• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.380-388
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• 2010

This paper explored an effective scheduling method for the Seoul-Busan High Speed Rail. It is important to decide train frequency influencing on scheduling method. Main factors to decide train frequency are location of station, social economic index, land use of station area and travel demand. In this paper, we focused on travel demand which is critical factor to decide train frequency. And we studied on standardized scheduling method. Simulation method is used to analyze the performance of explored method.

• 방송공학회논문지
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• 제14권2호
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• pp.189-196
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• 2009

통신과 방송이 융합되는 모바일 데이터 방송에서 방송 아이템 스케줄링을 위한 방법으로서, 주기적인 방법과 on-demand 방법을 혼합한 새로운 방법을 제안한다. 방송 아이템은 DMB 등의 하향 방송채널을 통하여 전달되고, 사용자들의 요구 메시지는 셀룰러 폰, 무선랜, 와이브로 등의 다양한 상향 통신채널을 통하여 서버에 전달되는 환경을 가정한다. 서버는 사용자들의 요구 통계를 바탕으로, 방송할 데이터 아이템들을 인기 아이템과 비인기 아이템의 집합으로 나눈다. 그리고 인기 아이템 주기적인 방법으로 전송되고, 비인기 아이템에는 on-demand 방법을 적용한 혼합 형태로 스케줄링한다. 시뮬레이션을 통한 성능평가를 수행하여, 제안하는 스케줄링 방법이 기존의 방법들에 비하여 적은 응답대기시간과 높은 응답성공률을 나타냄을 확인하였다.

• 전기학회논문지
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• 제68권3호
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• pp.405-415
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• 2019

The considerations of the electrical device' characteristics and the customers' satisfaction have been important criteria for efficient smart grid systems. In general, an electrical device is classified into a non-interruptible device or an interruptible device. The consideration of the type is an essential information for the efficient smart grid scheduling. In addition, customers' scheduling preferences or satisfactions have to be considered simultaneously. However, the existing research studies failed to consider both criteria. This paper proposes a new and efficient smart grid scheduling framework considering both criteria. The framework consists of two modules - 1) A day-head smart grid scheduling algorithm and 2) Real-time sudden demand negotiation framework. The first method generates the smart grid schedule efficiently using an embedded genetic algorithm with the consideration of the device's characteristics. Then, in case of sudden electrical demands, the second method generates the more efficient real-time smart grid schedules considering both criteria. In order to show the effectiveness of the proposed framework, comparisons with the existing relevant research studies are provided under various electricity demand scenarios.

• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.1843-1850
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• 2014

In this paper, we investigate a group building based power consumption scheduling to minimize the electricity cost. We consider the demand shift to reduce the peak load and suggest the compensation function reflecting the relationship between the change of the building demand and the occupants' comfort. Using that, the electricity cost minimization problem satisfied the convexity is formulated, and the optimal power consumption scheduling algorithm is proposed based on the iterative method. Extensive simulations show that the proposed algorithm achieves the group management gain compared to the individual building operation by increasing the degree of freedom for the operation.

• 한국통신학회논문지
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• 제35권9B호
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• pp.1407-1415
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• 2010

최근 전 세계적으로 많은 관심을 받고 있는 스마트 그리드는 기존 전력망의 에너지 효율을 최적화하고자 하는 차세대 전력망을 말한다. 그 중에서 수요 반응(Demand Response)은 현재 전력망과 차별화되는 핵심 기술이다. 가정에서 전력 요금의 최소화 및 사용자의 만족도를 최대화하기 위해, 본 논문은 가정에서 사용하고 있는 여러 종류의 전력 기계의 특성을 활용하여, 최적화 문제를 통한 스케쥴링 알고리듬을 제안한다. 여러 전력 기계의 소비패턴을 수학적 모델로 유도하였으며, 하루 동안 각 시간에서 전력 기계의 중요도에 따른 최적화된 스케쥴링 기법을 제안한다. 실제 통계 수치를 활용한 본 논문의 실험 결과에서는 제안하는 최적화 스케쥴링 알고리듬이 전력요금을 최소화하는 유틸리티에 매우 효과적인 것으로 나타났다.

