• 한국산학기술학회논문지
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• 제19권7호
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• pp.258-264
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• 2018

본 논문은 마이크로 그리드 최적 운영을 위해 Differential Search (DS) 알고리즘을 적용하였다. DS 알고리즘은 이주하는 생물의 유사 브라운 운동 형태의 임의보행 (random-walk)을 모의하여 개발된 알고리즘이다. DS 알고리즘은 다른 최적화 알고리즘과 달리 한 개 이상의 개체를 동시에 사용 할 수 있고, 유사 최적해중에서 전역 최적 해를 선별하는 직진성 특성으로 multi-modal 함수들의 해법을 위한 성공적인 탐색 전력을 지니고 있으며, 높은 비선형성과 불연속성을 갖는 전력계통의 다른 분야에도 효율적으로 적용될 수 있다. 마이크로 그리드 시스템은 풍력 발전기, 디젤발전기, 연로전지 및 태양광 발전기로 구성된다. 풍력 발전기는 가변 출력특성을 이용하여 모델링 하였다. 연료비용과 연료가 전력으로 변환되는 경우의 효율을 포함시켜 시스템의 비용을 최소화 하였으며, 마이크로 그리드 단독 운용에 관해서만 분석하였다. 본 연구는 신재생 에너지원 기반의 마이크로 그리드의 최적 운영에 대해 코딩의 단순성, 빠른 수렴 속도, 정확성 및 효율성을 갖춘 DS 알고리즘을 적용하여 다른 알고리즘의 최적 값과 비교하였다.

• 전기학회논문지
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• 제62권10호
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• pp.1451-1457
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• 2013

Recently, new concept of energy systems such as microgrid, smart grid, supergrid, and energy network has been introducing. In this paper, the concept of the centralized micro-energy network, which is an energy community of a building group without district heating system, is introduced. In addition, a mathematical model for optimal operation of the micro-energy network as a main function of an energy management system (EMS) for the micro-energy network is proposed. In order to show the validation, the proposed model is tested through the simulation and analyzed.

• 조명전기설비학회논문지
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• 제26권12호
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• pp.50-55
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• 2012

This paper presents an application of optimization method for efficient operation in micro grid. For operational efficiency, the objective function in a diesel generator consists of the fuel cost function similar to the cost functions used for the conventional fossil-fuel generating plants. The wind turbine generator is modeled by the characteristics of variable output. The cost function of fuel cell plant considers the efficiency of fuel cell. Particle swarm optimization(PSO) and sequential quadratic programming(SQP) are used for solving the problem of microgrid system operation. Also, from the results this paper presents the way to attend power markets which can buy and sell power from upper lever grids by connecting a various generation resources to micro grid.

• 전기학회논문지
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• 제65권2호
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• pp.239-246
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• 2016

In recent years, the power demand has been increasing steadily and the occurrence of maximum power demand has been moving from the summer season to the winter season in Korea. And since the control of electric power supply and demand is more important under those situations, a micro-grid system began to emerge as a keyword for the sTable operation of electric power system. A micro-gird power system is composed of various kinds of distributed generators(DG) such as small diesel generator, wind turbine, photo-voltaic generator and energy storage system(ESS). This paper introduces a method to determine the optimal capacities of the distributed generators which are installed in a stand-alone type of microgrid power system based on the fundamental proportion of diesel generator. At first, the fundamental proportion of diesel generator will be determined by changing from 0 to 50 percent. And then we will optimize the capacities of renewable energy resources and ESS according to load patterns. Lastly, after recalculating the capacity of ESS with consideration for SOC constraints, the optimal capacities of distributed generators will be decided.

• KEPCO Journal on Electric Power and Energy
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• 제4권2호
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• pp.67-73
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• 2018

