• Journal of Korea Water Resources Association
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• v.40 no.2 s.175
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• pp.101-112
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• 2007

In this study, a methodology was developed to evaluate the effects produced in the event of joint-operation of dams from the viewpoint of water use. It was applied to evaluating the actual results of dam operation in the Han River basin. In order to evaluate the effects of real joint-operation in terms of water supply and flow conditions, the methodology used the satisfaction rate of water requirement and the stability of flow conditions at the evaluation site as indicator. In order to evaluate the effects of joint-operation in terms of power generation, the total power generation produced by dams was used as evaluation indicator. Actual operation results were evaluated by comparison of evaluation indicators relating to single dam operation by which the notified mont of water was supplied, as well as to optimization models. Results of actual joint-operation of the Han River basin, from 2001 to 2004, were compared yearly with results from single operation and optimization model; in terms of water supply, the satisfaction ratio of water requirement stood at $94.36{\sim}99.68%$ for single operation, $97.16{\sim}99.90%$ for actual joint-operation, and 100.0 % for optimization model for all four years. The stability of flow condition was evaluated by the coefficient of river regime and coefficient of flow conditions definitely, indicating that flow conditions were more stable in case of actual operation and optimization models than in case of single operation. The actual total power generation was compared with that generated by other operation rules, indicating that the optimization model increased the power generation by $-3.47{\sim}6.54%$ compared with the actual total power generation, and that the single operation decreased the power generation amount by $12.68{\sim}38.94%$ compared with the actual total power generation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.8
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• pp.585-592
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• 1989

This paper presents an efficient algorithm for the reactive planning of transmission network under normal operating conditions. The optimal operation of a power system is a prerequisite to obtain the optimal investment planning. The operation problem is decomposed into a P-optimization module and a Q-optimization module, but both modules use the same objective function of generation cost. In the investment problem, a new variable decomposition technique is adopted which can operate the operation and the investment variables. The optimization problem is solved by using the gradient projection method (GPM).

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.9 no.3
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• pp.410-425
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• 1997

Buildings are mostly under part load conditions causing an inefficient system operation in terms of energy consumption. It is critical to operate building air-conditioning system with a scientific or optimal manner which minimizes energy consumption and maintains thermal comfort by matching building sensible and latent loads. Little research has been performed in developing general methodologies for the optimal operation of air-conditioning system. Based on this research motivation, system simulation program was developed by adopting various equipment operating strategies which are energy efficient especially for humidity control in summer. A numerical optimization technique was utilized to search optimal solution for multi-independent variables and then linked to the developed system simulation model within a mam program. The main goal of the study is to provide a systematic framework and guideline for the optimal operation of air-conditioning system focusing on air-side. For given cooling loads and ambient outdoor conditions the optimal operating strategies of a commercial building are determined by minimizing a constrained objective function by a nonlinear programming technique. Desired space setpoint conditions were found through evaluating the trade-offs between comfort and system power consumption. The results show that supply airflow rate and compressor fraction play main roles in the optimization process. It was found that variable setpoint optimization technique could produce lower indoor humidity level demanding less power consumption which will be benefits for building applications of humidity problem.

• Journal of Biosystems Engineering
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• v.29 no.1
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• pp.53-58
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• 2004

The purpose of this study was to evaluate an optimization model to determine the operation conditions of the chestnuts flame peeling system. The results of this study were summarized as follows. The optimization model was developed and evaluated to represent the flame peeling characteristics of the domestic chestnuts. When the heating depth was selected for various utilization of the peeled chestnuts, the model could determine the optimal conditions of the hardness of the chestnut shells, the flame temperature, and the flame time to get the maximum peeling ratio of the chestnut flame peeling system. When the heating depth was limited to 2.2 mm, the optimization model determined the proper operation conditions and the maximum peeling ratio such as 1594 g/$\textrm{mm}^2$ of the hardness of the chestnut shells, 780$^{\circ}C$ of the flame temperature, 29 second of the flame time, and 98.1 % of the peeling ratio.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.7
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• pp.37-45
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• 2004

Grinding is a finishing operation of products in various areas. Surface roughness of industrial components obtained in grinding operation is a critical quality measure but is a function of many operating parameters and their interactions. To achieve higher surface roughness and to identify the influence of grinding parameters on surface roughness, it is an ideal situation fer using the design of experiments. This paper presents an successful optimization of grinding conditions and prediction of surface roughness using the design of experiments. From the experimental verification tests, it was observed that this approach was useful as a robust design methodology for grinding operation.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.537-539
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• 2015

considerate operation is a major issue in the equipment-intensive operation. Identifying an optimal equipment combination is important to achieve low-energy operations. An Earthwork operation planning system, which measures the energy consumption of construction operations by taking into account construction equipments' engineering attributes (e.g., weight, capacity, energy consumption rate, etc.) and operation conditions (e.g., road condition, attributes of materials to be moved, geometric information, etc.), is essential to achieve the low-energy consumption. This study develops an automated computerized system which identifies an optimal earthmoving equipment fleet minimizing the energy consumption. The system imports a standard template of earthmoving operation model and compares numerous scenarios using alternative equipment allocation plans. It finds the fleet that minimizes the energy consumption by enumerating all cases using sensitivity analysis. A case study is presented to verify the validity of the system.

• Journal of Hydrogen and New Energy
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• v.24 no.1
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• pp.50-60
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• 2013

High temperature proton exchange membrane fuel cells (PEMFCs) using phosphoric acid (PA) doped polybenzimidazole (PBI) membranes have been concentrated as one of solutions to the limits with traditional low temperature PEMFCs. However, the amount of reported experimental data is not enough to catch the operational characteristics correlated with cell performance and durability. In this study, design of experiments (DOE) based operational optimization method for high temperature PEMFCs has been proposed. Response surface method (RSM) is very useful to effectively analyze target system's characteristics and to optimize operating conditions for a short time. Thus RSM using central composite design (CCD) as one of methodologies for design of experiments (DOE) was adopted. For this work, the statistic models which predict the performance and degradation rate with respect to the operating conditions have been developed. The developed performance and degradation models exhibit a good agreement with experimental data. Compared to the existing arbitrary operation, the expected cell lifetime and average cell performance during whole operation could be improved by optimizing operating conditions. Furthermore, the proposed optimization method could find different new optimal solutions for operating conditions if the target lifetime of the fuel cell system is changed. It is expected that the proposed method is very useful to find optimal operating conditions and enhance performance and durability for many other types of fuel cell systems.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.582-588
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• 1993

A scheme of dynamic optimization for batch reactor his been developed and applied to a semi-batch esterification reactor. To obtain optimal operating conditions for the given semi-batch reactor system with complex reaction kinetic and process constraints, a general nonlinear programming solver and finite element techniques have been introduced. The optimization results for the complex reactor system have been compared with those of Kumar et al. [1984] to show better optimization performance. The proposed optimizing scheme has been applied to the free end time problem to obtain the realistic operating condition. The results can supply valuable information for economic operation of the given batch esterification reactor.

• International Journal of Korean Welding Society
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• v.3 no.2
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• pp.15-23
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• 2003

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.879-884
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• 1988

For more economical operation of chemical plants, optimal operating conditions are to be set and maintained as far as possible. For this purpose, optimizing control is applied to chemical plants. In this study, a process optimizer composed of a process simulator and an optimization routine using Successive Quadratic Programming as optimization technique is developed and the effect of optimizing control is tested on an example process, and a new process optimization strategy based on modified Jacobian matrix is developed.