• Korean Institute of Interior Design Journal
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• v.15 no.6 s.59
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• pp.139-149
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• 2006

Because of economic growth and the social trend to respect individuality, people's average commodity volume tends to increase. It makes people perceive the importance of storage space. The storage planning without consideration of commodity volume in the apartment can not satisfy the needs of residents. This study is developed focused on the $85m^2$ apartment which is the most representative and general type. The objectives of the study are to investigate the storage-capacity of $85m^2$ apartment offered by 4 construction companies to know the present storage condition, to investigate the average volumes and type of commodities in 30 families located in Seoul and Kyungkido to produce the necessary storage-capacity, and lastly to produce optimal storage-capacity and proportion of optimal storage-capacity considering the volume of the furniture owned by each resident. The results of the study are 1) the storage capacity for commodity volume in $85m^2$ apartment is $19.41m^3$. 2) the optimal storage-capacity which only counts the storage volume of built-in furniture is $17.14m^3$ 3) the proportion of optimal storage-capacity is 9.5% of the house-capacity.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.274-281
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• 1999

In this paper, we determine the required storage capacity of a unit-load automated storage/retrieval system(AS/RS) under random storage assignment(RAN) and n-class turnover-based storage assignment(CN) policies. For each of the storage policies, an analytic model to determine the optimal storage capacity of the AS/RS is formulated so that the total cost related to storage space and space shortage is minimized while satisfying a desired service level. A closed form of optimal solutions for the RAN policy is derived from the model. For the CN policy, an optimal storage capacity is shown to be determined by applying the existing iterative search algorithm developed for the full turnover-based storage(FULL) policy. Finally, an application of the approach to the standard economic-order-quantity inventory model is provided.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.8
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• pp.8-14
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• 2010

In this Paper, optimal capacity of battery storage in Je-Ju is calculated. First, Electricity demand data of Je-Ju('06~'16) is estimated based on real electricity demand data of Je-Ju('06~'07). Then, the 4th power supply planning is used to calculate benefits from battery storage capacity in view of maximum power savings, preventing outages savings and energy charge fee reduction. Finally, optimal battery storage capacity is suggested.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.7
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• pp.1232-1236
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• 2010

In this Paper, optimal capacity of energy storage and amount of $CO_2$ reduction in Jeju is calculated. Based on electricity demand data of Je-Ju from 2006 to 2007, the estimation electricity demand from 2009 to 2018 is performed. To calculate the amount of maximum $CO_2$ reduction and energy storage capacity in Jeju, the 4th power supply planning and IPCC guideline are used. Finally, Optimal capacity of energy storage and the amount of $CO_2$ reduction are showed.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.2
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• pp.69-80
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• 1998

The optimal reservoir storage capacity is needed to be determined at the stage of reservoir planning. The reservoir storage capacity should be based on water balance between demand and supply, and meet the water deficity during the growing season. However, the optimal reservoir storage capacity should be determined considering benefit-cost analysis for the project. In this study, Two models are developed. The one is the RSOM(Reservoir Storage Optimization Model), that is consisted by three submodels, MROPER (Modified Reservoir OPERation model), RESICO(REservoir SIze and the construction COst computation) model. And the other is the BECA(BEnefit-Cost Anaysis) model. For model application, three districts, Chungha, Ipsil and Edong were selected. The relative difference of B/C ratio between project planning data and estimation by RSOM is 17.9, 15.0 and 7.3% respectively, which may be applicable for water resources development feasibility planning.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.529-533
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• 2012

By introducing RPS(Renewable Portfolio Standard) for reduction of greenhouse gas, Renewable energy sources have becoming widespread gradually. However, Renewable energy sources, such as wind power and PV are difficult to control the output and they have intermittent characteristics of the output. These characteristics would cause some problems when it is connected in the power system. In order to solve these problems, Energy Storage Systems(ESS) are considered to use. Although there are many different storage devices, the utilization of Secondary Battery is the one of the best ways to stabilize an output fluctuation of RES because of its fast responsibility. For that reason, it would better fit a large-capacity of Secondary battery for stabilization. However, batteries cannot be installed with a large capacity blindly because of its expensive cost. So to select proper capacity of the battery is an important consideration. This paper presented a methodology for the optimal capacity and operation of ESS in microgrids.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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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.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.2
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• pp.97-105
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• 2008

This paper presents simulated and experimental test results of optimal control algorithm for an encapsulated ice thermal storage system with full capacity chiller operation. The algorithm finds an optimal combination of a chiller and/or a storage tank operation for the minimum total operation cost through a cycle of charging and discharging. Dynamic programming is used to find the optimal control schedule. The conventional control strategy of chiller-priority is the baseline case for comparing with the optimal control strategy through simulation and experimental test. Simulation shows that operating cost for the optimal control with chiller on-off operation is not so different from that with chiller part load capacity control. As a result from the experimental test, the optimal control operation according to the simulated operation schedule showed about 14 % of cost saving compared with the chiller-priority control.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.802-810
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• 1998

The purpose of this study is to find the analytic solution of determining the optimal capacity of processes and storages to meet the product demand. Recent trend to reduce product delivery time and to provide high quality product to customer requires the increasing capacity of storage facilities. However, the cost of constructing and operating storage facilities is becoming substantial because of increasing land value, environmental and safety concern. Therefore, reasonable decision making about the capacity of processes and storages is important subject for industries. The industrial solution for this subject is to use the classical economic lot sizing method, EOQ(Economic Order Quantity) model, trimmed with practical experience but the unrealistic assumption of EOQ model is not suitable for the chemical plant design with highly interlinked processes and storages. This study, a first systematic attempt for this subject, clearly overcomes the limitation of classical lot sizing method. The superstructure of the plant consists of the network of serially and/or parallelly interlinked processes and storages. A novel production and inventory analysis method, PSW(Periodic Square Wave) model, is applied. The objective function of optimization is minimizing the total cost composed of setup and inventory holding cost. The advantage of PSW model comes from the fact that the model provide a set of simple analytic solution in spite of realistic description of material flow between process and storage. The resulting simple analytic solution can greatly enhance the proper and quick investment decision for the preliminary plant design confronting diverse economic situation.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.5
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• pp.207-217
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• 2018

Recently, the importance of energy demand management, particularly peak load control, has been increasing due to the policy changes of the Second Energy Basic Plan. Even though the installation of distributed generation systems such as Photovoltaic and energy storage systems (ESS) are encouraged, high initial installation costs make it difficult to expand their supply. In this study, the power consumption of a university building was measured in real time and the measured power consumption data was used to calculate the optimal installation capacity of the Photovoltaic and ESS, respectively. In order to calculate the optimal capacity, it is necessary to analyze the operation methods of the Photovoltaic and ESS while considering the KEPCO electricity billing system, power consumption patterns of the building, installation costs of the Photovoltaic and ESS, estimated savings on electric charges, and life time. In this study, the power consumption of the university building with a daily power consumption of approximately 200kWh and a peak power of approximately 20kW was measured per minute. An economic analysis conducted using these measured data showed that the optimal capacity was approximately 30kW for Photovoltaic and approximately 7kWh for ESS.