• Environmental and Resource Economics Review
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• v.23 no.4
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• pp.583-615
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• 2014

Including the rolling black out in 2011, Korea has suffered from rapid increase of electricity consumption and demand forecasting failure for last five years. In addition, because of the Fukushima disaster, high fuel prices, and introduction of new generation sources such as renewables, the uncertainty on a power supply strategy increases. Consequently, a stable power supply becomes the new agenda and a revisino of strategy for new power generation sources is needed. In the light of this, we appraises the sixth basic plan for long term electricity demand and supply considering the changes of foreign and domestic conditions. We also simulate a strategy for the new power generation sources using a portfolio analysis method. As results, a diversity of power generation sources will increase and the share of renewable power generation will be surged on the assumptions of a cost reduction of renewable power sources and an increase of fuel costs. Particularly, on the range of a risk level(standard deviation) from 0.06 and 0.09, the efficient frontier has the most various power sources. Besides, the existing power plan is not efficient so that an improvement is needed. Lastly, the development of an electricity storage system and energy management system is necessary to make a stable and efficient power supply condition.

• KDI Journal of Economic Policy
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• v.35 no.4
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• pp.31-61
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• 2013

The purpose of this study is to calculate the economic value of transport demand forecasting risks in the road PPP project. Under the assumption that volatility of the road PPP project value occurs only in regard with uncertainty of traffic volume forecasting, this study calculates the economic value of the traffic forecasting risks in the case of the road PPP project. To that end, forecasted traffic volume is assumed to be a stochastic variable and to follow the Geometric Brownian motion as time passes. In particular, this study attempts to differentiate itself from existing studies that simply use an arbitrary assumption by presenting the application of different traffic volume growth volatility and the rates before and after the ramp-up period. Analysis of the case projects reveals that the risk premium related to traffic volume forecast of the project turns out as 7.39~8.30%, without considering option value-such as minimum revenue guarantee-while the project value volatility caused by transport demand forecasting risks is 17.11%. As the discount rate grows higher, the project value volatility tends to decrease and volatility in project value is always suggested to be larger than that in transport volume influenced by leverage effect due to fixed expenditure. The market value of transport demand forecasting risk-calculated using the project value volatility and risk premium-is analyzed to be between 0.42~0.50, implying that a 1% increase or decrease in the transport amount volatility would lead to a 0.42~0.50% increase or decrease in risk premium of the project.

• The Journal of Bigdata
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• v.2 no.2
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• pp.33-46
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• 2017

Service part has the attribute causing a difficulty of the systematic management like a kind of diversity, uncertainty of demand, high request for quick response against general complete product. Especially, order picking is recognized as the most important work in the warehouse of the parts since inbound cycle of the service part long but outbound cycle is relatively short. But, increasing work efficiency in the warehouse has a limitation that cycle, frequency and quantity for the outbound request depend on the inherent features of the part. Through this research, not only are the types of the parts classified with the various and specified data but also the method is presented that it minimizes (that) the whole distances of the order picking and store location about both inbound and outbound by developing the model of the demand prediction. Based on this study, I expect that all of the work efficiency and the space utilization will be improved without a change of the inbound and outbound quantity in the warehouse.

• STI Policy Review
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• v.5 no.1
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• pp.75-97
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• 2014

Entrepreneurial financing, such as publicly initiated venture capital or grant schemes, serves as an important policy instrument that aims to bridge the financing gap facing young, innovative businesses, a gap that is mainly due to higher risk and growing uncertainty, and to strategically promote the creation of new ventures through the revitalization of their venture capital industries. This study examines public venture capital initiatives in Australia, Canada, and Sweden, and discovered that all three countries actively foster their venture capital industry through the formation of funds or the provision of tax incentives. It is notable that the majority of financing initiatives heavily depend on supply-side measures rather than demand-driven policies that focus on stimulating private investment in technological innovations and discoveries. This paper discusses in-depth the policy impact of public financing initiatives and their subsequent side-effects raised in the process such as overlapping in funding structure across the country, lack of monitoring and evaluation for feedback, fragmentation across the government ministries and agencies, and competition with the private sector, which may cause inefficiency as a result of public intervention. Financial constraints may arise for many reasons, partly resulting from the lack of investment readiness of young entrepreneurs. This signals a policy shift towards the creation of market-driven demand away from the traditional supply-push approach, and is a grand challenge to policymakers in entrepreneurial financing. Attention is leaning towards the efficiency and effectiveness of these public-financing initiatives in terms of their policy roles. It is worth noting that policy should focus on generating synergy so available resources can be channeled into the early, risky stage of new ventures, working as facilitator to the achievement of an intended policy goal.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.305-312
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• 2010

The aim of this study is to find an analytic solution to the problem of determining the optimal capacity of a batch-storage network to meet demand for finished products in a system undergoing joint random variations of operating time and batch material loss. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to joint random variations in the cycle time and batch size. The production processes have also joint random variations in cycle time and product quantity. The spoiled materials are treated through regeneration or waste disposal processes. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced. The proposed method has the potential to rapidly provide very useful data on which to base investment decisions during the early plant design stage. It should be of particular use when these decisions must be made in a highly uncertain business environment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.53-62
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• 2009

