• 대한전기학회논문지:전력기술부문A
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• 제50권9호
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• pp.424-430
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• 2001

A multi-level optimal power flow(OPF) algorithm has been evolved from a simple two stage optimal Power flow algorithm for constrained power economic dispatch control. In the proposed algorithm, we consider various constraints such as ower balance, generation capacity, transmission line capacity, transmission losses, security equality, and security inequality constraints. The proposed algorithm consists of four stages. At the first stage, we solve the aggregated problem that is the crude classical economic dispatch problem without considering transmission losses. An initial solution is obtained by the aggregation concept in which the solution satisfies the power balance equations and generation capacity constraints. Then, after load flow analysis, the transmission losses of an initial generation setting are matched by the slack bus generator that produces power with the cheapest cost. At the second stage we consider transmission losses. Formulation of the second stage becomes classical economic dispatch problem involving the transmission losses, which are distributed to all generators. Once a feasible solution is obtained from the second stage, transmission capacity and other violations are checked and corrected locally and quickly at the third stage. The fourth stage fine tunes the solution of the third stage to reach a real minimum. The proposed approach speeds up the two stage optimization method to an average gain of 2.99 for IEEE 30, 57, and 118 bus systems and EPRI Scenario systems A through D testings.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 C
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• pp.926-928
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• 1998

A fast optimization algorithm has been evolved from a simple two stage optimal power flow(OPF) algorithm for constrained power economic dispatch. In the proposed algorithm, we consider various constraints such as power balance, generation capacity, transmission line capacity, transmission losses, security equality, and security inequality constraints. The proposed algorithm consists of four stages. At the first stage, we solve the aggregated problem that is the crude classical economic dispatch problem without considering transmission losses. An initial solution is obtained by the aggregation concept in which the solution satisfies the power balance equations and generation capacity constraints. Then, after load flow analysis, the transmission losses of an initial generation setting are matched by the slack bus generator that produces power with the cheapest cost. At the second stage we consider transmission losses. Formulation of the second stage becomes classical economic dispatch problem involving the transmission losses, which are distributed to all generators. Once a feasible solution is obtained from the second stage, transmission capacity and other violations are checked and corrected locally and quickly at the third stage. The fourth stage fine tunes the solution of the third stage to reach a real minimum. The proposed approach speeds up the coupled LP based OPF method to an average gain of 53.13 for IEEE 30, 57, and 118 bus systems and EPRI Scenario systems A through D testings.

• 한국CDE학회논문집
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• 제14권5호
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• pp.297-305
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• 2009

Automatic generation of the mid-surfaces of a CAD model is becoming a useful function in that it can help increase the efficiency of engineering analysis as far as it does not affect the result seriously. Several methods had been proposed previously to automatically generate the mid-surfaces, but they often failed to generate the mid-surfaces of complex CAD models. Due to the inherent difficulty of this mid-surface generation problem, it may not be possible to come up with a complete and general method to solve this problem. Since a method that can handle a specific case may not work for different cases, it seems that developing case-specific methods ends up with solving only a fraction of the problem. In this paper, therefore, we propose a method to generate mid-surfaces based on a divide-and-conquer paradigm. This method first decomposes a complex CAD model into simple volumes. The mid-surfaces of the simple volumes are automatically generated by the existing methods, and then they are converted into the mid-surfaces of the original CAD model.

• 대한산업공학회지
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• 제39권3호
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• pp.183-191
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• 2013

We address the power generation mix problem that considers not only nuclear and fossil fuels such as oil, coal and LNG but also renewable energy technologies. Unlike nuclear or other generation technologies, the expansion plan of renewable energy is highly uncertain because of its dependency on the government policy and uncertainty associated with technology improvements. To address this issue, we conduct a delphi survey and forecast the capacity of renewable energy. We further propose a stochastic mixed integer programming model that determines an optimal capacity expansion and the amount of power generation using each generation technology. Using the proposed model, we test eight generation mix scenarios and particularly evaluate how much the expansion of renewable energy contributes to the total costs for power generation in Korea. The evaluation results show that the use of renewable energy incurs additional costs.

