• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2227-2235
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• 2018

Under the current policies and compensation rules in South Korea, Photovoltaic (PV) generation supplier can maximize the profit by combining PV generation with Energy Storage System (ESS). However, the existing operational strategy of ESS is not able to maximize the profit due to the limitation of ESS capacity. In this paper, new ESS scheduling algorithm is introduced by utilizing the System Marginal Price (SMP) and PV generation forecasting to maximize the profits of PV generation supplier. The proposed algorithm determines the charging time of ESS by ranking the charging schedule from low to high SMP when PV generation is more than enough to charge ESS. The discharging time of ESS is determined by ranking the discharging schedule from high to low SMP when ESS energy is not enough to maintain the discharging. To compensate forecasting error, the algorithm is updated every hour to apply the up-to-date information. The simulation is performed to verify the effectiveness of the proposed algorithm by using actual PV generation and ESS information.

• Smart Structures and Systems
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• v.17 no.3
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• pp.523-539
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• 2016

The ambient vibration measurement is an output-data-only dynamic testing where natural excitations are represented, for instance, by winds and typhoons. The modal identification involving output-only measurements requires the use of specific modal identification techniques. This paper presents the application of a reliable method (the Stochastic Subspace Identification - SSI) implemented in a general purpose software. As a criterion toward the robustness of identified modes, a bio-inspired optimization algorithm, with a highly nonlinear objective function, is introduced in order to find the optimal deployment of a reduced number of sensors across a large civil engineering structure for the validation of its modal identification. The Ting Kau Bridge (TKB), one of the longest cable-stayed bridges situated in Hong Kong, is chosen as a case study. The results show that the proposed method catches eigenvalues and eigenvectors even for a reduced number of sensors, without any significant loss of accuracy.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.1001-1007
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• 2006

In this paper we present robust optimal supporting positions for large glass panels used for TFT-LCD monitors when they are stored in a cassette during manufacturing process. The criterion taken is to minimize their maximum deflection. Since they are supported by some supports and have large deformations, contact analysis with a geometrically nonlinear effect is necessary. In addition, the center of a panel can not be positioned exactly as intended and should be considered as uncertainties. To take into account of these effects, the mean and the standard deviation of system response functions, particularly the deflection of the panels, need be calculated. A function approximation moment method (FAMM) is utilized to estimate them. It is a special type of response surface methodology for structural reliability analysis and can be efficiently used to estimate the two stochastic properties, that is, the system performance and the perturbations caused by uncertainties. For a design purpose, they are to be minimized simultaneously by some optimization algorithm to obtain robust optimal supporting positions.

• Journal of Korea Water Resources Association
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• v.31 no.1
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• pp.59-69
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• 1998

A regression model with basin physiographic characteristics as independent variables was calibrated for regional flood frequency analysis. In case that high correlations existing among the independent variables the ridge regression has been known to have capability of overcoming the problems of multicollinearity. To optimize the ridge regression model the cost function including regularization parameter must be minimized. In this research the genetic algorithm was applied on this optimization problem. The genetic algorithm is a stochastic search method that mimic the metaphor of natural biological heredity. Using this method the regression model could have optimized and stable weights of variables.

• Journal of Environmental Science International
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• v.11 no.12
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• pp.1217-1226
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• 2002

This study aims at the effective estimation of water supply capacity of small scale reservoir and the proposal of the data which is necessary to establish the water resources management plan of down stream area of the reservoir in the future by comparison and examination about reservoir operation technique for the security of agricultural water in small scale reservoir. The result of flow calculation by Tank model is used for the input data as the inflow data which is needed for the analysis of water supply capacity. Stochastic method, simulation method, and optimization method are used to examine the water supply capacity, and water security amount is compared with each method. From the analyses of water supply capacities by each method, slightly different results are shown in spite of the effort to compare them equally using input data such as inflow data under equal conditions, and the comparison of water supply capacities by each method are as follows; linear planning method, simulation method, and transition probability matrix method in the order of amount from the largest. It is thought that the simulation method in which comparatively reasonable application of the inflow data is possible and is simulated in successive time series dam operation of the three methods used in this study thus, simulation model is proper to estimate the water supply capacity of agricultural small scale reservoir. And it is judged that the heightening of efficiency of water resources utilization according to the development of downstream area of dam may be possible using the upward readjusted water supply amount of $55.18{\tiems}10^6ton$ and $63.7{\times}10^6ton$ at 95% and 90% supply reliability respectively which are above the planning water supply amount of $50.0{\times}10^6$ton when the simulation method is introduced as the standard.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.1
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• pp.231-243
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• 1994

