• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1039-1046
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• 2017

Campus microgrid is designed and built by considering not only power generation but also power consumption management as connected microgrid type because the main goal of the campus microgrid is to save power consumption costs. There are many functions to achieve the goal and they are mainly to use generation-based functions such as islanding operation for peak management and for emergency events. In power distribution operation, Conservation Voltage Reduction (CVR) is applied in order to reduce power consumption. The CVR is defined as a function for load consumption reduction by voltage reduction in order to reduce peak demands and energy consumption. However, application of CVR to microgrid is difficult because the microgrid cannot control a tap of transformer in a substation and the microgrid normally is not designed with phase modifying equipment like a step-voltage-regulator which can control voltage in power distribution system operation. In addition, an impact of the CVR is depended on load characteristics such as a normal load, a rated power, and synchronous motors. Therefore, this paper proposes an application of CVR using linear voltage control based AVR in campus microgrid with power consumption reduction considering characteristics of load and component in the microgrid. The proposed system can be applied to each buildings by a configuration of power distribution cables; and the application results and CVR factor are presented in this paper.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.277-282
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• 2020

The construction of medium-and large-sized microgrid systems by unit area, which is being promoted worldwide, is being developed and expanded in the form of efficient operation of electric grids and independent operation in preparation for power emergencies. Therefore, for the development of the domestic electricity industry, it is urgent to analyze the current status and technology of relevant international standardization, and to make international standardization of domestic standard (draft) on the matters that need to be enacted and newly established. Campus microgrid implements smart grid element technologies such as Integrated Energy Management System(EMS), Distributed Power(DG), Energy Storage System(ESS), Demand Response(DR), and Electric Vehicle(EV) in a university campus. As a system that reduces energy use and improves energy use efficiency and energy independence, standardization is established to secure interoperability and reliability of such systems.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.2
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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.

• Journal of IKEEE
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• v.22 no.3
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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.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.1-6
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• 2024

In order to increase the use of electric vehicles (EVs) and minimize grid strain, microgrid using renewable energy must take an important role. Microgrid may use fossil fuels such as small diesel power, but in many cases, they can be supplied with energy from renewable energy, which is an eco-friendly energy source. However, renewable energy such as solar and wind power have variable output characteristics. Therefore, in order to meet the charging and discharging energy demands of electric vehicles and at the same time supply load power stably, it is necessary to review the configuration of electric vehicle charging infrastructure that utilizes diesel power or electric vehicle-to-grid (V2G) as a parallel energy source in the microgrid. Against this background, this study modelized a microgrid that can stably supply power to loads using solar power, wind power, diesel power, and V2G. The proposed microgrid uses solar power and wind power generation as the primary supply energy source to respond to power demand, and determines the operation type of the load's electric vehicles and the rotation speed of the load synchronous machine to provide stable power from diesel power for insufficient generations. In order to verify the system performance of the proposed model, we studied the stable operation plan of the microgrid by simulating it with MATLAB /Simulink.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.461-462
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• 2015

세계적으로 마이크로그리드에 이목이 집중되고 있는 현재 상황에서 DER(Distributed Energy Resources : 분산형 독립전원)의 역할이 대두되고 있다. 캠퍼스 마이크로그리드는 대학교의 캠퍼스를 하나이상의 DER로 선정하여 피크 시 교내 전기수요의 일부분을 해소할 수 있는 전력망 기반의 네트워크 시스템이다. 해외에서는 이미 캠퍼스 마이크로그리드 성공사례를 보여주었고, 이후 많은 캠퍼스에서 캠퍼스 마이크로그리드를 벤치마킹하고 있다. 본 논문에서는 캠퍼스 마이크로그리드에 필요한 DER을 구성하기 전 캠퍼스 내의 건물별, 계절별 전력수요 특성을 분석하고자 한다.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.531-532
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• 2015

마이크로그리드 내에서 기존의 중앙 제어 방식은 중앙 제어기가 방대한 데이터의 수집 및 처리를 포함해 제어 결정까지 대부분을 부담하여 확장성과 유연성이 좋지 않다. 따라서 이를 위한 해결책으로 부담을 나눌 수 있는 분산 제어가 필요하다. 본 논문에서는 Multi Agent System(MAS)를 기반으로 일치 알고리즘을 이용한 정보 공유를 통해 유닛들의 분산 제어를 제시하였고 캠퍼스 마이크로그리드에 대한 적용가능성을 분석했다.