• 한국멀티미디어학회논문지
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• 제25권11호
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• pp.1572-1581
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• 2022

Energy conversion to renewable energy is being promoted to solve the recently serious environmental pollution problem. Solar energy is one of the promising natural renewable energy sources. Compared to other energy sources, it is receiving great attention because it has less ecological impact and is sustainable. It is important to predict power generation at a future time in order to maximize the output of solar energy and ensure the stability and variability of power. In this paper, solar power generation data and sensor data were used. Using the PCC(Pearson Correlation Coefficient) analysis method, factors with a large correlation with power generation were derived and applied to the GAM(Generalized Additive Model). And the prediction accuracy of the power generation prediction model was judged. It aims to derive efficient solar power generation in the future and improve power generation performance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 B
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• pp.1187-1188
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• 2006

This paper a new method which applies a genetic algorithm for determining which sectionalizing switch to operate in order to solve the distribution system loss minimization re-configuration problem. In addition, the proposed method introduces a ultra efficient MPP tracking in a solar power generation system.

• 한국정보시스템학회지:정보시스템연구
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• 제29권1호
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• pp.75-91
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• 2020

Purpose Retrofit, defined to be addition of new technologies or features to the old system to increase efficiency or to abate GHG emissions, is considered as an important alternative for the old coal-fired power plant. The purpose of this study is to propose mathematical method to model multiple alternative retrofit in Generation Capacity Expansion Planning(GCEP) problem, and to get insight to the retrofit patterns from realistic case studies. Design/methodology/approach This study made a multi-alternative retrofit GECP model by adopting some new variables and equations to the existing GECP model. Added variables and equations are to ensure the retrofit feature that the life time of retrofitted plant is the remaining life time of the old power plant. We formulated such that multiple retrofit alternatives are simultaneously compared and the best retrofit alternative can be selected. And we found that old approach to model retrofit has a problem that old plant with long remaining life time is retrofitted earlier than the one with short remaining life time, fixed the problem by some constraints with some binary variables. Therefore, the proposed model is formulated into a mixed binary programming problem, and coded and run using the GAMS/cplex. Findings According to the empirical analysis result, we found that approach to model the multiple alternative retrofit proposed in this study is comparing simultaneously multiple retrofit alternatives and select the best retrofit satisfying the retrofit features related to the life time. And we found that retrofit order problem is cleared. In addition, the model is expected to be very useful in evaluating and developing the national policies concerning coal-fired power plant retrofit.

• 한국건설관리학회논문집
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• 제8권6호
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• pp.235-245
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• 2007

This research study presents the development and application of an Elitist Genetic Algorithm (Elitist GA) for solving the resource-constrained project scheduling problem, which is one of the most challenging problems in construction engineering. Main features of the developed algorithm are that the elitist roulette selection operator is developed to preserve the best individual solution for the next generation so as to obtain the improved solution, and that parallel schedule generation scheme is used to generate a feasible solution to the problem. The experimental results on standard problem sets indicate that the proposed algorithm not only produces reasonably good solutions to the problems over the heuristic method and other GA, but also can find the optimal and/or near optimal solutions for the large-sized problems with multiple resources within a reasonable amount of time that will be applicable to the construction industry. This paper will help researchers and/or practitioners in the construction project scheduling software area with alternative means to find the optimal schedules by utilizing the advantages of the Elitist GA.

• 산업경영시스템학회지
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• 제24권65호
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• pp.89-102
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• 2001

In this paper, the aircraft route scheduling consists of two steps; the pairing generation and the aircraft assignment. The pairing generation is heuristic approach how flights construct pairings from and to the main base. The aircraft resource assignment which is to establish a aircraft route schedule is constructed by constraint satisfaction problem technique. ILOG solver and schedule is used to solve this problem. In addition, a aircraft route reschedule process against departure-arrival delay or aircraft maintenance schedule change is added by partial constraints satisfaction problem technique. Also, Gantt chart made by ILOG views is used to show aircraft route schedule results more easily.

• 한국실내디자인학회논문집
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• 제16권2호
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• pp.63-70
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• 2007

Analogy in problem solving is similarity-based reasoning facilitated by verbal and visual operation. This similarity-based reasoning generally supports initial phase of idea search. Therefore, this study intends to infer the types of problem solving by tracing the analogy use of verbal and visual representation through a experimental research. According to the result of this research, the types of problem solving by analogy are classified into 'evolving', 'divergent', and 'poor conversion' type. Firstly, 'evolving type' is distinguished between 'combination type' associated different contents to develope a new design and 'transformation type' associated similar words and sketches to be continuously revised and developed. In these types usually structural analogy rather than surface analogy is used. Secondly, in 'divergent type' associated words or sketches are individually represented, and among them one design solution is selected. In this type usually surface analogy is used. Thirdly, in 'poor conversion type' interaction between verbal representation and visual representation does not go on smoothly, and the generation of idea is poor. In here surface analogy is mostly used. These findings could form the basis of skill development of idea generation and conversion in design education.