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.67-77
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• 2005

Logistics network of the enterprise is defined to determine the optimal node and link considering the production, inventory and transportation based on the demand forecasting. This study consider the optimal logistics network of A painter company which maintain the existing transportation network and plan to relocate its plants and build new distribution centers. For this, we design possible alternative scenarios and install the simulation models for analysis of each scenario. The result of simulation will help the proper logistic network and determining the size of distribution center further.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.3
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• pp.33-45
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• 2009

In the industry of landscape architecture, in which the core of production is manpower, the management of manpower is of utmost importance. The industry of landscape architecture, however, is highly sensitive to economic shifts and policy changes; this sensitivity renders the management of manpower-maintaining the balance between supply and demand-often times difficult. Currently, this vicious circle appears to persist in the sense that the industry suffers from a lack of skilled employees, and a new body of skilled laborers from the paucity of jobs. This study, in analyzing current manpower management as well as the prospective supply and demand in the field, looks forward to the stability of the supply and demand in landscape architecture in the nation. According to this study, the number of new skilled laborers-those who have a higher credential than that of "landscape architect-engineer"-is expected to increase by 10% per year. The number of new skilled laborers being 1,137 in 2008, it can be inferred that there will be a new group of 1,251 skilled laborers in the field in 2009. Meanwhile, estimating that the number of current skilled laborers in the field of landscape architecture is 14,783, the demand for new skilled laborers remains approximately 540. The supply of 1,251 skilled laborers outnumbers the demand of 540 by nearly 230%. Hence, the educational institutions of landscape architecture must be prepared to deal with this imbalance between the excessive supply and the lesser demand of skilled laborers. The issue of the excessive supply of manpower is particularly critical, because it may well undermine the competitiveness of the industry as a whole: compared to other related industries such as architecture and civil engineering, for instance. With the customary validation of long work experience no longer in effect, the need for an engineer's license will keep on increasing. It is time that educational institutions took this issue into full account and helped their students to be better qualified and more competent.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.611-614
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• 2004

현실에서의 공급사슬에 대한 분배 계획은 수요예측(forecasting)을 통해 얻어진 확률적인 분포(stochastic distribution)를 바탕으로 수립된다. 그러나 이러한 수요예측 값은 특정한 한 값을 갖는 것이 아니라 일반적으로 특정한 범위로써 존재하며 이 범위 내의 한 값을 의사 결정자가 선택하고 이를 바탕으로 분배 계획을 수립하게 된다. 하지만 수요의 불확실한 특성 때문에 효과적인 값을 결정하는 것은 쉬운 일이 아니다. 따라서 본 연구에서는 확률적인 형태의 다양한 수요 분포 형태를 정의하고, 이러한 여러 가지 분포 하에서 수요 선택에 영향을 주는 요소들을 판명한다. 이를 바탕으로 적절한 실험계획과 모의실험을 통해서 효과적인 수요선택 방안을 도출한다. 이와 같은 접근 방법을 통해 다양한 실험 조건 하에서 공급 사슬 내의 총 비용을 최소화 시키면서 동시에 목표로 하는 서비스 수준(target service level)을 만족하는 수요 선택 방안을 제시한다.

• Korea Journal of Hospital Management
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• v.25 no.4
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• pp.60-75
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• 2020