• New & Renewable Energy
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• v.18 no.1
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• pp.35-45
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• 2022

The renewable energy based MG is becoming one of the prominent solutions for greenhouse gas and constructing less power lines. However, how to procure the economics of MG considering the CO₂ emission and utility network impact is one of major issues as the proportion of renewable resource increases. This paper proposes the feasibility study scheme of campus MG and shows that the LCOE and CO₂ emission can be reduced by utilizing the excess power and introducing hydrogen system and plus DR. For this, the three cases: (a) adding the PV and selling excess power to utility, (b) producing and selling hydrogen using excess power, and (c) participating in plus DR are considered. For each case, not only the topology and component capacity of MG to secure economic feasibility, but also CO₂ emission and utility network effects are derived. If an electrolyzer with a capacity of 400 kW participates in plus DR for 3,730hours/year, the economic feasibility is securable if plus DR settlement and hydrogen sale price are more than 7.08¢/kWh and 8.3USD/kg or 6.25¢/kWh and 8.6USD/kg, respectively. For this end, continuous technical development and policy support for hydrogen system and plus DR are required.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.617-634
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• 2022

Purpose: This paper introduces Pohang University of Science Technology (POSTECH) advanced metering infrastructure (AMI) and Open Innovation Big Data Center (OIBC) platform and analysis results of electricity consumption data collected via the AMI in POSTECH campus. Methods: We installed 248 sensors in seven buildings at POSTECH for the AMI and collected electricity consumption data from the buildings. To identify the amounts and trends of electricity consumption of the seven buildings, electricity consumption data collected from March to June 2019 were analyzed. In addition, this study compared the differences between the amounts and trends of electricity consumption of the seven buildings before and after the COVID-19 outbreak by using electricity consumption data collected from March to June 2019 and 2020. Results: Users can monitor, visualize, and download electricity consumption data collected via the AMI on the OIBC platform. The analysis results show that the seven buildings consume different amounts of electricity and have different consumption trends. In addition, the amounts of most buildings were significantly reduced after the COVID-19 outbreak. Conclusion: POSTECH AMI and OIBC platform can be a good reference for other universities that prepare their own microgrid. The analysis results provides a proof that POSTECH needs to establish customized strategies on reducing electricity for each building. Such results would be useful for energy-efficient operation and preparation of unusual energy consumptions due to unexpected situations like the COVID-19 pandemic.

• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.13-21
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• 2016

In this paper we are trying to explain the effect of temperature on polymer membrane exchange water electrolysis (PEMWE) and polymer membrane exchange fuel cell (PEMFC) simultaneously. A comprehensive studying approach is proposed and applied to a 50Watt PEM fuel cell system in the laboratory. The monitoring process is carried out through wireless LoRa node and gateway network concept. In this experiment, temperature sensor measure the temperature level of electrolyzer, fuel cell stack and $H_2$ storage tank and transmitted the measured value of data to the management control unit (MCU) through the individual node and gateway of each PEMWE and PEMFC. In MCU we can monitor the temperature and its effect on the performance of the fuel cell system and control it to keep the lower heating value to increase the efficiency of the fuel cell system. And we also proposed a mathematical model and operation algorithm for PEMWE and PEMFC. In this model, PEMWE gives higher efficiency at lower heating level where as PEMFC gives higher efficiency at higher heating value. In order to increase the performance of the fuel cell system, we are going to monitor, communicate and control the temperature and pressure of PEMWE and PEMFC by installing these systems in a building of university which is located in the southern part of Korea.