• 전기학회논문지P
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• 제66권4호
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• pp.169-176
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• 2017

This paper presents research on low-voltage microgrids to maintain a continuous power supply to critical loads on grid-connected islands in Korea. The low-voltage microgrids of this paper focused on that changes public office buildings into uninterrupted microgrids by autonomous operation. For this, a microgrid controller (MGC) and a power conditioning system (PCS) that allow a seamless transfer between grid-connected and grid-isolated operation are proposed. The proposed PCS operates with a silicon controlled rectifier (SCR) switch and employs a simple structure. It supplies power continuously without operators through a coordinated operation between MGC and PCS. In addition, proposed MG has a schedule operation for minimizing electricity charges and provides ancillary services that enable the utilization of resources according to the operation purpose of utility distribution networks. To demonstrate the uninterrupted low-voltage microgrid proposed in this study, a microgrid was implemented and tested in a public office building in Anjwa Island, Jeollanam-do in Korea. A seamless, autonomous operation history, despite system disturbances, was obtained through a long-term demonstration of operation. The results showed that the proposed microgrid technology can be used to achieve energy resilience in grid-connected island areas.

• 전기학회논문지
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• 제63권10호
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• pp.1337-1346
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• 2014

Power system technologies in the area of smart grid are being converged with communication system technologies or information technologies(IT). This interdisciplinary action affects on two parts vigorously so that IT has become a essential part of power industry. But terminologies of two parts are confused and it is necessary that these are standardized to develop the industry. The writing system of the Open Korean Knowledge Dictionary for standardization of smart grid terminologies which are IEC TC 57 glossary and non-glossary is proposed. The writing system includes the process of collection, writing guideline and standardization of terminologies. Writing results of 90,000 terminologies for electricity, communication and computer fields including smart grid terminologies, which are registered in the Open Korean Knowledge Dictionary, are shown. The system provides the capability of collection and delivery of academic society opinions for the selected and interpreted terminologies through the internet for standardization and industry propagation of smart grid terminologies.

• 한국에너지공학회:학술대회논문집
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• 한국에너지공학회 2000년도 추계 학술발표회 논문집
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• pp.221-227
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• 2000

본 연구에서 대상아파트에 적용할 열병합발전 시스템의 적정 용량은 투자회수기간 및 이익발생량 등을 고려할 때 약 300kW(전기출력)급으로 나타났으며, 열병합발전 시스템의 운전 모드는 전기부하추종을 바탕으로 하여 아파트 단지의 전기수요의 기저부하를 담당하도록 하며, 아파트 단지의 전기부하가 발전기 정격용량(300kW) 이상의 범위에서는 한전전기와 계통 연계되어 운전토록 하고, 전기부하가 발전기 정격용량의 50% 부하 이상의 범위에서는 발전기만 운전하고, 전기부하가 발전기 정격용량의 50% 부하 이하에서는 발전기를 정지하고 한전전기만으로 운전하는 것이 바람직한 것으로 나타났다.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2011년도 춘계학술대회 초록집
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• pp.110.1-110.1
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• 2011

This study analyzed the performance of long term operation photovoltaic system The 50 kWp grid connected photovoltaic system which was installed at KEPRI site in 1999 has been operated more than 12 years. In order to acquire long term operation characteristics of medium size photovoltaic system, the operation test data related on power generation electricity and capacity factor of 50 kWp system, which have been collected since 1999, were analysed. From the analysing results, 57.7 MWh in annual power generation electricity of 50 kWp photovoltaic system in 1999 has been decreased 49.1 MWh in 2005 and reached 38.0 MWh in 2010. In addition to, the capacity factor of 50 kWp photovoltaic system also showed 13.2 % in 1999, 11.2% in 2005 and finally reached 8.8% in 2011. The operation test data showed a trend of decreasing of generation electricity and capacity factor during the 12 years operation time and we guessed that was caused by solar cell performance degradation and decreasing of PCS system efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.5712-5728
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• 2017

Recently, there are many studies, that considering green wireless cellular networks, have taken the energy consumption of the base station (BS) into consideration. In this work, we first introduce an energy consumption model of multi-mode sharing BS powered by multiple energy sources including renewable energy, local storage and power grid. Then communication load requests of the BS are transformed to energy demand queues, and battery energy level and worst-case delay constraints are considered into the virtual queue to ensure the network QoS when our objective is to minimize the long term electricity cost of BSs. Lyapunov optimization method is applied to work out the optimization objective without knowing the future information of the communication load, real-time electricity market price and renewable energy availability. Finally, linear programming is used, and the corresponding energy efficient scheduling policy is obtained. The performance analysis of our proposed online algorithm based on real-world traces demonstrates that it can greatly reduce one day's electricity cost of individual BS.