Purpose: This study aims to develop a cost model for NRP (Nursing Residency Program) operation and ultimately provide evidence for financial factors for NRP operation in the future by simulating a cost model. Methodology: This study developed a model for the NRP education cost calculation model based on the review of Hansen's model, which has systematically reported on the development and operation of NRP, and discussions with nursing education experts at a university-affiliated hospital. With the simulation, it was intended to predict nurses' supply and demand in the long term and to calculate changes in long-term education costs. Findings: Firstly, turnover model, term model, cost model necessary for calculating a model for the NRP education cost calculation model was set up. Secondly, the simulation showed the following results; 1) the proportion of newly graduated nurses less than 5 years of working decreases gradually over time, which will make the composition of nurses more balanced. 2) In the first year of the partial introduction of NRP, the cost of training new nurses was about 2.1 times higher than before. After the introduction, the training cost in the 13th year began to be lesser than before the introduction, and in the 25th year, it decreased by 28.1% compared to before the introduction. Practical Implications: Firstly, NRP would be an effective way to solve the higher turnover and frequent departure of new nurses and the imbalance of nurses' composition. Secondly, although the costs of NRP are incurred in the early stages, in the end, NRP training costs are reduced compared to before the introduction of NRP. It is necessary to systematically understand the contribution effect of NRP by analyzing the economic value of NRP considering financial and non-monetary returns in the future and providing a basis for decision-making related to NRP implementation.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.3
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• pp.71-83
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• 2020

Resilience is the capacity to maintain essential services under a range of circumstances from normal to extreme. It is achieved through the ability of assets, networks, systems and management to anticipate, absorb and recover from disturbance. It requires adaptive capacity in respect of current and future risks and uncertainties as well as experience to date. The agricultural infrastructures with high resilience can not only reduce the size of the disaster relatively, but also minimize the loss by reducing the time required for recovery. This study aims to evaluate the most suitable drought countermeasures with the analysis of various resilience indices by predicting future agricultural water shortage under land use and climate change scenarios for agricultural areas in Jeju Island. The results showed that the permanent countermeasure is suitable than the temporary countermeasures as drought size and the cost required for recovery increase. Wide-area water supply system, which is a kind of water grid system, is identified as the most advantageous among countermeasures. It is recommended to evaluate the capability of agricultural infrastructure against drought with the various Resilience Indices for reliable assessment of long-term effect.

• Journal of Korea Trade
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• v.25 no.4
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• pp.17-36
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• 2021

Purpose - This study provides useful information to stakeholders by forecasting the tramp shipping market, which is a completely competitive market and has a huge fluctuation in freight rates due to low barriers to entry. Moreover, this study provides the most effective parameters for Baltic Dry Index (BDI) prediction and an optimal model by analyzing and comparing deep learning models such as the artificial neural network (ANN), recurrent neural network (RNN), and long short-term memory (LSTM). Design/methodology - This study uses various data models based on big data. The deep learning models considered are specialized for time series models. This study includes three perspectives to verify useful models in time series data by comparing prediction accuracy according to the selection of external variables and comparison between models. Findings - The BDI research reflecting the latest trends since 2015, using weekly data from 1995 to 2019 (25 years), is employed in this study. Additionally, we tried finding the best combination of BDI forecasts through the input of external factors such as supply, demand, raw materials, and economic aspects. Moreover, the combination of various unpredictable external variables and the fundamentals of supply and demand have sought to increase BDI prediction accuracy. Originality/value - Unlike previous studies, BDI forecasts reflect the latest stabilizing trends since 2015. Additionally, we look at the variation of the model's predictive accuracy according to the input of statistically validated variables. Moreover, we want to find the optimal model that minimizes the error value according to the parameter adjustment in the ANN model. Thus, this study helps future shipping stakeholders make decisions through BDI forecasts.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1859-1864
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• 2004

An effective methodology is reported for the optimal design of multisite batch production/transportation and storage networks under uncertain demand forecasting. We assume that any given storage unit can store one material type which can be purchased from suppliers, internally produced, internally consumed, transported to or from other plant sites and/or sold to customers. We further assume that a storage unit is connected to all processing and transportation stages that consume/produce or move the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. A batch transportation process can transfer one material or multiple materials at once between plant sites. The objective for optimization is to minimize the probability averaged total cost composed of raw material procurement, processing setup, transportation setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two sub-problems. The first yields analytical solutions for determining lot sizes while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks for the given demand forecast scenario. The result of this study will contribute to the optimal design and operation of large-scale supply chain system.