• 전기학회논문지
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• 제63권1호
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• pp.18-26
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• 2014

A microgrid can play a significant role for enlargement of renewable energy sources and emission reduction because it is a network of small, distributed electrical power generators operated as a collective unit. In this paper, an application of optimization method to economical operation of a microgrid is studied. The microgrid to be studied here is composed of distributed generation system(DGS), battery systems and loads. The distributed generation systems include combined heat and power(CHP) and small generators such as diesel generators and the renewable energy generators such as photovoltaic(PV) systems, wind power systems. Both of thermal loads and electrical loads are included here as loads. Also the emissions trading scheme to be applied in near future, the cost of unit start-up and the operational characteristics of battery systems are considered as well as the probabilistic characteristics of the renewable energy generation and load. A mathematical equation for optimal operation of this system is modeled based on the mixed integer programming. It is shown that this optimization methodology can be effectively used for economical operation of a microgrid by the case studies.

• 전기학회논문지
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• 제66권2호
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• pp.305-314
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• 2017

Most of the existing researches on systemwide optimization of generator maintenance scheduling do not consider the equivalent operating hours(EOHs) mainly due to the difficulties of calculating the EOHs of the CCGTs in the large scale system. In order to estimate the EOHs not only the operating hours but also the number of start-up/shutdown during the planning period should be estimated, which requires the mathematical model to incorporate the economic dispatch model and unit commitment model. The model is inherently modelled as a large scale mixed-integer nonlinear programming problem and the computation time increases exponentially and intractable as the system size grows. To make the problem tractable, this paper proposes an EOH calculation based on demand grouping by K-means clustering algorithm. Network congestion is also considered in order to improve the accuracy of EOH calculation. This proposed method is applied to the actual Korean electricity market and compared to other existing methods.

• 전기학회논문지
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• 제57권4호
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• pp.692-699
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• 2008

Semiconductor research and development(R&D) fabs are very different than production fabs in many ways such as the scales of production, job priority, production methods, and performance measures. Efficient operations of R&D fabs are very important to the development of new product, process stability, high yield, and ultimately company competitiveness. This paper proposes the fab-wide scheduling method for operational optimization of the R&D fabs. Most scheduling systems of semiconductor fabs have only focused on maximizing throughput of each separated areas without considering WIP(works in process) flows of entire fab. In this paper, we proposes the a fab-wide scheduling system which schedules all lots to entire fab equipment at once. We develop the MIP(mixed integer programing) model which allocates the lots to production equipment considering many constraints of all processes and the CP(constraint programming) model which determines the sequences of the lots in the production equipment. The proposed FAB-wide scheduling model is applied to the newly constructed R&D fab. As a result, we have accomplished the system based automated job reservation, decrease of the hot lot delay, increase of the queue time satisfaction, the high throughput by maximizing the batch sizes, decrease of the WIP TAT(Turn Around Time).

• Journal of Information Processing Systems
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• 제17권4호
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• 산업경영시스템학회지
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• 제39권2호
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• pp.28-36
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• 2016

Recently, owing to the development of ICT industry and wide spread of smart phone, the number of people who use car sharing service are increased rapidly. Currently two-way car sharing system with same rental and return locations are mainly operated since this system can be easily implemented and maintained. Currently the demand of one-way car sharing service has increase explosively. But this system have several obstacle in operation, especially, vehicle stock imbalance issues which invoke vehicle relocation. Hence in this study, we present an optimization approach to depot location and relocation policy in one-way car sharing systems. At first, we modelled as mixed-integer programming models whose objective is to maximize the profits of a car sharing organization considering all the revenues and costs involved and several constraints of relocation policy. And to solve this problem efficiently, we proposed a new method based on particle swarm optimization, which is one of powerful meta-heuristic method. The practical usefulness of the approach is illustrated with a case study involving satellite cities in Seoul Metrolitan Area including several candidate area where this kind systems have not been installed yet and already operating area. Our proposed approach produced plausible solutions with rapid computational time and a little deviation from optimal solution obtained by CPLEX Optimizer. Also we can find that particle swarm optimization method can be used as efficient method with various constraints. Hence based on this results, we can grasp a clear insight into the impact of depot location and relocation policy schemes on the profitability of such systems.

