• 한국ITS학회:학술대회논문집
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• 한국ITS학회 2008년도 제7회 추계학술대회 및 정기총회
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• pp.428-436
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• 2008

• 대한전기학회:학술대회논문집
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• 대한전기학회 1986년도 하계학술대회논문집
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• pp.296-299
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• 1986

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 춘계학술대회 논문집
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• pp.107-108
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• 2010

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(I)
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• pp.633-635
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• 1987

• 전기학회논문지
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• 제62권5호
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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.

• Journal of Electrical Engineering and Technology
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• 제12권5호
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• pp.1729-1742
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• 2017

In designing System Protection Schemes (SPSs) in power systems, protecting transmission network against extreme undesired conditions becomes a significant challenge in mitigating the transmission line overloading. This paper presents an intelligent Special Protection and Control Scheme (SPCS) using of Differential Evolution with Adaptive Mutation (DEAM) approach to obtain the optimum generation rescheduling to solve the transmission line overloading problem in system contingency conditions. DEAM algorithm employs the attraction-repulsion idea that is applied in the electromagnetism-like algorithm to support the mutation process of the conventional Differential Evolution (DE) algorithm. Different N-1 contingency conditions under base and increase load demand are considered in this paper. Simulation results have been compared with those acquired from Genetic Algorithm (GA) application. Minimum severity index has been considered as the objective function. The final results show that the presented DEAM method offers better performance than GA in terms of faster convergence and less generation fuel cost. IEEE 30-bus test system has been used to prove the effectiveness and robustness of the proposed algorithm.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.820-831
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• 2015

In a deregulated electricity market, congestion of the transmission lines is a major problem the independent system operator (ISO) would face. Rescheduling of generators is one of the most practiced techniques to alleviate the congestion. However, not all generators in the system operate deterministically and independently, especially wind power generators (WTGs). Therefore, a novel optimal rescheduling model for congestion management that accounts for the uncertain and correlated power sources and loads is proposed. A probabilistic power flow (PPF) model based on 2m+1 point estimate method (PEM) is used to simulate the performance of uncertain and correlated input random variables. In addition, the impact of direct electricity purchase contracts on the congestion management has also been studied. This paper uses artificial bee colony (ABC) algorithm to solve the complex optimization problem. The proposed algorithm is tested on modified IEEE 30-bus system and IEEE 57-bus system to demonstrate the impacts of the uncertainties and correlations of the input random variables and the direct electricity purchase contracts on the congestion management. Both pool and nodal pricing model are also discussed.

• Journal of Electrical Engineering and Technology
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• 제3권2호
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• pp.199-206
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• 2008

The introduction of competition in electricity markets emphasizes the importance of sufficient transmission capacities to guarantee effective power transactions. Therefore, for the economic and stable electric power system operation, transmission security constrains should be incorporated into the dispatch scheduling problem. With the intent to solve this problem, we decompose a dispatch scheduling problem into a master problem(MP) and several subproblems(SPs) using Benders decomposition. The MP solves a general optimal power flow(OPF) problem while the SPs inspect the feasibility of OPF solution under respective transmission line contingencies. If a dispatch scheduling solution given by the MP violates transmission security constraints, then additional constraints corresponding to the violations are imposed to the MP. Through this iterative process between the MP and SPs, we derive an optimal dispatch schedule incorporating the post-contingency corrective rescheduling. In addition, we consider interruptible loads as active control variables since the interruptible loads can participate as generators in competitive electricity markets. Numerical examples demonstrate the efficiency of the proposed algorithm.

• 산업경영시스템학회지
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• 제20권44호
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• pp.185-195
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• 1997

In this paper, research and applications of a knowledge-base system in scheduling are review. The method is based on the problem-solving techniques developed in artificial intelligent. The object of this paper is to enable the re-time rescheduling under dynamic environments. Developed to KBS(Knowledge-Based Scheduling) system in this paper, will based on expert system, and applicate to requirement of users effectively.

• 산업공학
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• 제9권2호
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• pp.75-82
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• 1996

A scheduling system is developed for a parallel machine flow shop which reflects the situations of the manufacturing processes in the tire industry. The schedule is generated via simulation using heuristic rules to get satisfaction on such constraints as due dates, demands, work-in-process, process capacity, set-up times and scheduling speed. This system, constructed with relational DB, SQL and C language, consumes less than 10 minutes of PC simulation to handle real size problems.