• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.347-349
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• 2000

Under an open transmission access, the generation dispatch is determined by the bidding process of market participants. Congestion occurs when the dispatch would result in the violation of operational constraints. Congestion problem is formulated and solved by OPF(optimal power flow) calculation. The objective functions in OPF are given as quadratic cost functions or piecewise linear functions of bidding functions. In this study, the optimization technique of generation dispatch is presented for the combination of two types of quadratic and linear cost functions.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.12
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• pp.603-610
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• 2002

In this paper, a new economic dispatch algorithm for unit commitment is proposed to improve both the accuracy of the final solution and the calculation speed of economic dispatch. By using the inverse incremental cost functions, economic dispatch can be transformed into a simple optimization problem associated with an n-th order polynomial equation. The proposed method remarkably reduces the computation time with adaptability to any higher order generation cost functions. The proposed method is tested with sample system, which shows that the proposed algorithm yields more accurate and economical generation scheduling results with high computation speed.

• Proceedings of the KIEE Conference
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• summer
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• pp.348-350
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• 2004

This paper presents the scheme for reliability improvement by dispersed generation system (US) installation and operation in distribution systems. The objective functions such as power losses cost, operation cost of DGS, power buy cost and interruption cost are minimized for reliability improvement. The original objective functions and constraints are transformed into the equivalent multiple objective functions with fuzzy sets to evaluate their imprecise nature. The several indices for reliability evaluation are improved by dispersed generation system installation.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.143-146
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• 2004

This paper presents a method to improve reliability by dispersed generation (DG) installation considering load types and interruption cost. The objective functions such as power losses cost, operation cost of DGS, power buy cost and interruption cost are minimized for reliability improvement and efficient operation. The several indices for reliability evaluation are improved by dispersed generation system installation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.11
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• pp.520-527
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• 2001

This paper suggests a new methodology of evolutionary computations - an Adaptive Evolutionary Algorithm (AEA) for solving the Economic Load Dispatch (ELD) problem which has piecewise quadratic cost functions and prohibited operating zones with many local minima. AEA uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations: global search capability of GA and local search capability of ES. In the reproduction procedure, proportions of the population by GA and the population by ES are adaptively modulated according to the fitness. Case studies illustrate the superiority of the proposed methods to existing conventional methods in power generation cost and computation time. The results demonstrate that the AEA can be applied successfully in the solution of ELD with piecewise quadratic cost functions and prohibited operating zones

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.5
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• pp.591-595
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• 2013

This paper presents a method of generation rescheduling using Newton's Approach which searches the solution of the Lagrangian function. The generation fuel cost and $CO_2$ emission cost functions are used as objective function to reallocate power generation while satisfying several equality and inequality constraints. The Pareto optimum in the fuel cost and emission objectives has a number of non-dominated solutions. The economic effects are analyzed under several different conditions, and $CO_2$ emission reductions offered by the use of storage are considered. The proposed approach can explore more efficient and noninferior solutions of a Multiobjective optimization problem. The method proposed is applied to a 4-machine 6-buses system to demonstrate its effectiveness.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1270-1272
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• 1999

The generator cost function is one of the basic data for the generation scheduling. Generally the cost functions are obtained form design calculations or from heat rate tests. The real operating condition may be different from the condition of design or the tests. Some of the conditions may not be tested during the periodical maintenance. In order to improve the calculation of the generator cost function, this paper presents a new calculation method of the generator cost functions using the utilization factors of generators and the mixed fuel burning ratio of the generators.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.88-93
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• 2024

The main problem with existing edge detection techniques is that they have many limitations in detecting edges for complex and diverse images that exist in the real world. This is because only edges of a defined shape are discovered based on an accurate definition of the edge. One of the methods to solve this problem is the cost minimization method. In the cost minimization method, cost elements and cost functions are defined and used. The cost function calculates the cost for the candidate edge model generated according to the candidate edge generation strategy, and if the cost is found to be satisfactory, the candidate edge model becomes the edge for the image. In this study, we proposed an enhanced candidate edge generation strategy to discover edges for more diverse types of images in order to improve the shortcoming of the cost minimization method, which is that it only discovers edges of a defined type. As a result, improved edge detection results were confirmed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.12
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• pp.597-602
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• 2002

The restructuring of power industry is still going on all over the world for last several decades. Many kinds of restructuring model have been studied, proposed, and applied. Among those models, power pool is more popular than other. This paper assumes the power pool market structure having competitive generation sector, and a new method is presented to build a bidding strategy in that market. The utilities participating in the market have the perfect information of their cost and price functions, but they don't know which strategy to be chosen by others. To define one's strategy as a vector, we make utility's cost/price functions into discrete step functions. An utility knows only his own strategy, so he estimates the other's cost/price functions into discrete step functions. An utility knows only his own strategy, so he estimates the other's strategy using Nash equilibrium or stochastic methods. And he also has to forecast the system demand. According to this forecasting result, his payoffs can be changed. Considering these all conditions, we formulate a bidding game problem and apply noncooperative game theory to that problem for the optimal strategy or solution. Some restrictive assumption are added for simplification of solving process. A numerical example is given in Case Study to show essential features and concrete results of this approach.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.486_487
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• 2009

This paper presents a method for optimal operation to improve reliability of MicroGrid systems considering load types and interruption cost. The objective functions such as power losses cost, operation cost of dispersed generations, power purchasing cost, and interruption cost are minimized for reliability improvement and efficient operation. The several indices for reliability evaluation are improved by renewable energy sources installation.