• 한국항해학회지
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• 제15권3호
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• pp.13-24
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• 1991

This paper aims to determining the optimal capacity of Pusan port in view point of Container Physical Distribution cost. It has been established a coast model of the container physical distribution system in Pusan port is composed of 4 sub-systems and in-land transport system. Cargo handling system, transfer & storage system and in-land transport system, and analyzed the cost model of the system. From this analysis, we found that the system had 7 routes including in-land transport by rail or road and coastal transport by feeder ship between Pusan port and cargo owner's door. Though railway transport cost was relatively cheap, but, it was limited to choose railway transport routes due to the introducing of transport cargo allocation practice caused by shortage of railway transport capacity. The physical distribution ost for total import & export container through Pusan port was composed of 4.47% in port entring cost, 12.98% in cargo handling cost, 7.44% in transfer & storage cost and 75.11% in in-land transport cost. Investigation in case of BCTOC verified the results as follows. 1) The optimal level of one time cargo handling was verified 236VAN (377TEU) and annual optimal handling capacity was calculated in 516, 840VAN(826, 944TEU) where berth occupancy is $\rho$=0.6 when regardless of port congestion cost, 2) The optimal level of one time cargo handling was verified 252VAN (403TEU) and annual optimal handling capacity was calculated in 502, 110VAN (803, 376TEU) where berth occupancy is $\rho$=0.58 when considering of port congestion cost.

• KIEE International Transactions on Power Engineering
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• 제5A권1호
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• pp.9-15
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• 2005

In the operation of distribution systems, DGs (Distributed Generations) are installed as an alternative to extension and the establishment of substations, transmission and distribution lines according to the increasing power demand. In the operation planning of DGs, determining optimal capacity and allocation achieves economical profitability and improves the reliability of power distribution systems. This paper proposes a determining method for the optimal number, size and allocation of DGs in order to minimize the operation costs of distribution systems. Capacity and allocation of DGs for economical operation planning duration are determined to minimize total cost composed with power buying cost, operation cost of DGs, loss cost and outage cost using the GA (Genetic Algorithm).

• 한국항해항만학회지
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• 제35권2호
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• pp.159-165
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• 2011

The aim of paper is to calculate the optimized size of Mobile Harbor(MH) which would be operated in South Korea coast area. MH is the combined entity which has the function of both ship and container port. In estimating the optimized size, the total cost concept is applied to the different size of MH. Trade-off factors for calculating total cost are MH cost and the over-capacity lost cost. The factors for MH cost estimation are the cargo demand, distance from origin to destination, voyage route and MH's fixed and variable cost in both sailing and port. The other cost is the over-capacity lost cost which is occurred from dead space in case of oversize compared with a voyage demand. The alternatives for the least cost are 250TEU, 500TEU, 750TEU and 1,000TEU sized vessel. The result of research is that 250TEU sized vessel is optimized in a South Korea costal service. If the coastal area be separated in terms of voyage distance or the specific area in considering trade, the optimized size is changed depending upon distance.

• 대한산업공학회지
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• 제16권1호
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• pp.51-58
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• 1990

A deterministic capacity expansion planning model for a two-capacity type facility is analyzed to determine the sizes to be expanded in each period so as to supply the known demands for two distinct capacity type(product) on time and to minimize the total cost incurred over a finite planning horizon of T periods. The model assumes that capacity unit of the facility simultaneously serves a prespecified number of demand units of each capacity type, that capacity type 1 can be used to supply demands for capacity type 2, but that capacity type 2 can't be used to supply demands for capacity type 1. Capacity expansion and excess capacity holding cost functions considered are nondecreasing and concave. The structure of an optimal solution is characterized and then used in developing an efficient dynamic programming algorithm that finds optimal capacity planning policy.

• 전기학회논문지
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• 제57권9호
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• pp.1531-1535
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• 2008

In the past vertically integrated power system, the power utility forecasted power demand and invested new power plants to keep a system adequacy. However, in the competitive electricity markets, a principle part of the capacity investment is market participants who decided the investment to maximize their profit. Especially, one of the main factors in their long-term decision making is the retrieval of fixed costs (construction costs). This paper presents the capacity payment in electricity power markets. The capacity payment (CP) in Cost Based Pool (CBP) is needed to recover fixed costs. However, CP in CBP was applied not only recovering fixed costs but also ensuring supply reliability. In order to operate harmonious power markets, pool needs reasonable CP mechanism. This paper analysis CP using capacity proportion and Reliability Pricing Model (RPM).