마이크로 그리드 환경에는 변압기, 스위치, 에너지저장장치 등 많은 종류의 전력 설비가 존재하지만, IoT 기술의 발달에 따라 온도, 압력, 습도와 같은 센서 정보를 취득할 수 있는 기회를 제공하고 있다. 기존의 마이크로 그리드 환경에서는 IEC 61850 표준에서 정의하고 있는 MMS 등의 통신 프로토콜을 준용하여 전력 설비와 플랫폼 간 통합 운용되고 있다. 그렇기 때문에 IoT 데이터를 수용하기 위해서는 IEC 61850 기반으로 구성된 데이터 수집 장치(FEP)에 IoT 데이터를 연계해 줄 수 있는 게이트웨이 기술이 필요하다. 본 논문에서는 마이크로그리드 운영 시스템 연계를 위한 IEC 61850기반 IoT 게이트웨이 플랫폼 프로토타입을 제안하고자 한다. 게이트웨이 플랫폼은 IoT 프로토콜(MQTT, CoAP, AMQP) 인터페이스 모듈과 데이터베이스, IEC 61850서버로 구성되어 있다. 데이터베이스의 경우, JSON 데이터를 저장하기 위해 오픈소스 기반의 NoSQL 데이터베이스인 Hbase와 MongoDB를 이용하였다. IoT 프로토콜을 검증하기 위해 라즈베리파이 아두이노 인텔 에디슨 SoC 기반 전력 IoT 디바이스 시뮬레이터를 이용하였고, IEC 61850은 Sisco's MMS EASY Lite를 이용하여 IoT 프로토콜과 IEC 61850 프로토콜간의 상호호환성을 검증하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2012년도 추계학술발표대회
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• pp.1235-1237
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• 2012

연료전지는 온실가스를 배출하지 않기 때문에 차세대 친환경에너지로 평가 받고 있으며, 추후 마이크로그리드에 많은 도입이 예상된다. 이에 본 논문에서는 전력과 열을 동시에 생산하는 연료전지를 고려한 마이크로그리드의 최적운용계획을 수립하고 사례연구를 통하여 제시된 수리적 모델의 타당성을 입증하고자 한다.

• Journal of Electrical Engineering and Technology
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• 제7권6호
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• pp.869-875
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• 2012

Because of the nature of wind, the output power of wind turbines fluctuates according to wind speed variation. Therefore, many countries have set up wind-turbine interconnection standards usually named as Grid-Code to regulate the output power of wind farms to improve power system reliability and power quality. This paper proposes three operation modes of wind farms such as maximum power point tracking (MPPT) mode, single wind turbine control mode and wind farm control mode to control the output power of wind turbines as well as overall wind farms. This paper also proposes an operation scheme of wind farm to alleviate power fluctuation of wind farm by choosing the appropriate control mode and coordinating multiple wind turbines in consideration of grid conditions. The performance of the proposed scheme is verified via simulation studies in PSCAD/EMTDC with doubly-fed induction generator (DFIG) based wind turbine models.

• 조명전기설비학회논문지
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• 제29권5호
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• pp.34-40
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• 2015

This paper presents an application of Differential Search (DS) meta-heuristic optimization algorithm for optimal operation of micro grid system. DS algorithm has the benefit of high convergence rate and precision compared to other optimization methods. The micro grid system consists of a wind turbine, a diesel generator, and a fuel cell. The simulation is applied to micro grid system only. The wind turbine generator is modeled by considering the characteristics of variable output. One day load data which is divided every 20 minute and wind resource for wind turbine generator are used for the study. The method using the proposed DS algorithm is easy to implement, and the results of the convergence performance are better than other optimization algorithms.

• 전기전자학회논문지
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• 제22권3호
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• pp.672-679
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• 2018

Recently, microgrid (MG) has been proposed as one of the most critical solutions for various energy problems. For the optimal and economic operation of MGs, it is very important to forecast the load profile. However, it is not easy to predict the load accurately since the load in a MG is small and highly variable. In this paper, we propose an artificial neural network (ANN) based method to predict the energy use in campus buildings in short-term time series from one hour up to one week. The proposed method analyzes and extracts the features from the historical data of load and temperature to generate the prediction of future energy consumption in the building based on sparsified K-means. To evaluate the performance of the proposed approach, historical load data in hourly resolution collected from the campus buildings were used. The experimental results show that the proposed approach outperforms the conventional forecasting methods.

• 전기학회논문지P
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• 제67권2호
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• pp.94-99
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• 2018

Depending on how the energy storage system(ESS) is used in a system that can construct a microgrid by using an independent power source such as campus, surplus power can be generated that can not be charged to the ESS. For example, assuming that heat is supplied by a fuel cell in the case of a system in which thermal self-sustaining is prioritized, the fuel cell capacity required differs depending on the heat load. The amount of surplus power that can not be stored in the ESS will appear differently depending on the load operation of the fuel cell for each cycle. This power is hydrogenated through a water electrolytic device to present the amount of hydrogen energy that can be operated for each cycle. Therefore, this paper propose the possibility of utilizing University campus as a hydrogen station.