• 산업경영시스템학회지
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• 제43권4호
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• pp.67-75
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• 2020

This paper proposes a methodology for gantry route optimization in order to maximize the productivity of a odd-type surface mount device (SMD). A odd-type SMD is a machine that uses a gantry to mount electronic components on the placement point of a printed circuit board (PCB). The gantry needs a nozzle to move its electronic components. There is a suitability between the nozzle and the electronic component, and the mounting speed varies depending on the suitability. When it is difficult for the nozzle to adsorb electronic components, nozzle exchange is performed, and nozzle exchange takes a certain amount of time. The gantry route optimization problem is divided into the mounting order on PCB and the allocation of nozzles and electronic components to the gantry. Nozzle and electronic component allocation minimized the time incurred by nozzle exchange and nozzle-to-electronic component compatibility by using an mixed integer programming method. Sequence of mounting points on PCB minimizes travel time by using the branch-and-price method. Experimental data was made by randomly picking the location of the mounting point on a PCB of 800mm in width and 800mm in length. The number of mounting points is divided into 25, 50, 75, and 100, and experiments are conducted according to the number of types of electronic components, number of nozzle types, and suitability between nozzles and electronic components, respectively. Because the experimental data are random, the calculation time is not constant, but it is confirmed that the gantry route is found within a reasonable time.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.53-63
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• 2017

The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.

• 대한교통학회지
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• 제17권2호
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• pp.127-135
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• 1999

간선도로상에서의 교통혼잡해소를 위해서 연동화기법이 많이 사용되지만 기존 모형들은 간선도로를 한 개의 교통축으로 하여 신호를 최적화해주기 때문에 이들과 교차되는 교차도로는 물론 일반적인 도로망체계에서의 교통흐름을 고려하지 못한다. 그리고 도로망 제어가 가능한 모형의 경우에도 루프로 형성되어야 하고 현시순서에 제약이 따르기 때문에 적용상에 한계가 있다. 따라서 본 연구에서는 이러한 문제들을 해결하고자 이동류들을 이용하여 현시순서를 최적화하고 이를 일반적인 도로망에 적용할 수 있는 모형을 제시하였다. 모형적용 결과 본 모형은 다양한 도로망 구조나 교차로 형태를 반영하여 도로망에서의 차량흐름을 동시에 제어해주는 신호계획를 산정해 낼 수 있었다. 본 모형의 사용으로 일반적인 도로망체계에서 각 도로들의 교통량과 용량을 고려하는 연동처리가 가능해져 도시가로망에서의 교통흐름을 원활히 해줄 것으로 기대된다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.89-93
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• 2009

홍수기에 집중되는 하천유출량을 갈수기에 적절히 활용하기 위한 대표적인 시설이 댐이다. 제한된 용수공급량을 적절히 분배해 용수수요량을 만족시키면서 미래 갈수기시 용수공급을 위한 댐 저류량을 조절하는 것이 댐 운영의 중요한 목적 중 하나이다. 본 연구에서는 댐 저류량에 따라 댐 계획방류량을 일정비율 줄여주는 Hedging Rule을 5단계로 적용하여 댐의 상시만수위 저류량에 대한 실제 저류량의 편차 절대치 합, 수요에 대한 용수공급 부족량의 합, 그리고 하천유지유량에 대한 하천유량 부족량의 합을 목적함수로 하여 혼합정수 선형계획법(MILP, Mixed Integer Linear Programming)으로 식을 구성하였다. 한강수계의 다목적댐인 충주, 횡성, 소양강 댐과 용수전용댐인 광동 댐, 그리고 발전용 댐이지만 비교적 큰 저류용량을 가진 화천 댐을 댐 연계 운영 대상으로 하여 수자원장기종합계획의 2003년 유출량 및 수요량 자료와 댐운영실무편람의 댐 계획방류량 자료를 10일 단위로 입력하여 GAMS/CPLEX를 이용해 최적화하였다. 그 결과 생공용수 수요량 99.99%, 농업용수 수요량 99.91%, 그리고 하천유지용수 수요량 99.24%를 충족시키면서, 댐 저류율이 66.54%에서 86.39%로 증가하였다.

• 산업공학
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• 제16권4호
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• pp.485-495
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• 2003

This paper reports on the application of the integration of mathematical programming model and database in a decision support system (DSS) for the planning of the multi-reservoir operating system. The DSS is based on a multi-objective, mixed-integer goal programming (MIGP) model, which can generate efficient solutions via the weighted-sums method (WSM). The major concern of this study is seamless, efficient integration between the mathematical model and the database, because there are significant differences in structure and content between the data for a mathematical model and the data for a conventional database application. In order to load the external optimization results on the database, we developed a systematic way of naming variable/constraint so that a rapid identification of variables/constraints is possible. An efficient database structure for planning of the multi-reservoir operating system is presented by taking advantage of the naming convention of the variable/constraint.