• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.579-589
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• 1998

Full turnover-based storage policy (FULL) is often used to minimize the travel time needed to perform storage/retrieval operations in automated storage/retrieval systems (AS/RSs). This paper presents an approach for determining the required storage capacity for a unit load AS/RS under the FULL. An analytic model is formulated such that the total cost related to storage space and space shortage is minimized while satisfying a desired service level. To solve the model, some analytic properties are derived and based on them, an iterative search algorithm which always generates optimal solutions is developed. To illustrate the validity of the approach, an application is provided when the standard economic-order-quantity inventory model is used.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.2043-2050
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• 2017

This paper presents two MPC (Model Predictive Control) based charging and discharging algorithms of BESS (Battery Energy Storage System) for capacity firming of wind generation. To deal with the intermittency of the output of wind generation, a single BESS is employed. The proposed algorithms not only make the output of combined systems of wind generation and BESS track the predefined reference, but also keep the SoC (State of Charge) of BESS within its physical limitation. Since the proposed algorithms are both presented in simple if-then statements which are the optimal solutions of related optimization problems, they are both easy to implement in a real-time system. Finally, simulations of the two strategies are done using a realistic wind farm library and a BESS model. The results on both simulations show that the proposed algorithms effectively achieve capacity firming while fulfilling all physical constraints.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.81-84
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• 2003

The ability to determine the optimal frequencies and offsets for independent and unrestricted ordering cycles for multiple items can be very valuable for managing storage capacity constrained facilities in a supply chain. The complexity of this problem has resulted in researchers focusing on more tractable surrogate problems that are special cases of the base problem. Murthy et al. (European Journal of Operation Research 2003) developed insights leading to solution of the original problem and present a heuristic for offsetting independent and unrestricted ordering cycles for items to minimize their joint storage requirements. However, their study cannot find optimal solution due to the Greedy Heuristic solution procedure. In this paper, we present a complete procedure to find the optimal solution for the model with a integer programming optimization approach and genetic algorithm. Numerical examples are included to compare each model with that of Murthy et at. Research of this type may prove useful in solving the more general problem of selecting order policies to minimize combined holding, ordering, and storage costs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4063-4086
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• 2016

Cloud computing is a robust technology, which facilitate to resolve many parallel distributed computing issues in the modern Big Data environment. Hadoop is an ecosystem, which process large data-sets in distributed computing environment. The HDFS is a filesystem of Hadoop, which process data blocks to the cluster nodes. The data block placement has become a bottleneck to overall performance in a Hadoop cluster. The current placement policy assumes that, all Datanodes have equal computing capacity to process data blocks. This computing capacity includes availability of same storage media and same processing performances of a node. As a result, Hadoop cluster performance gets effected with unbalanced workloads, inefficient storage-tier, network traffic congestion and HDFS integrity issues. This paper proposes a storage-tier-aware Robust Data Placement (RDP) scheme, which systematically resolves unbalanced workloads, reduces network congestion to an optimal state, utilizes storage-tier in a useful manner and minimizes the HDFS integrity issues. The experimental results show that the proposed approach reduced unbalanced workload issue to 72%. Moreover, the presented approach resolve storage-tier compatibility problem to 81% by predicting storage for block jobs and improved overall data block placement by 78% through pre-calculated computing capacity allocations and execution of map files over respective Namenode and Datanodes.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.10
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• pp.52-58
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• 2009

In this paper, we propose a probability method to determine minimum capacity of energy storage system(ESS) for Micro-grid Because of high capital cost of ESS, It's very important to determine optimal capacity of ESS and for stable operation of Micro grid(MG), we should determine minimum capacity of ESS. The proposed method has abilities to consider forced outage rate of generators and intermittent of non-dispatchable generators and minimum capacity make MG keep energy balancing by oneself.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.1
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• pp.45-54
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• 2024

