• 대한전기학회논문지
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• 제43권3호
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• pp.351-362
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• 1994

This paper presents a new method for solving a long term unit commitment problem including hydro and pumped storage hydro units in a large scale power system. The proposed method makes it possible to get variable power of hydro and pumpde storage hydro units and results in the better unit commitment with good convergency. Moreover this paper proposes an unit commitment algorithm to consider variable power of these units effectively by Lagrangian Relaxation method. By applying the proposed method to the test system and the real system, it is verified the usefulness of this method.

• 대한전기학회논문지:전력기술부문A
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• 제51권12호
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• pp.591-596
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• 2002

This Paper Presents a new methodology for Direct Load Control(DLC) and Unit Commitment. To consider economical effect of DLC, we developed 3-Dimensional dynamic programming which can combine unit commitment and DLC. Traditional dynamic programming has 2-Dimensional which consist of state and stage, but newly developed dynamic programming has DLC state, U.C. state, and stage. As a result, economical DLC and unit commitment schedule of the power system is possible. This method is applied to the test system, and the usefulness of the method is verified.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1506-1509
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• 1999

This paper presents a new economic dispatch algorithm to improve the unit commitment solution while guaranteeing the near optimal solution without reducing calculation speed. The conventional economic dispatch algorithms have the problem that it is not applicable to the unit commitment formulation due to the frequent on/off state changes of units during the unit commitment calculation. Therefore, piecewise linear iterative method have generally been used for economic dispatch algorithm for unit commitment. In that method, the approximation of the generator cost function makes it hard to obtain the optimal economic dispatch solution. In this case, the solution can be improved by introducing a inverse of the incremental cost function. The proposed method is tested with sample system. The results are compared with the conventional piecewise linear iterative method. It is shown that the proposed algorithm yields more accurate and economical solution without calculation speed reduction.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 추계종합학술대회
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• pp.713-716
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• 2001

본 연구에서는 전력계통의 경제적인 운용의 일환으로 DLC와 기동정지계획을 연계하여, DLC에 의해 조절되는 부하에 대응할 수 있는 기동정지계획을 수립할 수 있도록 하였다. 이의 방법으로, 동적계획법에서의 State를 DLC에 의해 변화하는 부하에 대응할 수 있도록 화장하는 3차원 동적계획법을 구성함으로써 DLC와의 연계를 가능토록 한 것이다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 C
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• pp.1066-1068
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• 1998

Many other unit commitment performed by complex mathmatical problems and algorithmm. but fuzzy logic is not concerned with mathmatical formulations so unit commitment is scheduled with ease. and fuzzy can express many constraints which has uncertanity feasibly because it use lingustic expressions. In this paper MATLAB is used as a simulation tool. Fuzzy Toolbox is made to make fuzzy control systems. Using this Toolbox easily and effectly we can make good unit commitment.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.415-422
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• 2014

This paper presents a new approach to solve the multi area unit commitment problem (MAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method. The objective of this paper is to determine the optimal or near optimal commitment schedule for generating units located in multiple areas that are interconnected via tie lines. The evolutionary programming based particle swarm optimization method is used to solve multi area unit commitment problem, allocated generation for each area and find the operating cost of generation for each hour. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. Case study of four areas with different load pattern each containing 7 units (NTPS) and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the operating cost using evolutionary programming-based particle swarm optimization method with conventional dynamic programming (DP), evolutionary programming (EP), and particle swarm optimization (PSO) method. Experimental results show that the application of this evolutionary programming based particle swarm optimization method has the potential to solve multi area unit commitment problem with lesser computation time.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.203-205
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• 1999

The unit commitment is an important problem of production scheduling which determines the generating unit to in service(on/off) during scheduling period, to meet system demand and reserve requirement at minimum cost. This paper presents an box type crossover to improve searching ability of GA, to solve unit commitment problem. Satisfactory results are obtained by GA with the proposed crossover operator.

• 전기학회논문지
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• 제60권4호
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• pp.717-725
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• 2011

In the power system with an electric storage system that can increase utilization rate of the source of such new renewable energy, this paper introduces the approach on the daily unit commitment scheduling that determines simultaneously optimum operational condition and output of thermal generators and electric storage device. The unit commitment is one of the most important issues in economic operation and security of short-term operational plan of the power system. It is to determine on/off status of generator to minimize operational cost during the given period. The committed generator should satisfy various operational limitation such as estimated demand by system, spinning reserve condition within minimum operational cost. In order to determine on/off or charge/discharge/idle condition and output level of units and electric storage system, the MILP(Mixed Integer Linear Programming) is suggested. The proposed approach is the mixed method between LP(Linear Programming) and IP(integer programming) which seeks the value of real number and integer that maximize or minimize function objective within given condition. The daily unit commitment problem with the electric storage system is applied to MILP algorithm through linearization and formulation process. The proposed approach is applied to the test system.

• Water Engineering Research
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• 제1권4호
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• pp.279-291
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• 2000

A mathematical model using dynamic programming approach is applied to an optimal unit commitment problem. In this study, the units are treated as stages instead of as state dimension, and the time dimension corresponds to the state dimension instead of stages. A considerable amount of computer time is saved as compared to the normal approach if there are many units in the basin. A case study on the Lower Colorado River Basin System is presented to demonstrate the capabilities of the optimal scheduling of hydropower units.

• Journal of Electrical Engineering and Technology
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• 제4권2호
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• pp.159-167
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• 2009

This paper presents the Improved Pre-prepared Power Demand (IPPD) table and Muller's method as a means of solving the Profit Based Unit Commitment (PBUC) problem. In a deregulated environment, generation companies (GENCOs) schedule their generators to maximize profits rather than to satisfy power demand. The PBUC problem is solved by the proposed approach in two stages. Initially, information concerning committed units is obtained by the IPPD table and then the subprob-lem of Economic Dispatch (ED) is solved using Muller's method. The proposed approach has been tested on a power system with 3 and 10 generating units. Simulation results of the proposed approach have been compared with existing methods and also with traditional unit commitment. It is observed from the simulation results that the proposed algorithm provides maximum profit with less computational time compared to existing methods.