A stochastic programming model for river water quality management was developed. River water quality, river flow, quality and flowrate of the wastewater treatment plant inflow were treated as random variables in the model. Withdrawal for water supply and submerged weir reaeration were included in the model itself. A probabilistic model was formulated to compute the expectation and variance of water quality using Streeter-Phelps equation. Chance constraints of the optimization problem were converted to deterministic equivalents by chance constrained method. Objective function was total annual treatment cost of all wastewater treatment plants in the region. Construction cost function and O & M cost function were derived in the form of nonlinear equations that are functions of treatment efficiency and capacity of treatment plant. The optimization problem was solved by nonlinear programming. This model was applied to the lower Han River. The results show that the reliability to meet the DO standards of the year 1996 is about 50% when the treatment level of four wastewater treatment plants in Seoul is secondary treatment, and BOD load from the tributary inflows is the same as present time. And when BOD load from Tanchon, Jungrangchon, and Anyangchon is decreased to 50%, the reliability to meet the DO standards of the year 1996 is above 60%. This results indicated that for the sake of the water quality conservation of the lower Han River, water quality of the tributaries must be improved, and at least secondary level of treatment is required in the wastewater treatment plants.

• Earthquakes and Structures
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• v.1 no.1
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• pp.109-127
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• 2010

This work aims at introducing structural sensitivity analysis capabilities into existing commercial finite element software codes for the purpose of mapping retrofit strategies for a broad group of structures including heritage-type buildings. More specifically, the first stage sensitivity analysis is implemented for the standard deterministic environment, followed by stochastic structural sensitivity analysis defined for the probabilistic environment in a subsequent, second phase. It is believed that this new generation of software that will be released by the industrial partner will address the needs of a rapidly developing specialty within the engineering design profession, namely commercial retrofit and rehabilitation activities. In congested urban areas, these activities are carried out in reference to a certain percentage of the contemporary building stock that can no longer be demolished to give room for new construction because of economical, historical or cultural reasons. Furthermore, such analysis tools are becoming essential in reference to a new generation of national codes that spell out in detail how retrofit strategies ought to be implemented. More specifically, our work focuses on identifying the minimum-cost intervention on a given structure undergoing retrofit. Finally, an additional factor that arises in earthquake-prone regions across the world is the random nature of seismic activity that further complicates the task of determining the dynamic overstress that is being induced in the building stock and the additional demands placed on the supporting structural system.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.3
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• pp.89-97
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• 1997

A genetic algorithm (GA) is a stochastic direct search strategy that mimics the process of genetic evolution. The GA applied herein works on a population of structural designs at any one time, and uses a structured information exchange based on the principles of natural selection and wurvival of the fittest to recombine the most desirable features of the designs over a sequence of generations until the process converges to a "maximum fitness" design. Principles of genetics are adapted into a search procedure for structural optimization. The methods consist of three genetics operations mainly named selection, cross- over and mutation. In this study, a method of finding the optimum topology of truss/beam structure is pro- posed by using the GA. In order to use GA in the optimum topology problem, chromosomes to FEM elements are assigned, and a penalty function is used to include constraints into fitness function. The results show that the GA has the potential to be an effective tool for the optimal design of structures accounting for sizing, geometrical and topological variables.variables.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.51 no.1
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• pp.5-14
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• 2002

In this paper, we analyze inductive interference in conductive material around 345 kV power transmission line, and evaluate the effects of mitigation wires. Finite element method (FEM) is used to numerically compute induced eddy currents as well as magnetic fields around powder transmission lines. In the analysis model, geometries and electrical properties of various elements such as power transmission line, buried pipe lines, overhead ground wire, and conducting earth are taken into accounts. The calculation shows that mitigation wire reduces fairly good amount of eddy currents in buried pipe line. To find the optimum magnetic field shielding location of mitigation wire, we applied evolution strategy algorithm, a kind of stochastic approach, to the analysis model. Finally, it was shown that we can find more effective shielding effects with optimum location of one mitigation wire than with arbitrary location of multi-mitigation wires around the buried pipe lines.

• Management Science and Financial Engineering
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• v.17 no.1
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• pp.45-63
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• 2011

The aim of this paper is to consider the process of supplying trained workers with knowledge and skills for upcoming business opportunities and the process of training apprentices to be prepared to meet future demands in an IT service firm. As the demand for new workers fluctuates, a firm should employ a buffer workforce such as apprentices or interns. However, as a result of rapid business development, the capacity of the buffer may be exceeded, thus requiring the company to recruit skilled workers from outside the firm. Therefore, it is important for a firm to map out a strategy for manpower planning so as to fulfill the demands of new business and minimize the operation costs related to training apprentices and recruiting experienced workers. First, this paper analyzes the supply and demand of workers for the IT service in a knowledge-intensive field. It then presents optimal human resource planning strategies via the familiar method of stochastic process. Also, we illustrate that our model is applied to the human resource planning of an information security service firm in South Korea.