Lee[15] examined quantity discount contracts between a manufacturer and a retailer in a stochastic, two-period inventory model where quantity discounts are provided based on the previous order size. During the two periods, the retailer faces stochastic (truncated Poisson distributed) demands and he/she places orders to meet the demands. The manufacturer provides for the retailer a price discount for the second period order if its quantity exceeds the first period order quantity. In this paper we extend the above two-period model to a k-period one (where k < 2) and propose a stochastic nonlinear mixed binary integer program for it. In order to make the program tractable, the nonlinear term involving the sum of truncated Poisson cumulative probability function values over a certain range of demand is approximated by an i-interval piecewise linear function. With the value of i selected and fixed, the piecewise linear function is determined using an evolutionary algorithm where its fitness to the original nonlinear term is maximized. The resulting piecewise linear mixed binary integer program is then transformed to a mixed binary integer linear program. With the k-period model developed, we suggest a solution procedure of receding horizon control style to solve n-period (n < k) order decision problems. We implement Lee's two-period model and the proposed k-period model for the use in receding horizon control style to solve n-period order decision problems, and compare between the two models in terms of the pattern of order quantities and the total profits. Our computational study shows that the proposed model is superior to the two-period model with respect to the total profits, and that order quantities from the proposed model have higher fluctuations over periods.

• Journal of the Earthquake Engineering Society of Korea
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• v.27 no.5
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• pp.213-220
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• 2023

Seismic fragility curves play a crucial role in assessing potential seismic losses and predicting structural damage caused by earthquakes. This study compares non-sampling-based methods of seismic fragility curve derivation, particularly the probabilistic seismic demand model (PSDM) and finite element reliability analysis (FERA), both of which require employing sophisticated finite element analysis to evaluate and predict structural damage caused by earthquakes. In this study, a three-dimensional finite element model of API 5L X65, a buried gas pipeline widely used in Korea, is constructed to derive seismic fragility curves. Its seismic vulnerability is assessed using nonlinear time-history analysis. PSDM and a FERA are employed to derive seismic fragility curves for comparison purposes, and the results are verified through a comparison with those from the Monte Carlo Simulation (MCS). It is observed that the fragility curves obtained from PSDM are relatively conservative, which is attributed to the assumption introduced to consider the uncertainty factors. In addition, this study provides a comprehensive comparison of seismic fragility curve derivation methods based on sophisticated finite element analysis, which may contribute to developing more accurate and efficient seismic fragility analysis.

• Composites Research
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• v.37 no.2
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• pp.108-114
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• 2024

Due to the continuously increasing global demand for electricity, the demand for high-voltage submarine cables is also increasing. One of the issues that need to be addressed for submarine cables is the high production cost and expensive laying costs. Submarine cables exposed to the marine environment encounter external forces such as wave and current, leading to issues such as cable damage due to external factors or high maintenance costs in the event of an accident. Therefore, we are preparing for the uncertainty of the submarine environment through many protective materials and protective equipment. In this study, we examined the bending performance of piggyback clamps (PBC) and strap, which are representative protective equipment, in response to the submarine environment through analytical methods. To examine the structural performance of PBC, the bending performance were assessed under the maximum bending moment criterion of 15 kN·m for the flexible protection tube. As a result, it was confirmed that the structural performance regarding the bending moment of both PBC and straps was ensured.

• Korean Journal of Construction Engineering and Management
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• v.10 no.1
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• pp.91-101
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• 2009

The factors of uncertainty such as work delay could cause many problems, for example, increase of construction cost and terms of work, and the deterioration of quality. Because of these, the uncertainty risk is regarded as an important management factor to obtain the success of construction project. So, the systematic management plan about the uncertainty factors is needed because it plays an important role in the completion of entire project. And also analysis of some factors which can cause the work delay can be one way of improving construction project's certainty and making it competitive. In this reason, we have to make an effort to set a priority based on analysis of quantitatively numerical value about work delay factors to manage them effectively. Thus, this study aims to suggest the basic data for the effective management and prevention of work delay in steel-frame work which is progressive actively now, along with increasing of demand of high-rise buildings by analyzing each reasons of work delay factors and also by suggesting important management factors that are coded according to each construction work using FMEA method which could give a data about the importance of work delay factors through quantitatively numerical value.

• Journal of the Korean Geographical Society
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• v.31 no.4
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• pp.648-661
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• 1996

The traditional von Thunen model has various shortcomings. Perhaps the greatest dificiency is the model's sole emphasis on the production side of the economy;that is, the agricultural markets are rarely closed for demand. In thes paoer a closed model for a three-activity, two-dimensional economy is developed. Equillibrium solutions are generated for prices, land areas, and outputs. Comparative static analysis then follows. Attention is next given to a maximum expected-return model under environmental uncertainty. Land uses for the traditional model and the closed model are then compared.