• Journal of Electrical Engineering and Technology
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• 제12권5호
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• pp.1709-1718
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• 2017

This paper presents a hybrid stochastic deterministic multi-timescale scheduling (SDMS) approach for generation scheduling of a power grid. SDMS considers flexible resource options including conventional generation flexibility in a chance-constrained day-ahead scheduling optimization (DASO). The prime objective of the DASO is the minimization of the daily production cost in power systems with high penetration scenarios of variable generation. Furthermore, energy storage is scheduled in an hourly-ahead deterministic real-time scheduling optimization (RTSO). DASO simulation results are used as the base starting-point values in the hour-ahead online rolling RTSO with a 15-minute time interval. RTSO considers energy storage as another source of grid flexibility, to balance out the deviation between predicted and actual net load demand values. Numerical simulations, on the IEEE RTS test system with high wind penetration levels, indicate the effectiveness of the proposed SDMS framework for managing the grid flexibility to meet the net load demand, in both day-ahead and real-time timescales. Results also highlight the adequacy of the framework to adjust the scheduling, in real-time, to cope with large prediction errors of wind forecasting.

• 제어로봇시스템학회논문지
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• 제5권6호
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• pp.714-723
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• 1999

This paper presents a short-term scheduling algorithm for the operation of steelmaking processes. The scope of the problem covers refining of the hot iron transferred form a blast furnace, ladle treatment, continuous casting, hot-rolling, and coiling for the final products that should satisfy the given demand. The processing time at each unit depends on how much the batch amount is treated, and te dedicated intermediate storage with finite capacity between the units is considered. Resource constraints and initial amount of each state are incorporated into the presented scheduling model for the algorithm of on-line scheduling. We propose amixed integer linear programming (MILP) model with two objectives for the scheduling. The first is to maximize the total profit while atisfying the due date constraint for each product. And the second is to minimize the total processing time, makespan, while satisfying the demand for each product. Especially, we observe the effect of penalizing the intermediate storage and the inventory level of the final product on the scheduling results.

• ETRI Journal
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• 제35권4호
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• pp.677-686
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• 2013

In this paper, we first introduce a general architecture of an energy management system in a home area network based on a smart grid. Then, we propose an efficient scheduling method for home power usage. The home gateway (HG) receives the demand response (DR) information indicating the real-time electricity price, which is transferred to an energy management controller (EMC). Referring to the DR, the EMC achieves an optimal power scheduling scheme, which is delivered to each electric appliance by the HG. Accordingly, all appliances in the home operate automatically in the most cost-effective way possible. In our research, to avoid the high peak-to-average ratio (PAR) of power, we combine the real-time pricing model with the inclining block rate model. By adopting this combined pricing model, our proposed power scheduling method effectively reduces both the electricity cost and the PAR, ultimately strengthening the stability of the entire electricity system.

• 한국정보과학회논문지:시스템및이론
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• 제32권9호
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• pp.433-444
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• 2005

주문형 비디오 시스템에서 방송에 기초한 스케줄링 기법은 방대한 규모의 클라이언트에게 인기 비디오를 전파하기 위한 매우 효율적인 기술로 알려져 있다. 방송 스케줄링 기법의 주된 동기는 그들은 확장성이 매우 좋으며 아주 적당한 수준의 대역폭을 요구한다는 것이다. 본 논문은 FDBS로 명명된 새로운 동적 방송 스케줄링 기법을 제안하고 이 기법의 정확성을 증명한다. 그리고 시뮬레이션 방법을 통하여 FDBS의 성능을 평가한다 성능 평가 결과에 의하면 FDBS는 매우 적당한 수준의 대역폭을 요구하면서도 UD, CBHD, 그리고 NPB 기법보다 평균 응답시간에 있어서 더 우수한 성능을 보인다.

• Journal of Electrical Engineering and Technology
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• 제11권2호
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• pp.338-346
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• 2016

In order for the optimal solution of generators’ annual maintenance scheduling to be applicable to the actual power system it is crucial to incorporate the constraints related to the equivalent operation hours (EOHs) in the optimization model. However, most of the existing researches on the optimal maintenance scheduling are based on the assumption that the maintenances are to be performed periodically regardless of the operation hours. It is mainly because the computation time to calculate EOHs increases exponentially as the number of generators becomes larger. In this paper an efficient algorithm based on demand grouping method is proposed to calculate the approximate EOHs in an acceptable computation time. The method to calculate the approximate EOHs is incorporated into the optimization model for the maintenance scheduling with consideration on the EOHs of generators. The proposed method is successfully applied to the actual Korean power system and shows significant improvement when compared to the result of the maintenance scheduling algorithm without consideration on EOHs.