• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.10
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• pp.1548-1553
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• 2012

The important requirement for microgrid operation is to meet the balance between supply and demand. To meet, Combined Heat and Power (CHP) generation should be considered in microgrid scheduling. CHP generation is economical on the side of a consumer because it products heat and power. Therefore, it is high efficient. This paper presents a mathematical model for optimal microgrid operation including CHP generation using the optimal ratio of heat and power due to demand. The objective function and constraints are modeled by linear program (LP). Through the case study, the validation of the proposed model is shown.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.594-595
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• 2011

본 논문에서 수요 자원의 수요 반응 프로그램 참여에 관한 정보들을 등록 정보와 참여 정보로 구분하여 수요 자원의 특성을 나타내는 지수들로 구분한다. 이 지수들은 수요 반응 참여 가능 용량, 기간, 횟수, 한계 비용에 관하여 정보를 제공하며 이들을 바탕으로 수요 자원을 하나의 발전 자원으로 평가한다. 이로써 수요 자원은 발전 자원과 직접적으로 경쟁할 수 있으며 계통 운영자는 수요 자원을 운영 계획에 포함한다. 계통 운영자는 발전 및 수요 반응 비용을 최소화하여 운영 계획을 수행하는데 이때 발전 자원과 수요 자원의 제약 조건을 위반하지 않아야 한다. 본 논문에는 기존 개발된 발전 자원의 제약 조건으로부터 수요 자원의 제약 조건을 제안한다.

• IE interfaces
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• v.15 no.1
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• pp.99-106
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• 2002

A recently developed alternative to traditional production planning and control systems such as material requirement planning(MRP) and just-in-time(JIT) is the drum-buffer-rope(DBR). The DBR now being implemented in growing number of manufacturing organizations enables better scheduling and decision making on the shop floor. In implementing the DBR, however, an information system is usually needed to transmit the signal that runs from the constraint to material release. In this paper we propose a different mechanism to transmit the signal in the case that the demand of product is stable, which uses the well-known Kanban system. To improve the reality, this paper shows and example of the Kanban format, its operation, and calculation of the number of Kanbans.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.33-51
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• 1998

The industrial operation is one of the three basic modes of shipping operation with liner and Tramp operations. Industrial operators usually control vessels of their own or on a time charter to minimize the cost of shipping their cargoes. Such operations abound in shipping of bulk commodities, such as oil, chemicals and ores. This work is concerned with an operational optimization analysis of the fleet owned by a major oil company. a typical industrial operator. The operational optimization problem of the fleet of a major oil company is divided Into two phase problem. The front end corresponds to the optimization problem of the transportation of crude oil. product mix. and the distribution of product oil to comply with the demand of the market. The back end tackles the scheduling optimization problem of the fleet to meet the seaborne transportation demand derived from the front end. A case study reflecting the practices of an international major oil company is demonstrated to make clear the underlying ideas.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.529-530
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• 2015

스마트그리드 환경에서 증가하는 에너지 수요에 대응하기 위하여 수요 반응(Demand response, DR) 프로그램에 대한 연구가 활발히 진행 중에 있다. 특히, 전력 분야에서는 공급측 자원과 수요측 자원을 효율적으로 운영하기 위하여 수요 반응에 기반한 마이크로그리드 운영 기술이 요구되며, 추후 마이크로그리드의 실 시스템에 많은 도입이 예상된다. 본 논문에서는 TOU(Time-of-use)와 DLC(Direct load control)에 기반한 마이크로그리드의 최적 운영계획을 수립하고, 시뮬레이션을 통하여 제안된 수리적 모델의 타당성을 검토하고자 한다.

• Journal of the Korean Institute of Navigation
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• v.23 no.4
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• pp.63-76
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• 1999

This paper aims at developing an integrated fleet management support system for industrial carriers who usually control the vessels of their own or on a time charter to minimize the cost of shipping their cargoes. The work is mainly concerned with the operational management problem of the fleet owned by a major oil company, a typical industrial carrier. The optimal fleet management problem for the major oil company can be divided into two phase problem. The front end corresponds to the production operation problem of the transportation of crude oil, the refinery operation, and the distribution of product oil to comply with the demand of the market. The back end is to tackle the fleet scheduling problem to meet the seaborne transportation demand derived from the front end. Relevant optimization models for each phase are proposed and described briefly. Then a user-friendly integrated fleet management support system is built based on the proposed optimization models for both ends under Windows environment. A case study reflecting the practices of fleet management problem for the major oil company is carried out by using the system.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.337-340
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• 2000

In this paper, the effects of the uncertain hourly load demand are stochastically analyzed especially by the consideration of the average over generation of the Unit Commitment(UC) results. In order to minimize the effects of the actual load profile change, a new UC algorithm is proposed. The proposed algorithm calculates the UC results with the lower load level than the one generated by the conventional load forecast. In case of the worse load forecast, the deviation of the conventional UC solution can be overcome with the lower load level and the more hourly reserve requirements. The proposed method is tested with sample systems, which shows that the proposed method can be used as the basic guideline for selecting the potimal load forecast applying to UC problem.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.847-852
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• 2003

This paper implements MOD system using multicast delivery. Conventional system provide server-based system in multicast delivery but implemented system provides on-demand client-based multicast system. The scheduler aggregates clients' request and it generate multcast group addresses and port numbers according to requested video items and service request time. Then it transmits immediately multicast address to MOD server and client who request service. And then MOD server transmits requested streams with a multicast group address and the client joins the group automatically. The scheduler assigns the same multicast group address when other clients request an identical video within the same scheduling duration. The system can reduce load of server and support many clients at the same time.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.11
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• pp.1495-1504
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• 2013

Renewable energy integration and increased system complexities make system operator maintain supply and demand balance harder than before. To keep the grid frequency in a stable range, an appropriate spinning reserve margin should be procured with consideration of ever-changing system situation, such as demand, wind power output and generator failure. This paper propose a novel concept of dynamic reserve, which arrange different spinning reserve margin depending on time. To investigate the effectiveness of the proposed dynamic reserve, we developed a new short-term reliability criterion that estimates the probability of a spinning reserve shortage events, thus indicating grid frequency stability. Uncertainties of demand forecast error, wind generation forecast error and generator failure have been modeled in probabilistic terms, and the proposed spinning reserve has been applied to generation scheduling. This approach has been tested on the modified IEEE 118-bus system with a wind farm. The results show that the required spinning reserve margin changes depending on the system situation of demand, wind generation and generator failure. Moreover the proposed approach could be utilized even in case of system configuration change, such as wind generation extension.