• Journal of the Korean Society of Industry Convergence
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• v.25 no.2_2
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• pp.209-218
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• 2022

The purpose of this study is to analyze an economic assessment of PV-ESS systems based on the power generation performance data of solar power (PV) operating in domestic area, and to calculate the optimal capacity of the energy storage system. In this study, PVs in Gyeonggi-do, Jeollabuk-do, and Gyeongsangbuk-do were targeted, and PVs in this area were assumed to be installed on a general site, and the research was conducted by applying weights based on the facility's capacity. All the analysis was conducted using the actual amount of KPX transactions of PVs in 2019. In order to calculate the optimal capacity of PCS and BESS according to GHI, PV with a minimum/maximum/central value was selected by comparing the solar radiation before the horizontal plane between three years (2017-2019) of the location where PV was installed. As a result of the analysis, in Gyeonggi-do, if the REC weight decreases to 3.4 when there is no change in the cost of installing BESS and PCS, it is more economical to link BESS than PV alone operation of PV. In Jeollabuk-do, it was analyzed that if the REC weight was reduced to 3.6, it was more likely to link BESS than PV operated alone. In Gyeongsangbuk-do, it was analyzed that if the REC weight was reduced to 3.4, it was more likely to link BESS than PV operated alone.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.952-965
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• 1993

A simulation modeling is necessary for the optimal design of a rice processing plant, which consists of a facility (a silo system) of rice drying and storage and a rice mill plant. In a rice processing plant, the production scheduling and the decision on capcity of each unit based on a queuing theory is very important and difficult. In this study a process-oriented simulation model was developed for the design of a rice drying and storage system with SLAMSYSTEM. The simulation model is capable of simulating virtually all the processing activities and provides work schedules which minimize total processing time , mean flow time and bottleneck of the plant system and estimate drying time for a batch in a drying silo. Model results were used for determination the size and capacity of each processing unit and for analyzing the performance of the plant . The developed model was actually applied to construct a grain silo system for rice drying and storage.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.969-978
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• 2016

Around the world are increasing the demand for ESS. Currently, the domestic is expected to benefit by operating ESS. In the domestic, it is expected to benefit from operations of the installed ESS because of the introduction of ESS less capacity. However ESS capacity to the maximum profit occurs is unknown. ESS is different from the charge-discharge characteristics and the reserve to replace, depending on the application. Therefore, it should be established in accordance with the ESS optimal capacity according to the purpose used because it can maximize the quality and efficiency of the electric energy. To the ESS optimal capacity estimation by the purpose used, It should compare the investment cost caused by ESS facility installation and operation cost caused by operating ESS. In this paper, the operation mathematical model for estimating marginal operation costs established. In operation mathematical model, operating cost is considered fuel cost and no-load cost start-up cost. Because no-load cost and start-up cost are not related to cost and power plant output, there are expressed an integer variable costs as a step function.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.248-256
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• 2021

Now that we're in the big data era, data has taken on a new significance as the storage capacity has exploded from trillion bytes to petabytes at breakneck pace. As the use of cloud computing expands and becomes more commonly accepted, several businesses and institutions are opting to store their requests and data there. Cloud storage's concept of a nearly infinite storage resource pool makes data storage and access scalable and readily available. The majority of them, on the other hand, favour a single cloud because of the simplicity and inexpensive storage costs it offers in the near run. Cloud-based data storage, on the other hand, has concerns such as vendor lock-in, privacy leakage and unavailability. With geographically dispersed cloud storage providers, multicloud storage can alleviate these dangers. One of the key challenges in this storage system is to arrange user data in a cost-effective and high-availability manner. A multicloud storage architecture is given in this study. Next, a multi-objective optimization problem is defined to minimise total costs and maximise data availability at the same time, which can be solved using a technique based on the non-dominated sorting genetic algorithm II (NSGA-II) and obtain a set of non-dominated solutions known as the Pareto-optimal set.. When consumers can't pick from the Pareto-optimal set directly, a method based on Principal Component Analysis (PCA) is presented to find the best answer. To sum it all up, thorough tests based on a variety of real-world cloud storage scenarios have proven that the proposed method performs as expected.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.1
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• pp.38-45
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• 2018