• Journal of Electrical Engineering and Technology
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• 제13권1호
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• pp.38-50
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• 2018

Spatio-temporal load forecasting (STLF) is a foundation for building the prediction-based power map, which could be a useful tool for the visualization and tendency assessment of urban energy application. Constructing one point-forecasting model for each electricity cell in the geographic space is possible; however, it is unadvisable and insufficient, considering the aggregation features of electricity cells and uncertainties in input variables. This paper presents a new STLF method, with a data-driven framework consisting of 3 subroutines: multi-level clustering of cells considering their aggregation features, load regression for each category of cells based on SLS-SVRNs (sparse least squares support vector regression networks), and interval forecasting of spatio-temporal load with sampled blind number. Take some area in Pudong, Shanghai as the region of study. Results of multi-level clustering show that electricity cells in the same category are clustered in geographic space to some extent, which reveals the spatial aggregation feature of cells. For cellular load regression, a comparison has been made with 3 other forecasting methods, indicating the higher accuracy of the proposed method in point-forecasting of spatio-temporal load. Furthermore, results of interval load forecasting demonstrate that the proposed prediction-interval construction method can effectively convey the uncertainties in input variables.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.937-944
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• 2022

Electric vehicles (EVs) have been growing to reduce energy consumption and greenhouse gas (GHG) emissions in the transportation sector. The increasing number of EVs requires adequate recharging infrastructure, and at the same time, adopts low- or zero-emission electricity production because the GHG emissions are highly dependent on primary sources of electricity production. Although previous research has studied solar photovoltaic (PV) -integrated EV charging stations, it is challenging to optimize spatial areas between where the charging stations are required and where the renewable energy sources (i.e., solar photovoltaic (PV)) are accessible. Therefore, the primary objective of this research is to support decisions of siting EV charging stations using a spatial data clustering method integrated with Geographic Information System (GIS). This research explores spatial relationships of PV power outputs (i.e., supply) and traffic flow (i.e., demand) and tests a community in the state of Indiana, USA for optimal sitting of EV charging stations. Under the assumption that EV charging stations should be placed where the potential electricity production and traffic flow are high to match supply and demand, this research identified three areas for installing EV charging stations powered by rooftop PV in the study area. The proposed strategies will drive the transition of existing energy infrastructure into decentralized power systems. This research will ultimately contribute to enhancing economic efficiency and environmental sustainability by enabling significant reductions in electricity distribution loss and GHG emissions driven by transportation energy.

• ETRI Journal
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• 제37권2호
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• pp.273-282
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• 2015

Vehicle-to-grid presents a mechanism to meet the key requirements of an electric power system, using electric vehicles (EVs) when they are parked. The most economic ancillary service is that of frequency regulation, which imposes some constraints regarding the period and duration of time the vehicles have to be connected to the grid. The majority of research explores the profitability of the aggregator, while the perspective of the EV fleet owner, in terms of their need for usage of their fleet, remains neglected. In this paper, the optimal allocation of available vehicles on a day-ahead basis using queuing theory and fuzzy multi-criteria methodology has been determined. The proposed methodology is illustrated on the daily scheduling of EVs in an electricity distribution company.

• International Journal of Advanced Culture Technology
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• 제2권2호
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• pp.11-14
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• 2014

In the smart grid, it will be possible to communicate with the consumers for the purposes of monitoring and controlling their power consumption without disturbing their business or comfort. This will bring easier administration capabilities for the utilities. On the other hand, consumers will require more advanced home automation tools which can be implemented by using advanced sensor technologies. For instance, consumers may need to adapt their consumption according to the dynamically varying electricity prices which necessitates home automation tools. This paper tries to combine neural network and nonlinear autoregressive with exogenous variable (NARX) class for next week electric load forecasting. The suitability of the proposed approach is illustrated through an application to electric load consumption data. The suggested system provides a useful and suitable tool especially for the load forecasting.

• 한국경영과학회지
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• 제39권1호
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• pp.49-67
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• 2014

This paper proposes a real time pricing model for smart grid considering consumers' behavior, real time price elasticity, and exogenous price. Based on the proposed model, we found the weight of utility over cost is the most sensitive factor compared to other factors. Also, if the electricity price is set to be changed too sensitively to energy consumption, it is warned that real time pricing sometimes can cause increment of peak-time demand and volatility. Finally, real time pricing could be less efficient when the difference between the maximum and the minimum consumption level is small.