This study developed a model to evaluate the co-benefits and trade-off effects between biodiversity and carbon storage capacity based on the implementation locations of nature-based solutions. The model aims to propose optimal implementation locations by using the conceptual idea of edge effects for carbon storage and connectivity for biodiversity. The co-benefits were considered by simultaneously taking into account two effects rather than a single effect. Trade-off effects were observed among optimal plans through a comparison of benefits. The NSGA-II multi-objective optimization algorithm was utilized, confirming the identification of Pareto-optimal solutions. The implementation patterns of Pareto-optimal solutions for green areas were examined. This study holds significance in proposing optimal locations by evaluating various co-benefits and trade-off effects of nature-based solutions. By advancing models based on this evaluation framework, it is anticipated that the assessment of co-benefits and trade-off effects among various benefits of nature-based solutions, such as climate change mitigation, enhancement of biodiversity, and provision of ecosystem services, can be accomplished.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.3
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• pp.283-289
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• 2010

Owing to the increasing worldwide interest in green technology and renewable energy sources, flywheel energy storage systems (FESSs) are gaining importance as a viable alternative to traditional battery systems. Since the energy storage capacity of an FESS is proportional to the principal mass-moment of inertia and the square of the running speed, a design that maximizes the principal inertia while operatingrunning at the highest possible speed is important. However, the requirements for the stability of the system may impose a constraint on the optimal design. In this paper, an optimal design of an FESS that not only maximizes the energy capacity but also satisfies the requirements for system stability and reduces the sensitivity to external disturbances is proposed. Cross feedback control in combination with a conventional proportional-derivative (PD) controller is essential to reduce the effect of gyroscopic coupling and to increase the stored energy and the specific energy density.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.797-799
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• 1997

This paper presents an operation and planning model of integrated energy systems which consist of small scale cogeneration systems, thermal accumulator, ice storage and electrical energy storage systems. In the proposed planning model, an optimization of total cost which contains investment, operation, thermal shortage and salvage costs has carried out with the maximum principle based on the lifetime of each system component and unit price per capacity. From this model, optimal investment capacity per annum can be determined during the studied periods using the marginal costs according to the operation characteristics of each system component.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1174-1180
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• 2018

In December 2017, the government announced plans to increase the current proportion of renewable energy from 7% to 20% by 2030 through a plan called the Renewable Energy 3020 Implementation Plan. Therefore, the demand for installation of photovoltaic(PV), wind turbine(WT) and battery energy storage system(BESS) is expected to increase. In particular, the system combined with energy storage system(ESS) is expected to take up a large portion since PV and WT can receive high renewable energy certificates(REC) weights when combined with ESS. In this study, we calculate the optimal capacity of the power conditioning system(PCS) and the BESS by comparing the economical efficiency and maximize the efficiency of the PV-BESS system in which the PV and the BESS are connected. By analyzing the system marginal price(SMP) and REC, it maximize profits through application of REC weight 5.0 and optimal charge-discharge scheduling according to the SMP changes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.4
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• pp.387-397
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• 2021

Most of Korea's agricultural water is supplied by reservoirs, so dependence on them is very high. Accordingly, it is important to reduce this dependence and provide a stable agricultural water supply by utilizing an applicable alternative water source. Therefore, in this work, scenarios for different land uses were constructed, and an optimal water supply plan using rainwater and reused sewage water - which are alternative water sources - was created. A study was also conducted to determine the optimal capacity of a rainwater facility. From the analysis, a stable water supply was achieved in the scenario of maximum utilization of rainwater by changing an existing paddy area to a greenhouse area, and about 0.82 ton of flow capacity was required for 1 mm of rainfall on farms utilizing rainwater. As a result of analyzing the optimal scenario to derive the ratio of the storage capacity per unit water collection area, the rainwater storage capacity determined through MODSIM and the storage capacity determined through actual monitoring showed similar results, about 31 and 32 %, respectively, and the optimal capacity of rainwater facilities was calculated to be about 5,796,000-6,182,400 ton.