• 품질경영학회지
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• 제49권3호
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• pp.341-358
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• 2021

Purpose: After product development, a Reliability Demonstration Test(RDT) is performed to confirm that the target life has been achieved. In the RDT, there are cases where the test equipment cannot accommodate all samples. Therefore, this study considers a test method to most economically demonstrate the target life of the product at a certain confidence level when the sample size is larger than the capacity of the test equipment. Methods: If the sample size is larger than the capacity of the test equipment, test equipments may be added or the test time of individual samples may be increased. So the test method is designed to cover this situation with limited capacity. A zero-failure test method is applied as a test method to RDT. To minimize the cost, the test cost is defined and the cost function is obtained. Finally, we obtain the optimal test plan. Results: A zero-failure test method is designed when the sample size is larger than the capacity of the test equipment, and the expected total cost is derived. In addition, the process of calculating the appropriate sample size, test time, and number of test equipment is illustrated through an example, and the effects of model parameters to the optimal solutions are investigated numerically. Conclusion: In this paper, we study a zero-failure RDT with test equipment that has limited capacity. The expected total cost is derived and the optimal sample size, test time, and number of test equipment are determined to minimize the expected total cost. We also studied numerical examples and for further studies, we can relax some restrictions in the test model and optimize the test method.

• 전기학회논문지
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• 제64권2호
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• pp.208-213
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• 2015

This study presents the estimation method for the optimal capacity of BESS(Battery Energy Storage System) in order to reduce the electric charges of common consumer. The daily optimal charge and discharge plan of BESS which satisfies the given constraints is established using linear programming through the change of rated output/rated capacity of the time that shows the electric charges in the highest reduced rate has been selected. There will be a problem to compare only reduced rate because the bigger the rated capacity, the more reduced rate is increased. Therefore, rated output/rated capacity of the time when the reduced amount of electric charges for a year is higher than the investment cost of BESS was selected.

• 전기학회논문지
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• 제65권6호
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• pp.979-986
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• 2016

At present, electric power industry around the world are being gradually changed to a new paradigm, such as electrical energy storage system, the wireless power transmission. Demand for ESS, the core technology of the new paradigm, has been growing worldwide. However, it is essential to estimate the optimal capacity of ESS facilities for frequency regulation because the benefit would be saturated in accordance with the investment moment and the increase of total invested capacity of ESS facilities. Hence, in this paper, the annual optimal mathematical investment model is proposed to estimate the optimal capacity and to establish investment plan of ESS facility for frequency regulation. The optimal mathematical investment model is newly established for each season, because the construction period is short and the operation effect for the load by seasons is different unlike previous the mathematical investment model. Additionally, the marginal operating cost is found by new mathematical operation model considering no-load cost and start-up cost as step functions improving the previous mathematical operation model. ESS optimal capacity is established by use value in use iterative methods. In this case, ESS facilities cost is used in terms of the value of the beginning of the year.

• 한국경영과학회지
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• 제13권2호
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• pp.59-65
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• 1988

This paper discusses the problem of coordinating aggregate planning and production schedules, minimizing the combined set-up inventory and capacity costs. In this study, by using the relation of fixed production quantity and the number of set-up we develop a heuristirc procedure of solving the discrete demand, fixed production quantity, variable capacity problem. First, we obtain the trade-off between set-up cost and capacity cost, then search the point minimizing the combined inventory and capacity costs.

• 상하수도학회지
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• 제26권2호
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• pp.191-199
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• 2012

Rainwater harvesting systems (RWHS), one of measures for on site rainwater management, have been promoted by laws, regulations and guidelines and have been increased. However, more evaluation of economic feasibility on RWHS is still needed due to seasonal imbalance of rainfall and little experiences and analysis on design and operation of RWHS. In this study, we investigated tank capacity of RWHS to secure economic validity considering catchment area and water demand, which is affected by building scale. Moreover, sensitivity analysis was performed to examine the effect of design factors, cost items and increase rate of water service charge on economic feasibility. The BCR (benefit cost ratio) is proportional to the increase in tank capacity. It is increased steeply in small tank capacity due to the effect of cost and, since then, gently in middle and large tank capacity. In case of 0.05 in the rate of tank volume to catchment area and 0.005 in water demand to catchment area, BCR was over one from the tank capacity of 160 $m^{3}$ taking into account of private benefits and from the tank capacity of 100 $m^{3}$ taking into account of private and public benefits. Sensitivity analysis shows that increase of water demand can improve BCR values with little cost so that it is needed to extend application of rainwater use and select a proper range of design factor. Decrease of construction and maintenance cost reduced the tank volume to secure economic validity. Finally, increase rate of water service charge had considerable impact on economic feasibility.