In September 2016, the government decided to apply a REC 5.0 weighting to solar-battery ESS to increase the supply of renewable energy. In this paper, we calculated the optimal capacity of battery ESS which maximizes the revenue when solar is linked with battery ESS. In the case study, the optimal capacity was calculated by applying the conservative REC price, and we studied sensitivity analysis about battery price and real-time REC price.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.33
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• pp.1-10
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• 1995

The allocation of files is essential to the efficiency and effectiveness of a distributed system that must meet geographically dispersed data processing demands. In this paper, we address an optimization model that generates optimal file migration policies in distributed database systems. The proposed model is a more generalized model that includes system's capacity constraints - computing sites' storage capacity and communication networks' capacity - which have not taken into consideration in previous researches. Using this model, we can establish initial file allocation, file reallocation and file migration polices that minimize a system operating cost under system's capacity constraints at an initial system design or reorganization point The proposed model not only can be adopted by small-sized systems but also provides a foundation for effective and simple heuristics for adaptive file migration in large systems.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.407-412
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• 2003

An effective methodology is .reported for determining the optimal capacity (lot-size) of batch processing and storage networks which include material recycle or reprocessing streams. We assume that any given storage unit can store one material type which can be purchased from suppliers, be internally produced, internally consumed and/or sold to customers. We further assume that a storage unit is connected to all processing stages that use or produce 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. The objective for optimization is to minimize the total cost composed of raw material procurement, 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 hold-up. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two subproblems. The first yields analytical solutions for determining batch 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 special case in which the number of storage is equal to the number of process stages and raw materials storage units, a complete analytical solution for average flow rates can be derived. The analytical solution for the multistage, strictly sequential batch-storage network case can also be obtained via this approach. The principal contribution of this study is thus the generalization and the extension to non-sequential networks with recycle streams. An illustrative example is presented to demonstrate the results obtainable using this approach.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.1
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• pp.21-26
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• 2018

Due to the international environmental regulations and changes in policies, the demand for generators using the renewable energy is increasing. However, renewable energy generators with intermittent output characteristics such as solar and wind power generators, need the buffer facilities such as ESS during system operations. However, because of low price competitiveness in energy storage system, it is difficult to operate the renewable energy generator with ESS. Therefore, the government has recently proposed a policy to compensate the REC for renewable energy system with ESS. For all this, since the initial cost of the ESS is high, it is the most important to calculate and operate the optimal capacity of the ESS through an economic analysis. In this paper, we proposed the method of calculation the optimal capacity of ESS and analyzed economic feasibility of renewable energy system using the ESS according to depreciation in ESS price.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.4
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• pp.294-300
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• 2004

This paper considers a trade-off effect between in-house storage space and leased storage space in generic warehouses operated under a randomized storage assignment policy. The amount of in-house storage space is determined based on the law of large numbers satisfying a given service level of protection against space shortages. Excess space requirement is assumed to be met via leased storage space. A new analytic model is formulated for determining the excess space such that the total cost of storage space is minimized. Finally, computational results are provided for the systems where the standard economic-order-quantity inventory model is used for all items.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1080-1088
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• 2014

By combining a wind turbine with an energy storage system (ESS), we are able to attenuate the intermittent wind power characteristic making the power derived from a wind farm dispatchable. This paper evaluates the influence of the phase delay of the low-pass filter in the conventional smoothing power control on the ESS capacity; longer phase delays require a larger ESS capacity. In order to eliminate the effect of the phase delay, we optimize the power dispatch using a zero-phase low-pass filter that results in a non-delayed response in the power dispatch. The proposed power dispatching method significantly minimizes the ESS capacity. In addition, the zero-phase low-pass filter, which is a symmetrical forward-reverse finite impulse response type, is designed simply with a small number of coefficients. Therefore, the proposed dispatching method is not only optimal, but can also be feasibly applied to real wind farms. The efficacy of the proposed dispatching method is verified by integrating a 3 MW wind turbine into the grid using wind data measured on Jeju Island.